EPISODE · Jul 28, 2017 · 9 MIN
Hyperparameter Optimization - The Math of Intelligence #7
from Siraj Raval
Hyperparameters are the magic numbers of machine learning. We're going to learn how to find them in a more intelligent way than just trial-and-error. We'll go over grid search, random search, and Bayesian Optimization. I'll also cover the difference between Bayesian and Frequentist probability. Code for this video: https://github.com/llSourcell/hyperparameter_optimization_strategies Noah's Winning Code: https://github.com/NoahLidell/math-of-intelligence/tree/master/probability_theory Hammad's Runner-up Code: https://github.com/hammadshaikhha/Math-of-Machine-Learning-Course-by-Siraj/tree/master/Naive%20Bayes%20Classifier More learning resources: https://www.iro.umontreal.ca/~bengioy/cifar/NCAP2014-summerschool/slides/Ryan_adams_140814_bayesopt_ncap.pdf https://thuijskens.github.io/2016/12/29/bayesian-optimisation/ https://jmhessel.github.io/Bayesian-Optimization/ https://arimo.com/data-science/2016/bayesian-optimization-hyperparameter-tuning/ https://dhnzl.files.wordpress.com/2016/12/fuzzymad2016_bo_pdf.pdf http://blog.revolutionanalytics.com/2016/06/bayesian-optimization-of-machine-learning-models.html https://www.youtube.com/watch?v=cWQDeB9WqvU https://nlpers.blogspot.nl/2014/10/hyperparameter-search-bayesian.html http://neupy.com/2016/12/17/hyperparameter_optimization_for_neural_networks.html Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Thanks to Veritasium (bayesian animation) & Angela Schoellig (drone clip) Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/
What this episode covers
Hyperparameters are the magic numbers of machine learning. We're going to learn how to find them in a more intelligent way than just trial-and-error. We'll go over grid search, random search, and Bayesian Optimization. I'll also cover the difference between Bayesian and Frequentist probability. Code for this video: https://github.com/llSourcell/hyperparameter_optimization_strategies Noah's Winning Code: https://github.com/NoahLidell/math-of-intelligence/tree/master/probability_theory Hammad's Runner-up Code: https://github.com/hammadshaikhha/Math-of-Machine-Learning-Course-by-Siraj/tree/master/Naive%20Bayes%20Classifier More learning resources: https://www.iro.umontreal.ca/~bengioy/cifar/NCAP2014-summerschool/slides/Ryan_adams_140814_bayesopt_ncap.pdf https://thuijskens.github.io/2016/12/29/bayesian-optimisation/ https://jmhessel.github.io/Bayesian-Optimization/ https://arimo.com/data-science/2016/bayesian-optimization-hyperparameter-tuning/ https://dhnzl.files.wordpress.com/2016/12/fuzzymad2016_bo_pdf.pdf http://blog.revolutionanalytics.com/2016/06/bayesian-optimization-of-machine-learning-models.html https://www.youtube.com/watch?v=cWQDeB9WqvU https://nlpers.blogspot.nl/2014/10/hyperparameter-search-bayesian.html http://neupy.com/2016/12/17/hyperparameter_optimization_for_neural_networks.html Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Thanks to Veritasium (bayesian animation) & Angela Schoellig (drone clip) Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/
NOW PLAYING
Hyperparameter Optimization - The Math of Intelligence #7
No transcript for this episode yet