Recommended Books on ML/DL

October 31, 2019 sherry 0 Data Science, Design, Engineering, Explaining of Israel, Technology,

Tags: and Prediction, and Techniques to Build Intelligent Systems, and TensorFlow: Concepts, Bayesian Data Analysis, Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science), Data Science from Scratch: First Principles with Python, deep learning, Deep Learning (MIT Press Essential Knowledge series), Deep Learning from Scratch: Building With Python From First Principles, Deep Learning Tutorial By LISA Lab, Deep Learning with Python, Deep Learning: Methods and Applications (Foundations and Trends in Signal Processing), From Theory to Algorithms, Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms, Hands-On Machine Learning with Scikit-Learn, Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Inference, Keras, MACHINE LEARNING, Machine Learning: A Probabilistic Perspective, Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series), Machine Learning: An Algorithmic Perspective, Machine Learning: The Art and Science of Algorithms that Make Sense of Data, Pattern classification, Pattern Classification with Computer Manual Set, Pattern Recognition and Machine Learning, Pattern Recognition Machine Learning, The Elements of Statistical Learning, The Elements of Statistical Learning: Data Mining, The Nature of Statistical Learning Theory (Information Science and Statistics), Third Edition (Chapman & Hall/CRC Texts in Statistical Science), Tools, Understanding Machine Learning, Understanding Machine Learning: From Theory to Algorithms, University of Montreal, למידה חישובית, למידה עמוקה, ספר deep learning, ספר machine learning, ספר למידה חישובית, ספר למידה עמוקה