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Python Machine Learning: Machine Learning and Deep Learning with Python scikit-learn and TensorFlow 2 3rd Edition
Hands-On Machine Learning with C++: Build train and deploy end-to-end machine learning and deep learning pipelines
Foundations of Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)
Machine Learning: A Practical Approach on the Statistical Learning Theory
Fuzzy Rule-BasedExpert Systems and Genetic Machine Learning.
Hands-On Artificial Intelligence for IoT: Expert machine learning and deep learning techniques for developing smarter IoT systems
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
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)
TensorFlow Deep Learning Projects: 10 real-world projects on computer vision machine translation chatbots and reinforcement learning
Machine Learning for Economics and Finance in TensorFlow 2: Deep Learning Models for Research and Industry
Machine Learning with TensorFlow
Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
Optimization for Machine Learning (Hard) <Neural Information Processing Series>
Encyclopedia of Machine Learning
Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists
Trustworthy Machine Learning
Machine Learning: The New AI (The MIT Press Essential Knowledge Series)
Machine Learning
Python for Probability Statistics and Machine Learning
Machine Learning for the Web
Structural Health Monitoring: A Machine Learning Perspective
MACHINE LEARNING (Int'l Ed)
Introduction to Machine Learning with Python: A Guide for Data Scientists
Thoughtful Machine Learning: A Test-Driven Approach
Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)
Exploring Zynq MPSoC: With PYNQ and Machine Learning Applications
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)
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
Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies
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
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