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Python Machine Learning: Machine Learning and Deep Learning with Python scikit-learn and TensorFlow 2 3rd Edition
Foundations of Machine Learning (Adaptive Computation and Machine Learning)
Hands-On Machine Learning with C++: Build train and deploy end-to-end machine learning and deep learning pipelines
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)
Fuzzy Rule-BasedExpert Systems and Genetic Machine Learning.
Machine Learning: A Practical Approach on the Statistical Learning Theory
Hands-On Artificial Intelligence for IoT: Expert machine learning and deep learning techniques for developing smarter IoT systems
TensorFlow Deep Learning Projects: 10 real-world projects on computer vision machine translation chatbots and reinforcement learning
機械学習(マシンラーニング)と深層学習(ディープラーニング)
Machine Learning for Economics and Finance in TensorFlow 2: Deep Learning Models for Research and Industry
Learning Deep Architectures for AI (Foundations and TrendsR in Machine Learning)
Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools techniques and algorithms for computer vision and machine learning 3rd Edition
Machine Learning with TensorFlow
Encyclopedia of Machine Learning
Trustworthy Machine Learning
Machine Learning
Machine Learning for the Web
Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
Optimization for Machine Learning (Hard) <Neural Information Processing Series>
Structural Health Monitoring: A Machine Learning Perspective
MACHINE LEARNING (Int'l Ed)
Introduction to Machine Learning with Python: A Guide for Data Scientists
Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists
Machine Learning: The New AI (The MIT Press Essential Knowledge Series)
Thoughtful Machine Learning: A Test-Driven Approach
Approaching (Almost) Any Machine Learning Problem
Machine Learning for OpenCV: Intelligent image processing with Python
Machine Learning Techniques for Online Social Networks (Lecture Notes in Social Networks)
Sparse Modeling: Theory, Algorithms, and Applications <(Chapman & Hall/CRC Machine Learning & Pattern Recognition)>
The Calabi?Yau Landscape From Geometry, to Physics, to Machine Learning <Lecture Notes in Mathematics 2293>
Scaling up Machine Learning: Parallel and Distributed Approaches
Boosting: Foundations and Algorithms (Adaptive Computation and Machine Learning series)
Statistical and Machine Learning Approaches for Network Analysis (Wiley Series in Computational Statistics)
Python for Probability Statistics and Machine Learning
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data Second Edition
Financial Signal Processing and Machine Learning (IEEE Press)
Probability and Statistics for Machine Learning: A Textbook
Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)
Exploring Zynq MPSoC: With PYNQ and Machine Learning Applications
Practical Time Series Analysis: Prediction with Statistics and Machine Learning
Linear Algebra and Optimization for Machine Learning: A Textbook
Driving Digital Transformation through Data and AI: A Practical Guide to Delivering Data Science and Machine Learning Products
GPU parallel computing for machine learning in Python: how to build a parallel computer
Hands-On Data Science for Marketing: Improve your marketing strategies with machine learning using Python and R
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