#
Title
1

1010: Fable 5 as Advisor: Anthropic's Two-Model Pattern for Smarter, Cheaper Agents

2

1009: How AI Is Quietly Saving Lives, with Steve Mock

3

1008: The AI-Native Startup Playbook

4

1007: How to Find Solid Career Ground in the AI Era, with 80,000 Hours Founder Ben Todd

5

1006: In Case You Missed It in June 2026

6

1005: People Skills for Analytical Thinkers, with Bestselling Author Gilbert Eijkelenboom

7

1004: Recursive Self-Improvement

8

1003: Building an AI Data Center End to End, with Lightning AI’s Frank Basso

9

1002: Fable 5: The Full Story from Capabilities to Drama

10

1001: How AI Erased My Career Moat, an Episode #1001 Special: Jon Krohn interviewed by Kirill Eremenko

11

1000: Ten Years of the Super Data Science Podcast, with Jon, Kirill and Special Guests

12

999: What's Left to Build When Software Is Free, with Chip Huyen

13

998: In Case You Missed It in May 2026

14

997: How This Text-to-Video-Game AI Startup Hit 20M Users

15

996: TrueFoundry’s Nikunj Bajaj on How to Get $100M Returns on AI Agent Deployments

16

995: End-to-End Foundation Models for the Energy Industry, with Jazmia Henry

17

994: AI’s Putting Recent Grads Out of Work; Here’s How to Get Hired Anyway!

18

993: How to Build AI-First Organizations, with Jacob Miller and Jeremy Mumford

19

992: Tokenmaxxing vs AI Hardware Bottlenecks

20

991: Pair Programming with AI in Your Python Notebook, with Dr. Trevor Manz

21

990: Inside Mythos: Anthropic's Locked-Down Frontier Model

22

989: Security for Mythos-Era Agentic Risks, with Rubrik’s Anneka Gupta and Cal Al-Dhubaib

23

988: In Case You Missed It in April 2026

24

987: AI Infrastructure, Ray, and Why Nonlinear Careers Win, with Linda Haviv

25

986: Building Hardware is Hard but AI Agents Help, with Kishore Subramanian

26

985: The Four Types of Memory Every AI Agent Needs, with Richmond Alake

27

984: Building AI Agents Where 99.9% Accuracy Isn't Good Enough, with Raju Malhotra

28

983: AI in the Classroom: How a Top Elementary School Is Doing It Right, with Principal Traci Walker Griffith

29

982: In Case You Missed It in March 2026

30

981: How Data Engineers Are “10x’ing” Themselves With Agents, feat. Matt Glickman

31

980: AI Making Theoretical Physics Breakthroughs

32

979: Agentic Data Management and the Future of Enterprise AI, with Rohit Choudhary

33

978: A Post-Transformer Architecture Crushes Sudoku (Transformers Solve ~0%)

34

977: Attention, World Models and the Future of AI, with Prof. Kyunghyun Cho

35

976: NVIDIA’s Nemotron 3 Super: The Perfect LLM for Multi-Agent Systems

36

975: Unmetered Intelligence is Heralding the Next Renaissance, with Zack Kass

37

974: When Will The AI Bubble Burst? How Bad Will It Be?

38

973: AI Systems Performance Engineering, with Chris Fregly

39

972: In Case You Missed It in February 2026

40

971: 90% of The World’s Data is Private; Lin Qiao’s Fireworks AI is Unlocking It

41

970: The “100x Engineer”: How to Be One, But Should You?

42

969: The Laws of Thought: The Math of Minds and Machines, with Prof. Tom Griffiths

43

968: Is AI Automating Away All Coding Jobs?

44

967: AI for the Physical World, with Samsara's Praveen Murugesan

45

966: The Moltbook Phenomenon: OpenClaw Unleashed

46

965: From PhD Side Project to $500M ARR: Will Falcon’s PyTorch Lightning Story

47

964: In Case You Missed It in January 2026

48

963: Reinforcement Learning for Agents, with Amazon AGI Labs’ Antje Barth

49

962: Wharton Prof Ethan Mollick on Why Your AI Strategy Is Already Obsolete

50

961: Distributed Artificial Superintelligence, with Dr. Vijoy Pandey

51

960: In Case You Missed It in December 2025

52

959: Building Agents 101: Design Patterns, Evals and Optimization (with Sinan Ozdemir)

53

958: Without Trusted Context, Agents are Stupid (featuring Salesforce’s Rahul Auradkar)

54

957: How AI Agents Are Automating Enterprise Data Operations, with Ashwin Rajeeva

55

956: From Agent Demo to Enterprise Product (with Ease!) feat. Salesforce’s Tyler Carlson

56

955: Nested Learning, Spatial Intelligence and the AI Trends of 2026, with Sadie St. Lawrence

57

954: Recap of 2025 and Wishing You a Wonderful 2026

58

953: Beyond “Agent Washing”: AI Systems That Actually Deliver ROI, with Dell’s Global CTO John Roese

59

952: How to Avoid Burnout and Get Promoted, with “The Fit Data Scientist” Penelope Lafeuille

60

951: Context Engineering, Multiplayer AI and Effective Search, with Dropbox’s Josh Clemm

61

950: Happy Holidays from All of Us at the SuperDataScience Podcast

62

949: Why AI Keeps Failing Society, with Stanford professor Alex “Sandy” Pentland

63

948: In Case You Missed It in November 2025

64

947: How to Get Hired at Top Firms like Netflix and Spotify, with Jeff Li

65

946: How Robotaxis Are Transforming Cities

66

945: AI is a Joke, with Joel Beasley

67

944: Gemini 3 Pro: Google’s Back on Top

68

943: Creative Machines: AI in Music and Art, with Prof. Maya Ackerman

69

942: Odds of AGI by 2040? LEAP Expert Forecasts and Workforce Implications

70

941: Multi-Agent Human Societies, with Dr. Vijoy Pandey

71

940: In Case You Missed It in October 2025

72

939: Mixture-of-Experts and State-Space Models on Edge Devices, with Tyler Cox and Shirish Gupta

73

938: Frontier AI Agents for Data Science, with Sphinx’s Rohan Kodialam

74

937: How to Design AI-First Products, with Marc Dupuis

75

936: LLMs Are Delighted to Help Phishing Scams

76

935: Global Issues Accelerated by AI (with Solutions), feat. Stephanie Hare

77

934: Is AI Replacing Junior Workers?

78

933: Future-Proofing Your Career in the AI Era, feat. Sheamus McGovern

79

932: Should You Build or Buy Your AI Solution? With Larissa Schneider

80

931: Boost Your Profits with Mathematical Optimization, feat. Jerry Yurchisin

81

930: In Case You Missed It in September 2025

82

929: Dragon Hatchling: The Missing Link Between Transformers and the Brain, with Adrian Kosowski

83

928: The “Lethal Trifecta”: Can AI Agents Ever Be Safe?

84

927: Automating Code Review with AI, feat. CodeRabbit’s David Loker

85

926: AI is Disrupting the Legal Industry: Are Paralegals Doomed?

86

925: AI, Automation and the Future of Work, with Oxford’s Prof. Carl Benedikt Frey

87

924: 95% of Enterprise AI Projects Fail (Per MIT Research)

88

923: Graph Algorithms, GraphRAG and Causal Graphs, with Graph Guru Amy Hodler

89

922: AI for Manufacturing and Industry, with Hugo Dozois-Caouette

90

921: NPUs vs GPUs vs CPUs for Local AI Workloads, with Dell’s Ish Shah and Shirish Gupta

91

920: In Case You Missed It in August 2025

92

919: Hopes and Fears of AGI, with All-Time Bestselling ML Author Aurélien Géron

93

918: Multi-Agent Systems with CrewAI

94

917: 8 Steps to Becoming an AI Engineer, with Kirill Eremenko

95

916: The 5 Key GPT-5 Takeaways

96

915: How to Jailbreak LLMs (and How to Prevent It), with Michelle Yi

97

914: Data Lakes 101 (and Why They’re Key for AI Models), with Oz Katz

98

913: LLM Pre-Training and Post-Training 101, with Julien Launay

99

912: In Case You Missed It in July 2025

100

911: The Future of Python Notebooks is Here, with Marimo’s Dr. Akshay Agrawal

101

910: AI is Disrupting Journalism: The Good, The Bad and The Opportunity

102

909: Causal AI, with Dr. Robert Usazuwa Ness

103

908: AI Agents Blackmail Humans 96% of the Time (Agentic Misalignment)

104

907: Neuroscience, AI and the Limitations of LLMs, with Dr. Zohar Bronfman

105

906: How Prof. Jason Corso Solved Computer Vision’s Data Problem

106

905: Why RAG Makes LLMs Less Safe (And How to Fix It), with Bloomberg’s Dr. Sebastian Gehrmann

107

904: A.I. is Disrupting the Entire Advertising Industry

108

903: LLM Benchmarks Are Lying to You (And What to Do Instead), with Sinan Ozdemir

109

902: In Case You Missed It in June 2025

110

901: Automating Legal Work with Data-Centric ML (feat. Lilith Bat-Leah)

111

900: 95-Year-Old Annie on How to Stay Healthy and Happy

112

899: Landing $200k+ AI Roles: Real Cases from the SuperDataScience Community, with Kirill Eremenko

113

898: My Four-Hour Agentic AI Workshop is Live and 100% Free

114

897: How to Enable Enterprise AI Transformation, with Strategy Consultant Diane Hare

115

896: AI (Probably) Isn’t Taking Your Job (At Least Anytime Soon)

116

895: The Future of Enterprise AI: Investor Shaun Johnson Reveals What Actually Works

117

894: In Case You Missed It in May 2025

118

893: How to Jumpstart Your Data Career (by Applying Like a Scientist), with Avery Smith

119

892: We’re In The AI “Trough of Disillusionment” (and that’s Great!)

120

891: Conversational AI is Overhauling Data Analytics, with Martin Brunthaler

121

890: The “State of AI” Report 2025

122

889: AI-Powered Virtual Reality: The Future of Education and Entertainment, with Mary Spio

123

888: Teams of Agents: The Next Frontier in AI Collaboration, with Mike Pell

124

887: Multi-Agent Teams, Quantum Computing and the Future of Work, with Dell’s Global CTO John Roese

125

886: In Case You Missed it In April 2025

126

885: Python Polars: The Definitive Guide, with Jeroen Janssens and Thijs Nieuwdorp

127

884: Model Context Protocol (MCP) and Why Everyone’s Talking About It

128

883: Blackwell GPUs Are Now Available at Your Desk, with Sama Bali and Logan Lawler

129

882: 40x Hotter Than the Sun: The ASML Machines That Make AI Chips

130

881: Beyond GPUs: The Power of Custom AI Accelerators, with Emily Webber

131

880: Manus, DeepSeek and China’s AI Boom

132

879: Serverless, Parallel, and AI-Assisted: The Future of Data Science is Here, with Zerve’s Dr. Greg Michaelson

133

878: In Case You Missed It in March 2025

134

877: The Neural Processing Units Bringing AI to PCs, with Shirish Gupta

135

876: Hugging Face’s smolagents: Agentic AI in Python Made Easy

136

875: How Semiconductors Are Made (And Fuel the AI Boom), with Kai Beckmann

137

874: How AI is Transforming Baseball (with Lessons For All of Us)

138

873: Become Your Best Self Through AI Augmentation — feat. Natalie Monbiot

139

872: Microsoft’s “Majorana 1” Chip Brings Quantum ML Closer

140

871: NoSQL Is Ideal for AI Applications, with MongoDB’s Richmond Alake

141

870: OpenAI’s “Deep Research”: Get Days of Human Work Done in Minutes

142

869: AI Should Make Humans Wiser (But It Isn’t), with Varun Godbole

143

868: In Case You Missed It in February 2025

144

867: LLMs and Agents Are Overhyped, with Dr. Andriy Burkov

145

866: Bringing Back Extinct Animals like the Woolly Mammoth and Dodo Bird

146

865: How to Grow (and Sell) a Data Science Consultancy, with Cal Al-Dhubaib

147

864: OpenAI’s o3-mini: SOTA reasoning and exponentially cheaper

148

863: TabPFN: Deep Learning for Tabular Data (That Actually Works!), with Prof. Frank Hutter

149

862: In Case You Missed It in January 2025

150

861: From Pro Athlete to Data Engineer: Colleen Fotsch’s Inspiring Journey

151

860: DeepSeek R1: SOTA Reasoning at 1% of the Cost

152

859: BAML: The Programming Language for AI, with Vaibhav Gupta

153

858: Are You The Account Executive We’re Looking For?

154

857: How to Ensure AI Agents Are Accurate and Reliable, with Brooke Hopkins

155

856: The Fastest-Growing Jobs Are AI Jobs

156

855: Exponential Views on AI and Humanity’s Greatest Challenges, with Azeem Azhar

157

854: The Six Epochs of Intelligence Evolution

158

853: Generative AI for Business, with Kirill Eremenko and Hadelin de Ponteves

159

852: In Case You Missed It in December 2024

160

851: Quantum ML: Real-World Applications Today, with Dr. Florian Neukart

161

850: Continuous Calendar for 2025

162

849: 2025 AI and Data Science Predictions, with Sadie St. Lawrence

163

848: Happy Holidays from the SuperDataScience Podcast

164

847: AI Engineering 101, with Ed Donner

165

846: Making Enterprise Data Ready for AI, with Anu Jain and Mahesh Kumar

166

845: Tech is Our New Religion And It Needs Reformation, with Greg Epstein

167

844: In Case You Missed It in November 2024

168

843: Safe, Fast and Efficient AI, with Protopia’s Dr. Eiman Ebrahimi

169

842: Flexible AI Deployments Are Critical, with Chris Bennett and Joseph Balsamo

170

841: Andrew Ng on AI Vision, Agents and Business Value

171

840: Delicate Viticultural Robotics

172

839: Double Your Data Salary in 11 Months, with Jess Ramos

173

838: Consciousness and Machines, with Jennifer K. Hill

174

837: Career Success in the AI Era, with Deepali Vyas

175

836: How to Become Happier, with Dr. Nat Ware

176

835: AI Systems as Productivity Engines, with You.com’s Bryan McCann

177

834: In Case You Missed It in October 2024

178

833: The 10 Reasons AI Projects Fail, with Dr. Martin Goodson

179

832: The Anthropic CEO’s Techno-Utopia

180

831: PyTorch Lightning, Lit-Serve and Lightning Studios, with Dr. Luca Antiga

181

830: The “A.I.” Nobel Prizes (in Physics and Chemistry??)

182

829: Neuroscience Fueled by ML, with Prof. Bradley Voytek

183

828: Are “Citizen Data Scientists” A Myth? With Keith McCormick

184

827: Polars: Past, Present and Future, with Polars Creator Ritchie Vink

185

826: In Case You Missed It in September 2024

186

825: Data Contracts: The Key to Data Quality, with Chad Sanderson

187

824: Llama 3.2: Open-Source Edge and Multimodal LLMs

188

823: Virtual Humans and AI Clones, with Natalie Monbiot

189

822: NotebookLM: Jaw-Dropping Podcast Episodes Generated About Your Documents

190

821: The Skills You Need to Be an Effective Data Scientist, with Marck Vaisman

191

820: OpenAI's o1 "Strawberry" Models

192

819: PyTorch: From Zero to Hero, with Luka Anicin

193

818: In Case You Missed It in August 2024

194

817: The Positron IDE, Tidy NLP and MLOps with Dr. Julia Silge

195

816: Explaining AGI to a 94-Year-Old

196

815: Polars: Faster DataFrame Ops, with Marco Gorelli

197

814: Summer Reflections

198

813: Solving Business Problems Optimally with Data, with Jerry Yurchisin

199

812: The AI Scientist: Towards Fully Automated, Open-Ended Scientific Discovery

200

811: Scaling Data Science Teams Effectively, with Nick Elprin

201

810: The Five Levels of Self-Driving Cars

202

809: Agentic AI, with Shingai Manjengwa

203

808: In Case You Missed It in July 2024

204

807: Superintelligence and the Six Singularities, with Dr. Daniel Hulme

205

806: Llama 3.1 405B: The First Open-Source Frontier LLM

206

805: How to Be a Supercommunicator, with Charles Duhigg

207

804: AI x Solar Power = Abundant Energy

208

803: How to Thrive in Your (Data Science) Career, with Daliana Liu

209

802: In Case You Missed It in June 2024

210

801: Merged LLMs Are Smaller And More Capable, with Arcee AI's Mark McQuade and Charles Goddard

211

800: A Transformative Century of Technological Progress, with Annie P.

212

799: AGI Could Be Near: Dystopian and Utopian Implications, with Dr. Andrey Kurenkov

213

798: Claude 3.5 Sonnet: Frontier Capabilities & Slick New "Artifacts" UI

214

797: Deep Learning Classics and Trends, with Dr. Rosanne Liu

215

796: Earth's Coming Population Collapse and How AI Can Help, with Simon Kuestenmacher

216

795: Fast-Evolving Data and AI Regulatory Frameworks, with Dr. Gina Guillaume-Joseph

217

794: Exciting (and Frightening!) Trends in Open-Source AI

218

793: Bayesian Methods and Applications, with Alexandre Andorra

219

792: In Case You Missed It in May 2024

220

791: Reinforcement Learning from Human Feedback (RLHF), with Dr. Nathan Lambert

221

790: Open-Source Libraries for Data Science at the New York R Conference

222

789: ML for Wind-Powered Energy Generation, with Dr. Jason Yosinski

223

788: Multi-Agent Systems: How Teams of LLMs Excel at Complex Tasks

224

787: MLOps: The Job and The Key Tools, with Demetrios Brinkmann

225

786: The Six Keys to Data Scientists' Success, with Kirill Eremenko

226

785: Math, Quantum ML and Language Embeddings, with Dr. Luis Serrano

227

784: Aligning Large Language Models, with Sinan Ozdemir

228

783: Generative A.I. for Solar Power Installation, with Navdeep Martin

229

782: In Case You Missed It in April 2024

230

781: Ensuring Successful Enterprise AI Deployments, with Sol Rashidi

231

780: How to Become a Data Scientist, with Dr. Adam Ross Nelson

232

779: The Tidyverse of Essential R Libraries and their Python Analogues, with Dr. Hadley Wickham

233

778: Mixtral 8x22B: SOTA Open-Source LLM Capabilities at a Fraction of the Compute

234

777: Generative AI in Practice, with Bernard Marr

235

776: Deep Utopia: AI Could Solve All Human Problems in Our Lifetime

236

775: What will humans do when machines are vastly more intelligent? With Aleksa Gordić

237

774: RFM-1 Gives Robots Human-like Reasoning and Conversation Abilities

238

773: Deep Reinforcement Learning for Maximizing Profits, with Prof. Barrett Thomas

239

772: In Case You Missed It in March 2024

240

771: Gradient Boosting: XGBoost, LightGBM and CatBoost, with Kirill Eremenko

241

770: The Neuroscientific Guide to Confidence

242

769: Generative AI for Medicine, with Prof. Zack Lipton

243

768: Is Claude 3 Better than GPT-4?

244

767: Open-Source LLM Libraries and Techniques, with Dr. Sebastian Raschka

245

766: Vonnegut's Player Piano (1952): An Eerie Novel on the Current AI Revolution

246

765: NumPy, SciPy and the Economics of Open-Source, with Dr. Travis Oliphant

247

764: The Top 10 Episodes of 2023

248

763: The Best A.I. Startup Opportunities, with venture capitalist Rudina Seseri

249

762: Gemini 1.5 Pro, the Million-Token-Context LLM

250

761: Gemini Ultra: How to Release an A.I. Product for Billions of Users, with Google's Lisa Cohen

251

760: Humans Love A.I.-Crafted Beer

252

759: Full Encoder-Decoder Transformers Fully Explained, with Kirill Eremenko

253

758: The Mamba Architecture: Superior to Transformers in LLMs

254

757: How to Speak so You Blow Listeners' Minds, with Cole Nussbaumer Knaflic

255

756: AlphaGeometry: AI is Suddenly as Capable as the Brightest Math Minds

256

755: Brewing Beer with A.I., with Beau Warren

257

754: A Code-Specialized LLM Will Realize AGI, with Jason Warner

258

753: Blend Any Programming Languages in Your ML Workflows, with Dr. Greg Michaelson

259

752: AI is Disadvantaging Job Applicants, But You Can Fight Back

260

751: How to Found and Fund Your Own A.I. Startup, with Dr. Rasmus Rothe

261

750: How A.I. is Transforming Science

262

749: Data Science for Clean Energy, with Emily Pastewka

263

748: The Five Levels of AGI

264

747: Technical Intro to Transformers and LLMs, with Kirill Eremenko

265

746: A Continuous Calendar for 2024

266

745: 2024 Data Science Trend Predictions

267

744: To a Peaceful 2024

268

743: How to Integrate Generative A.I. Into Your Business, with Piotr Grudzień

269

742: Happy Holidays from All of Us

270

741: How to Visualize Data Effectively, with Prof. Alberto Cairo

271

740: Q*: OpenAI's Rumored AGI Breakthrough

272

739: AI is Eating Biology and Chemistry, with Dr. Ingmar Schuster

273

738: Engineering Biomaterials with Generative AI, with Dr. Pierre Salvy

274

737: scikit-learn's Past, Present and Future, with scikit-learn co-founder Dr. Gaël Varoquaux

275

736: How to Officially Certify your AI Model, with Jan Zawadzki

276

735: A.I. Product Management, with Google DeepMind's Head of Product, Mehdi Ghissassi

277

734: Humanoid Robot Soccer, with the Dutch RoboCup Team

278

733: OpenAssistant: The Open-Source ChatGPT Alternative, with Dr. Yannic Kilcher

279

732: Data Science for Astronomy, with Dr. Daniela Huppenkothen

280

731: A.I. Agents Will Develop Their Own Distinct Culture, with Nell Watson

281

730: How GitHub Operationalizes AI for Teamwide Collaboration and Productivity

282

729: Universal Principles of Intelligence (Across Humans and Machines), with Prof. Blake Richards

283

728: Use Contrastive Search to get Human-Quality LLM Outputs

284

727: Unmasking A.I. Injustice, with Dr. Joy Buolamwini

285

726: Seven Factors for Successful Data Leadership

286

725: Neuroscience + Machine Learning, with Google DeepMind's Dr. Kim Stachenfeld

287

724: Decoding Speech from Raw Brain Activity, with Dr. David Moses

288

723: Mathematical Optimization, with Jerry Yurchisin

289

722: AI Emits Far Less Carbon Than Humans (Doing the Same Task)

290

721: Quantum Machine Learning, with Dr. Amira Abbas

291

720: OpenAI’s DALL-E 3, Image Chat and Web Search

292

719: Computational Mathematics and Fluid Dynamics, with Prof. Margot Gerritsen

293

718: ChatGPT Custom Instructions: A Major, Easy Hack for Data Scientists

294

717: Overcoming Adversaries with A.I. for Cybersecurity, with Dr. Dan Shiebler

295

716: Happiness and Life-Fulfillment Hacks

296

715: Make Better Decisions with Data, with Dr. Allen Downey

297

714: Using A.I. to Overcome Blindness and Thrive as a Data Scientist

298

713: Llama 2, Toolformer and BLOOM: Open-Source LLMs with Meta's Dr. Thomas Scialom

299

712: Code Llama

300

711: Image, Video and 3D-Model Generation from Natural Language, with Dr. Ajay Jain

301

710: LangChain: Create LLM Applications Easily in Python

302

709: Big A.I. R&D Risks Reap Big Societal Rewards, with Meta's Dr. Laurens van der Maaten

303

708: ChatGPT Code Interpreter: 5 Hacks for Data Scientists

304

707: Vicuña, Gorilla, Chatbot Arena and Socially Beneficial LLMs, with Prof. Joey Gonzalez

305

706: Large Language Model Leaderboards and Benchmarks

306

705: Feeding the World with ML-Powered Precision Agriculture

307

704: Jon’s “Generative A.I. with LLMs” Hands-on Training

308

703: How Data Happened: A History, with Columbia Prof. Chris Wiggins

309

702: Llama 2 — It's Time to Upgrade your Open-Source LLM

310

701: Generative A.I. without the Privacy Risks (with Prof. Raluca Ada Popa)

311

700: "The Dream of Life" by Alan Watts

312

699: The Modern Data Stack, with Harry Glaser

313

698: How Firms Can Actually Adopt A.I., with Rehgan Avon

314

697: The (Short) Path to Artificial General Intelligence, with Dr. Ben Goertzel

315

696: Brain-Computer Interfaces and Neural Decoding, with Prof. Bob Knight

316

695: NLP with Transformers, feat. Hugging Face's Lewis Tunstall

317

694: CatBoost: Powerful, efficient ML for large tabular datasets

318

693: YOLO-NAS: The State of the Art in Machine Vision, with Harpreet Sahota

319

692: Lossless LLM Weight Compression: Run Huge Models on a Single GPU

320

691: A.I. Accelerators: Hardware Specialized for Deep Learning

321

690: How to Catch and Fix Harmful Generative A.I. Outputs

322

689: Observing LLMs in Production to Automatically Catch Issues

323

688: Six Reasons Why Building LLM Products Is Tricky

324

687: Generative Deep Learning, with David Foster

325

686: Open-Source "Responsible A.I." Tools, with Ruth Yakubu

326

685: Tools for Building Real-Time Machine Learning Applications, with Richmond Alake

327

684: Get More Language Context out of your LLM

328

683: Contextual A.I. for Adapting to Adversaries, with Dr. Matar Haller

329

682: Business Intelligence Tools, with Mico Yuk

330

681: XGBoost: The Ultimate Classifier, with Matt Harrison

331

680: Automating Industrial Machines with Data Science and the Internet of Things (IoT)

332

679: The A.I. and Machine Learning Landscape, with investor George Mathew

333

678: StableLM: Open-source "ChatGPT"-like LLMs you can fit on one GPU

334

677: Digital Analytics with Avinash Kaushik

335

676: The Chinchilla Scaling Laws

336

675: Pandas for Data Analysis and Visualization

337

674: Parameter-Efficient Fine-Tuning of LLMs using LoRA (Low-Rank Adaptation)

338

673: Taipy, the open-source Python application builder

339

672: Open-source "ChatGPT": Alpaca, Vicuña, GPT4All-J, and Dolly 2.0

340

671: Cloud Machine Learning

341

670: LLaMA: GPT-3 performance, 10x smaller

342

669: Streaming, reactive, real-time machine learning

343

668: GPT-4: Apocalyptic stepping stone?

344

667: Harnessing GPT-4 for your Commercial Advantage

345

666: GPT-4

346

665: How to be both socially impactful and financially successful in your data career

347

664: MIT Study: ChatGPT Dramatically Increases Productivity

348

663: Astonishing CICERO negotiates and builds trust with humans using natural language

349

662: The Most Popular SuperDataScience Podcast Episodes of 2022

350

661: Designing Machine Learning Systems

351

660: Five Ways to Use ChatGPT for Data Science

352

659: Open-Source Tools for Natural Language Processing

353

658: How to Build Data and ML Products Users Love

354

657: How to Learn Data Engineering

355

656: A.I. Talent and the Red-Hot A.I. Skills

356

655: AI ROI: How to get a profitable return on an AI-project investment

357

654: Mike Wimmer: The 14-Year-Old A.I. Entrepreneur

358

653: Efficiently Glean-ing Insights from Vast Data Warehouses

359

652: A.I. Speech for the Speechless

360

651: The Intentional Use of Color in Data Communication

361

650: SparseGPT: Remove 100 Billion Parameters but Retain 100% Accuracy

362

649: Introduction to Machine Learning

363

648: VALL-E: Uncannily Realistic Voice Imitation from a 3-Second Clip

364

647: Is Data Science Still Sexy?

365

646: ChatGPT: How to Extract Commercial Value Today

366

645: Machine Learning for Video Games

367

644: A Framework for Big Life Decisions

368

643: A.I. for Medicine

369

642: Continuous Calendar for 2023

370

641: Data Science Trends for 2023

371

640: What I Learned in 2022

372

639: Simplifying Machine Learning

373

638: ChatGPT Holiday Greeting

374

637: How to Influence Others with Your Data

375

636: The Equality Machine

376

635: The Perils of Manually Labeling Data for Machine Learning Models

377

634: Model Error Analysis

378

633: Responsible Decentralized Intelligence

379

632: Liquid Neural Networks

380

631: Data Analytics Career Orientation

381

630: Resilient Machine Learning

382

629: Software for Efficient Data Science

383

628: The Critical Human Element of Successful A.I. Deployments

384

627: AutoML: Automated Machine Learning

385

626: Subword Tokenization with Byte-Pair Encoding

386

625: Analyzing Blockchain Data and Cryptocurrencies

387

624: Imagen Video: Incredible Text-to-Video Generation

388

623: Data Analyst, Data Scientist, and Data Engineer Career Paths

389

622: Burnout: Causes and Solutions

390

621: Blockchains and Cryptocurrencies: Analytics and Data Applications

391

620: OpenAI Whisper: General-Purpose Speech Recognition

392

619: Tools for Deploying Data Models into Production

393

618: The Joy of Atelic Activities

394

617: Causal Modeling and Sequence Data

395

616: The Four Requirements for Expertise (beyond the 10,000 Hours)

396

615: How to Ace Your Data Science Interview

397

614: Thriving on Information Overload

398

613: Causal Machine Learning

399

612: More Guests on Fridays

400

611: Open-Ended A.I.: Practical Applications for Humans and Machines

401

610: Who Dares Wins

402

609: Data Mesh

403

608: Daily Habit #11: Assigning Deliverables

404

607: Inferring Causality

405

606: Four Thousand Weeks

406

605: Upskilling in Data Science and Machine Learning

407

604: Ignition: A Landmark Nuclear Fusion Milestone is Achieved

408

603: Geospatial Data and Unconventional Routes into Data Careers

409

602: We Are Living in Ancient Times

410

601: Venture Capital for Data Science

411

600: Yoga Nidra Practice with Steve Fazzari

412

599: MLOps: Machine Learning Operations

413

598: Getting Kids Excited about STEM Subjects

414

597: A.I. Policy at OpenAI

415

596: The A.I. Platforms of the Future

416

595: Data Engineering 101

417

594: Why CEOs Care About A.I. More than Other Technologies

418

593: The Real-World Impact of Cross-Disciplinary Data Science Collaboration

419

592: How to Sell a Multimillion Dollar A.I. Contract

420

591: Simulations and Synthetic Data for Machine Learning

421

590: Artificial General Intelligence is Not Nigh (Part 2 of 2)

422

589: Narrative A.I. with Hilary Mason

423

588: Artificial General Intelligence is Not Nigh

424

587: Data Engineering for Data Scientists

425

586: Daily Habit #10: Limit Social Media Use

426

585: PyMC for Bayesian Statistics in Python

427

584: OpenAI Codex

428

583: The State of Natural Language Processing

429

582: Model Speed vs Model Accuracy

430

581: Bayesian, Frequentist, and Fiducial Statistics in Data Science

431

580: Collecting Valuable Data

432

579: Transforming Dentistry with A.I.

433

578: Identifying Commercial ML Problems

434

577: Scaling A.I. Startups Globally

435

576: Tech Startup Dramas

436

575: Optimizing Computer Hardware with Deep Learning

437

574: Music for Deep Work

438

573: Automating ML Model Deployment

439

572: Daily Habit #9: Avoiding Messages Until a Set Time Each Day

440

571: Collaborative, No-Code Machine Learning

441

570: DALL-E 2: Stunning Photorealism from Any Text Prompt

442

569: A.I. For Crushing Humans at Poker and Board Games

443

568: PaLM: Google's Breakthrough Natural Language Model

444

567: Open-Access Publishing

445

566: The Best Time to Plant a Tree

446

565: AGI: The Apocalypse Machine

447

564: Clem Delangue on Hugging Face and Transformers

448

563: How to Rock at Data Science — with Tina Huang

449

562: Daily Habit #8: Math or Computer Science Exercise

450

561: Engineering Data APIs

451

560: Daily Habit #7: Read Two Pages

452

559: GPT-3 for Natural Language Processing

453

558: Jon's Answers to Questions on Machine Learning

454

557: Effective Pandas

455

556: Jon's Machine Learning Courses

456

555: Sports Analytics and 66 Days of Data with Ken Jee

457

554: Jon's Deep Learning Courses

458

553: The Statistics and Machine Learning Quests of Dr. Josh Starmer

459

552: The Most Popular SuperDataScience Episodes of 2021

460

551: Deep Reinforcement Learning — with Wah Loon Keng

461

550: Daily Habit #6: Write Morning Pages

462

549: Engineering Natural Language Models — with Lauren Zhu

463

548: Daily Habit #5: Meditate

464

547: How Genes Influence Behavior — with Prof. Jonathan Flint

465

546: Daily Habit #4: Alternate-Nostril Breathing

466

545: Scaling Data-Intensive Real-Time Applications — with Matthew Russell

467

544: Daily Habit #3: Make Your Bed

468

543: Sparking A.I. Innovation — with Nicole Büttner

469

542: Continuous Calendar for 2022

470

541: Data Observability — with Dr. Kevin Hu

471

540: Daily Habit #2: Start the Day with a Glass of Water

472

539: Interpretable Machine Learning — with Serg Masís

473

538: Daily Habit #1: Track Your Habits

474

537: Data Science Trends for 2022

475

536: What I Learned in 2021

476

535: How to Found, Grow, and Sell a Data Science Start-up

477

534: A Holiday Greeting

478

533: Fusion Energy, Cancer Proteomics, and Massive-Scale Machine Vision — with Dr. Brett Tully

479

532: Mutable vs Immutable Conditions

480

531: Data Science at the Command Line

481

530: Ten A.I. Thought Leaders to Follow (on Twitter)

482

529: A.I. Robotics at Home

483

528: The Normal Anxiety of Content Creation

484

527: Automating Data Analytics

485

526: The Highest-Paying Data Frameworks

486

525: Hurdling Over Data Career Obstacles

487

524: The Highest-Paying Data Tools

488

523: Open-Source Analytical Computing (pandas, Apache Arrow)

489

522: Data Tools vs. Data Platforms

490

521: Skyrocket Your Career by Sharing Your Writing

491

520: The Highest-Paying Programming Languages for Data Scientists

492

519: A.I. for Good

493

518: Fail More

494

517: Courses in Data Science and Machine Learning

495

516: Does Caffeine Hurt Productivity? (Part 3: Scientific Literature)

496

515: Accelerating Impact through Community — with Chrys Wu

497

514: Does Caffeine Hurt Productivity? (Part 2: Experimental Results)

498

513: Transformers for Natural Language Processing

499

512: Does Caffeine Hurt Productivity? (Part 1)

500

511: Data Science for Private Investing — LIVE with Drew Conway

501

510: Deep Reinforcement Learning

502

509: Accelerating Start-up Growth with A.I. Specialists

503

508: Building Your Ant Hill

504

507: Bayesian Statistics

505

506: Supervised vs Unsupervised Learning

506

505: From Data Science to Cinema

507

504: Classification vs Regression

508

503: Deep Reinforcement Learning for Robotics

509

502: Managing Imposter Syndrome

510

501: Statistical Programming with Friends

511

500: Yoga Nidra with Jes Allen

512

499: Data Meshes and Data Reliability

513

498: How Only Beginners Know Everything

514

497: Maximizing the Global Impact of Your Career

515

496: 2040: A Brain-Computer Interface Story

516

495: Successful AI Projects and AI Startups

517

494: How to Instantly Appreciate Being Alive

518

493: Bringing Data to the People

519

492: The World is Awful (and it's Never Been Better)

520

491: R in Production

521

490: Say No to Pie Charts

522

489: Monetizing Machine Learning

523

488: The Price of Your Attention

524

487: Fixing Dirty Data

525

486: The History of Calculus

526

485: Financial Data Engineering

527

484: Algorithm Aversion

528

483: Setting Yourself Apart in Data Science Interviews

529

482: Continuous Calendars

530

481: Performance Marketing Analytics

531

480: Top Five Resume Tips

532

479: Knowledge Graphs

533

478: Five Keys to Success

534

477: How to Thrive as an Early-Career Data Scientist

535

476: Peer-Driven Learning

536

475: The 20% of Analytics Driving 80% of ROI

537

474: The Machine Learning House

538

473: Machine Learning at NVIDIA

539

472: The Learning Never Stops (so Relax)

540

471: 99 Days to Your First Data Science Job

541

470: My Favorite Books

542

469: Learning Deep Learning Together

543

468: The History of Data

544

467: High-Impact Data Science Made Easy

545

466: Good vs. Great Data Scientists

546

465: Analytics for Commercial and Personal Success

547

464: A.I. vs Machine Learning vs Deep Learning

548

463: Time Series Analysis

549

462: It Could Be Even Better

550

461: MLOps for Renewable Energy

551

460: The History of Algebra

552

459: Tackling Climate Change with ML

553

458: Behind the Scenes

554

457: Landing Your Data Science Dream Job

555

456: The Pomodoro Technique

556

455: Legal Tech, Powered by Machine Learning

557

454: The Staggering Pace of Progress Part 2

558

453: Big Global Problems Worth Solving with Machine Learning

559

452: The Staggering Pace of Progress

560

451: Translating PhD Research into ML Applications

561

450: Yoga Nidra

562

449: Fairness in A.I.

563

448: How to be a Data Science Leader

564

447: Commercial ML Opportunities Lie Everywhere

565

446: Getting Started in Machine Learning

566

445: Conversational A.I.

567

444: Future-Proofing Your Career

568

443: The End of Jobs

569

442: Data Science as an Atomic Habit

570

441: Communicating Data Effectively

571

440: MuZero: Learning Without Rules

572

439: Deep Learning for Machine Vision

573

438: Artificial General Intelligence

574

437: Data Science at a World-Leading Hedge Fund

575

436: Attention Sharpening Tools Part 2

576

435: Scaling Up Machine Learning

577

434: Attention Sharpening Tools Part 1

578

433: Data Science Trends for 2021

579

432: Hello from Jon and Welcome to 2021

580

431: One-on-one with Kirill: What I learned in 2020

581

430: Intellect and Intelligence

582

429: 2020's Biggest Data Science Breakthroughs

583

428: The Internal Conflict Model

584

427: Impacting Through Technology

585

426: The Shift: From Ambition to Meaning

586

425: The Past, Present, and Future of AI Services

587

424: A Symbiotic Relationship With AI

588

423: The Growth and Future of STEM in Africa

589

422: Pain Vs. Suffering

590

421: Real-World Applications of Digital Twins

591

420: Wheel of Life

592

419: Unlocking the Architecture of Innovation

593

418: Play With Feeling

594

417: Data Engineering and Product Development

595

416: My Advice for Career Success

596

415: Developing and Maintaining Your Technical and Soft Skills

597

414: Needs vs. Wants

598

413: Changing The World With Data

599

412: Stand More - Sit Less

600

411: Succeeding in Analytics by Thinking Outside the Data

601

410: Communicate Your Needs

602

409: Succeeding & Networking In The Virtual Space

603

408: Meaning is Everything

604

407: How to Encourage Diversity in Data Science

605

406: Abandon Hope

606

405: The Work of Quants and Data Scientists in the Financial Space

607

404: The Narrative Arc in Storytelling

608

403: Gamifying Your Data Science Work and Education

609

402: Face Your Demons

610

401: From Data Science Student to Professional

611

400: Think Bigger

612

399: Contributing to the Community of Data Scientists

613

398: Emotional Burnout

614

397: The Importance of Data Science Literacy

615

396: Five Job Hunting Tips

616

395: How to Tell Stories with Data

617

394: Teach It

618

393: The Importance of Keeping Science in Data Science

619

392: Start Your Own Morning Ritual

620

391: Data Science Campfire Tales with John Elder

621

390: Perception vs. Emotion

622

389: Becoming Good Enough: Jumpstarting Your Data Science Career

623

388: Get a Headhunter

624

387: Becoming a Data Science Leader

625

386: Cohort Analysis

626

385: Advanced Data Topics and People-Centered Data Science

627

384: 10 Tips to Become a Master Presenter

628

383: You're Not an Imposter, You're Learning: Data Science Journeys

629

382: Manage Cognitive Load in Data Science

630

381: How to Avoid Failing at Digital Transformation

631

380: Data Analyst vs. Data Scientist

632

379: Maelstrom, Chaos, and Mayhem: Guiding Your Data Science Career Path

633

378: Use Your Unconscious Mind

634

377: The Power of Women in STEM

635

376: Expose Yourself to New Ideas Regularly

636

375: Utilizing Oracle Cloud as an Enterprise, Small Business, or Developer

637

374: Remember to Wind Down

638

373: TensorFlow and AI Learnings for Developers

639

372: Understanding the P-Value

640

371: The Power of Memory For Productivity

641

370: What is Support Vector Regression (SVR)?

642

369: Real Data Analytics for Economics, HR, and COVID-19

643

368: Future-Proof Your Career

644

367: Building Data Pipelines for COVID-19 Modeling

645

366: Define Your Own Success

646

365: Deep Learning Models For Recruitment

647

364: Depression and Suicidal Thoughts

648

363: Intuition, Frameworks, and Unlocking the Power of Data

649

362: Hybrid AI

650

361: How To Succeed As An Analytics Consultant

651

360: Importance of Sleep

652

359: Tackling Data Science Job Hunting, Interviews & Negotiations

653

358: Racism and Discrimination

654

357: Emotions, Relationships, and Being Kind During the Pandemic

655

356: Working Remotely

656

355: DJ Patil on Harnessing the Power of Data Science Community

657

354: Negative Coefficients

658

353: How to Practice Human-Centric Data Science

659

352: History of Data Science - Part 5

660

351: Self-Starting In Data Science

661

350: Coronavirus

662

349: Human-in-the-Loop Algorithms in Retail

663

348: History of Data Science - Part 4

664

347: How To Tell Your Story For Career Success

665

346: My Top 5 Productivity Hacks

666

345: Machine Learning At Twitter

667

344: History of Data Science - Part 3

668

343: Career Jumpstarts through Data Science Retreat

669

342: History of Data Science - Part 2

670

341: Talking Robotics with Brandon Rohrer

671

340: History of Data Science - Part 1

672

339: The Power of Coaching

673

338: Too Many Photos

674

337: Hadley Wickham Talks Integration and Future of R and Python

675

336: Better Than Perfect

676

335: Many Ways to Fail & Five Ways to Succeed in Startups

677

334: No Coaching

678

333: BERT and NLP in 2020 and Beyond

679

332: Go through the Motions

680

331: Hacking Data Science Interviews for Graduates

681

330: Good!

682

329: Telling a Story Right with Data

683

328: Look for the Horse

684

327: Data Science Trends for 2020

685

326: Who Inspires You?

686

325: What I Learned in 2019

687

324: Proximity is Power #2

688

323: Data Science as a Freelance Career

689

322: Diets

690

321: The Life of One Advanced Data Scientist

691

320: Mentorship

692

319: The Path to Data Visualization

693

318: Amazing

694

317: A Deep Dive Into Neural Nets

695

316: Make It About Yourself

696

315: Making Data Accessible

697

314: Meet the Team

698

313: The Power of Online Data Education

699

312: Contemplation

700

311: Using Data Right In Smart Cities

701

310: Trial by Fire

702

309: Learning Through Competition

703

308: Your Tribe

704

307: Problem Solving Through Better Thinking

705

306: Pura Vida

706

305: Using Data Visualization Tools

707

304: The Law of Attraction

708

303: Proper Hypothesis Testing For Every Field

709

302: What is Data Science to you?

710

301: Finding Your Edge

711

300: Legacy

712

299: Becoming Seasoned At Failure

713

298: The Six Months Rule

714

297: Fortitude & Passion in the Data Science Journey

715

296: Who You Become

716

295: A Deep Conversation About Tech & Life

717

294: Perception of AI in Big Companies

718

293: True Personalization Through Reinforcement Learning

719

292: Introverts and Extroverts

720

291: Changing the World With Theory & Data

721

290: The Passion Paradox

722

289: AI, Deepfakes and Call of Duty

723

288: Love Yourself

724

287: How To Be Social About Data Science

725

286: Solitude Deprivation

726

285: Bringing Dev & Diverse Communities Into Data Science

727

284: Proximity is Power

728

283: Getting The Most Out of Data With Gradient Boosting

729

282: Learning Something New

730

281: Futureproofing Your Digital Marketing Tactics

731

280: Gap Year

732

279: Embedding Data Science in Business

733

278: Your Core Strength

734

277: The New Age of Reason

735

276: Data Science in Wealth Management

736

275: Machine Learning Through Reinforcement & Contextual Bandits

737

274: Ask the Right Question

738

273: Predict, Prevent, Detect: Cyber Security

739

272: Data Science in Energy

740

271: Making the Public Graphically Literate

741

270: The Cold is My Master

742

269: Maximizing Advertising Efforts With Data

743

268: Data Science in Insurance

744

267: Achieving Data Science Maturity

745

266: Exploration vs Exploitation

746

265: Data Science in the World of Big Data

747

264: Data Science in Agriculture

748

263: Communicating Data

749

262: You Cannot Make Progress Without a Routine

750

261: Succeeding in Data Science with the Trichotomy of Control

751

260: Data Science in Real Estate

752

259: Building Machine Autonomy With Neural Networks

753

258: Eating S.L.O.W.L.Y.

754

257: AI: How Far We Haven’t Actually Come

755

256: Data Science in Transportation

756

255: Diving Into Computer Vision

757

254: Two Wolves

758

253: Solving Problems With Data Science & Uber

759

252: Data Science In Construction

760

251: Transforming the Identity Authentication Space

761

250: Guilt vs Shame

762

249: Diving Into Data Science Consulting

763

248: Data Science in Government

764

247: The Science Fact of Technology, AI, & Social Media

765

246: Boost Your Self-Confidence

766

245: Knowing What You Need to Know With Data Science

767

244: Data Science in Entertainment

768

243: Geospatial Analytics: Where Data Science & Actuarial Science Meet

769

242: Meditation

770

241: Pushing the Boundaries in Mental Healthcare with Data Science

771

240: State of Artificial Intelligence in Business

772

239: From Candidate to Career: Pathways for Data Scientists

773

238: Data Science in Banking

774

237: Data Privacy, GDPR, and You

775

236: How to Deal with Negative Emotions

776

235: Living the Dream With Data Science

777

234: Data Science in Education

778

233: High Octane Data Science Leadership at Red Bull

779

232: Sleep on it

780

231: Data Visualizers: The Storytellers of Data Science

781

230: SuperDataScience 2.0

782

229: Data-Driven Approach of Doing Business

783

228: Data Science in Mining

784

227: Enhancing Your Mobile Gaming Experience With Data Science

785

226: Flat Tyres Happen

786

225: The Benefit of Having a Diverse Skill Set

787

224: Hacks For Reading More Books

788

223: Data Science Trends for 2019

789

222: 2018 in Numbers

790

221: 1-on-1 with Kirill: What I learned in 2018

791

220: Data Science in Retail

792

219: How Kaplan uses Data for Education

793

218: Start A Great Day

794

217: Aerospace Engineers and Data Science

795

216: Data Science In Healthcare

796

215: Integrating Data Science as a Developer

797

214: What Is Amazing In Your Life

798

213: Amazing Tips from Two Legends of Visualization

799

212: Model Driven Vs Data Driven

800

211: Working on Apache Spark & R Package Development

801

210: Compete With Yourself

802

SDS 209: Full-Time Data Scientist after just 1 year in the field

803

208: Re-live DSGO2018

804

207: The Technical Skills that Actually Add Business Value

805

206: Machine Learning is All Aroud You

806

205: Contributing to the community as a Data Science Influencer

807

204: Set Your Goals Higher

808

203: Highlights of DSGO 2018 According to an Aspiring Data Scientist

809

202: Ideas and Execution

810

201: Emerging Technologies: Challenges and Opportunities in a Revolutionized World

811

200: What’s the Future of Data Science? Speaker Mashup Edition

812

199: Data Visualization Insights from NYU

813

198: Two Millimeter Shifts

814

197: How to be Happy and Successful

815

196: Diversity in Data Science

816

195: Inspiration from the Founder of the R Ladies Organization

817

194: Why I Became Vegan

818

193: A serious talk on AI taking over jobs

819

192: Ace the "Greatest Weakness" Interview Question

820

191: Helping San Diego Become a Smart City

821

190: See You in San Diego

822

189: How I Got 45,000 Linkedin Followers in One Year

823

188: 6 Ways to Fill the Data Science Gap

824

187: How Data Science is Becoming a Science

825

186: Why Execution Trumps Knowledge

826

185: The Pre-Requisites for Analytics to Happen

827

184: Why You Need Domain Knowledge in Data Science

828

183: Everything about Data Analytics & its Future

829

182: The Importance of the Data Science Community

830

181: 10 Tips from a Data Science Consultant

831

180: The Idea Behind Essentialism

832

179: How a Data Science Recruiter Thinks

833

178: Visualization in Data Science

834

177: Building a Career in Data Science

835

176: The Importance of Storytelling in Data Science

836

175: Insights from the Founder of KDnuggets

837

174: A Technology Detox Challenge

838

173: Understanding Robotics Process Automation (RPA) to Disrupt Your Business

839

172: Why You Need to Go Beyond the Data

840

171: Deep dive into R Programming & R Studio

841

170: Tips for a Bumpy Ride

842

169: Data Science: Technology and Philanthropy

843

168: Focus on Your Strengths and Ignore Your Weaknesses

844

167: Why All Companies Need a Data Science Culture

845

166: Should You Be Effective or Efficient?

846

165: Giving Back to the Data Science Community

847

164: Love Languages and How They Impact Your Life

848

163: How to Deal with Disruptive Technologies

849

162: What I Learned from a 10 Day Detox

850

161: Using AI to Automate Communication

851

160: Up Your Presentation Skills with Toastmasters

852

159: From Developer to Data Scientist

853

158: Maximize Life with the Rapid Planning Method

854

157: The Amazing World of a Data Science Meetup

855

156: Parkinson's Law to Increase Productivity

856

155: How AI and Blockchain Converge

857

154: Why Socializing is Crucial

858

153: Tips to Improve your Memory

859

152: Data Science GO 2018

860

151: Women in Data Science & How to Help

861

150: Have a Mentor

862

149: Data Science Tips for Startups to Large Companies

863

148: The Trolley Problem

864

147: How to Live a More Fulfilling Life - Time & Energy Management

865

146: Empathy and Compassion

866

145: How to Use Data Science In Offline Business

867

144: Two Things to Remember and Two Things to Forget

868

143: Why Sensors and the Internet of Things are Becoming A Critical Part of Data Science

869

142: Coworking

870

141: Supply Chain Analytics, Worldwide Consulting and Learning Data Science In Your Career

871

140: Upper Limiting

872

139: The Rise of Blockchain: A Disruptive Super-Technology Much More Than Bitcoin

873

138: Zone of Genius

874

137: Cloud Technology: How It’s Changing Data Science, Collaboration and Enterprise

875

136: Learn Blockchain!

876

135: How Directors of Data Science Changes the World with Machine Learning and AI

877

134: How do Lobsters Grow?

878

133: How a Passion for Tableau Changed a Life

879

132: The Data-Driven Executive

880

131: The One Purpose to Data Science and The Truth about Analytics

881

130: Instant Gratification Monkey

882

129: Database Challenges for Data Science and How to Deal With Them

883

128: Confident Data Skills

884

127: No Compromise: Tableau, Twitter and Fearless Career Shifts

885

126: Ender's Game

886

125: A Glimpse into the Virtual Reality World of the Future

887

124: Reckless Commitment

888

123: How to be Unstoppable: Data Science, Reckless Commitment & Artificial Intelligence

889

122: Who Moved My Cheese?

890

121: Building a Successful Data Science Practice and How to be an Effective Data Scientist

891

120: Technological Singularity

892

119: Data Science Trends for 2018

893

118: New Year Resolutions

894

117: 1-on-1 with Kirill: What I learned in 2017

895

116: The Power of Gratitude

896

115: Application of Geospatial Analytics to Business and Real Life

897

114: Expand Your Comfort Zone

898

113: How Constant Learning Created a Jet-Set Career

899

112: How to Win Friends & Influence People

900

111: The Power of Soft Skills in Data Science

901

110: AlphaGo Zero

902

109: Business Consultancy in the Space of Data Science

903

108: Working Remotely

904

107: Charting a Career in Energy Analytics

905

106: Recap of our DataScienceGO 2017 Conference

906

105: DataScienceGO’s Discussion Panel on Careers

907

104: Board Games

908

103: Why this Is the Golden Age of Data Science & How to Get In

909

102: Intuition vs Mathematics in Data Science

910

101: What a Data Science Headhunter is Looking For

911

100: 100 Episodes

912

099: How a Software Developer Re-Focused his life to Learn Artificial Intelligence

913

098: Willpower

914

097: Leveraging Data Science Techniques into E-Commerce & Other Fields

915

096: Bayes Theorem

916

095: From Uber to Data Science – A Winner’s Journey

917

094: The Power of Now

918

093: Why Evolutionary Programming Machine Learning is Important

919

092: Exponential Thinking

920

091: Lessons From a Successful Career in Data Visualization

921

090: Do What You Want

922

089: Using Excel in Data Science and Life-Long Learning

923

088: Fermi Questions

924

087: Business Intelligence – The Role of Data Visualization

925

086: Computer Vision

926

085: The AI Revolution – What the Future Will Look Like

927

084: Why I Became Vegetarian

928

083: Leveraging Your Experience into Data Science

929

082: Data Science Go

930

081: Data Visualization & How to Freelance Your Passion

931

080: Your Questions

932

079: Reinforcement Learning - What You Need to Know

933

078: Breaking Patterns

934

077: Finding the Right Data Science Company That Best Fits You

935

076: Do It For Yourself

936

075: How to Re-Focus Your Career & Become an Entry Level Data Scientist

937

074: The Five Balls of Life

938

073: How to Stand Out to Recruiters in Data Science

939

072: Connecting the Dots

940

071: Where the World is Headed to in the Field of Artificial Intelligence

941

070: The Quant Crunch

942

069: Steps on How To Become a Thought Leader in the Field of Data Science

943

068: Stimulate Your Creativity

944

067: Latest Developments in the Field of AI and How it is Changing the World

945

066: The Best Ideas

946

065: How Data Science Brings Value through Consulting Firms

947

064: My Best Tool

948

063: How to Keep up with Data Science Trends

949

062: Dreams vs. Goals

950

061: Discovering Data Science Workflows and The Importance of Mentorship

951

060: Maker's Schedule vs. Manager's Schedule

952

059: Changing Human Behaviour Through a Driving App

953

058: Conferences

954

057: Building Image Datasets and Their Importance in Machine Learning

955

056: Date With Destiny

956

055: Building and Managing a Successful Data Science Team

957

054: Selective Ignorance

958

053: Career Transitioning to Data Science: Important Lessons from an Aspiring Data Scientist

959

052: Getting Things Done

960

051: Understanding the Newest Big Data Technology Buzz Terms

961

050: Teamwork

962

049: Great Tips on Building a Successful Analytics Culture

963

048: Push Yourself

964

047: An Expert Overview of the Deep Learning Models, Supervised and Unsupervised

965

046: What is Reality?

966

045: Exclusive Interview with the Legendary in Kaggle Competitions Eu Jin Lok

967

044: Addicted to Data

968

043: Solving an Optimization Problem with a Custom Built Algorithm

969

042: Secret to Success

970

041: An Inspiring Journey from a Totally Different Background to Data Science

971

040: Get in Touch

972

039: Key Data Science and Statistical Skills to Get Hired at VSCO

973

038: How to Get a Job in Data Science

974

037: Develop your Dream Data Science Career with Experfy

975

036: Happiness and Problem Solving

976

035: Build Your Own Data Science Masters Degree with David Venturi

977

034: Failure

978

033: Building a Personal Brand in Data Science with Senior Insights Manager Josh Coulson

979

032: Get Out There!

980

031: AB Testing, Kissmetrics and Ways to a Better Lifestyle with David Tanaskovic

981

030: Compartmentalization

982

029: Dive Into Deep Learning and Find Out Where Machines Can Outperform Humans With Ben Taylor

983

028: Pride and Humility

984

027: Career Choice, Disruptions in Finance and Application Stacks with Aziz Mamatov

985

026: Sweat Every Day

986

025: Women in STEM, Bench Science to Data Science and Data and Medical Ethics w/ Kimberly Deas

987

024: "What are you passionate about?"

988

023: Data in Marketing, Statistical Significance and Management and Career Advice

989

022: Seoi Pei - The Skin of Water

990

021: Applications of Data Science, Democratizing AI and Advice with Sinan Ozdemir

991

020: Generation Z Insights, Data Privacy and SQL and Database Design with Ilya Eremenko

992

019: Government Work, Revisiting Left Brain/Right Brain and Artistic Thinking with Ot

993

018: 20 Years in Data Analytics, Entrepreneurship, and Megatrends in Data with Jen Underwood

994

017: Partitioning, Roles in Database Infrastructure and SQL Databases with Colin Sloss

995

016: Data-Driven Operations, Consulting Approaches, and Mentoring with Richard Hopkins

996

015: Side Income, Stoic Philosophy, and the Importance of QA with Paul Brown

997

014: Credit Scoring Models, the Law of Large Numbers, and Model Building with Greg Poppe

998

013: 95% Accuracy Models, Winning People Over, and Saving Lives with Damian Mingle

999

SDS Special : Giving Up Coffee, IQ vs EQ and Asking the Right Questions with Vitaly Dolgov

1000

012: Online Learning, Tableau Insights and Ad Hoc Analytics with Megan Putney