[Pagsusuri] Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (Aurélien Géron) Nabuod.

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (Aurélien Géron) - Amazon USA Store: https://www.amazon.com/dp/1098125975?tag=9natree-20 - Amazon Worldwide Store: https://global.buys.trade/Hands-On-Machine-Learning-with-Scikit-Learn%2C-Keras%2C-and-TensorFlow-Aur%C3%A9lien-G%C3%A9ron.html - Apple Books: https://books.apple.com/us/audiobook/hands-on-machine-learning-with-scikit-learn-keras/id1825991771?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree - eBay: https://www.ebay.com/sch/i.html?_nkw=Hands+On+Machine+Learning+with+Scikit+Learn+Keras+and+TensorFlow+Aur+lien+G+ron+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1 - Shopee: https://asia.buys.trade/shopee_Hands-On-Machine-Learning-with-Scikit-Learn%2C-Keras%2C-and-TensorFlow-Aur%C3%A9lien-G%C3%A9ron.html - Lazada: https://asia.buys.trade/lazada_Hands-On-Machine-Learning-with-Scikit-Learn%2C-Keras%2C-and-TensorFlow-Aur%C3%A9lien-G%C3%A9ron.html - Tiktok: https://asia.buys.trade/tiktok_Hands-On-Machine-Learning-with-Scikit-Learn%2C-Keras%2C-and-TensorFlow-Aur%C3%A9lien-G%C3%A9ron.html - Magbasa pa: https://tagalog.9natree.com/read/1098125975/ #Endtoendnaproyektongmachinelearning #ScikitLearnpipelines #Overfittingatgeneralization #KerasatTensorFlow #CNN,transformers,atreinforcementlearning #HandsOnMachineLearningwithScikitLearnKerasandTensorFlow Ang Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow ni Aurélien Géron ay isang praktikal na gabay sa machine learning at deep learning para sa mga programmer na gustong bumuo ng mga sistemang natututo mula sa datos. Ikatlong edisyon ito, inilathala noong 2022, at gumagamit ng Python kasama ang Scikit-Learn, Keras, at TensorFlow. Hindi ito aklat na nakatuon lamang sa mga pormula o abstraktong teorya. Ang pangunahing layunin nito ay ipakita kung paano nagiging isang gumaganang proyekto ang mga konsepto, mula sa pag-unawa sa problema at paghahanda ng datos hanggang sa pagsasanay, pagsusuri, pagpapahusay, at paglalagay ng modelo sa aktuwal na paggamit. Saklaw nito ang klasikong mga algorithm gaya ng linear regression, support vector machines, decision trees, random forests, clustering, at dimensionality reduction. Umaabot din ito sa neural networks, computer vision, pagproseso ng sequence, generative models, transformers, at reinforcement learning. Mahalaga ang diin ng aklat sa mga halimbawa ng code at pagsasanay, kaya ang mambabasa ay hindi lang nakaaalam kung ano ang isang modelo, kundi nauunawaan din kung kailan ito gagamitin, paano susukatin, at paano maiiwasan ang karaniwang pagkakamali.