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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)
Machine Learning from Weak Supervision: An Empirical Risk Minimization Approach (Adaptive Computation and Machine Learning series)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)
Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)
学習物理学入門 = Introduction to machine learning physics
Fuzzy Rule-BasedExpert Systems and Genetic Machine Learning.
Deep Learning (Adaptive Computation and Machine Learning series)
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)
Learning Deep Architectures for AI (Foundations and TrendsR in Machine Learning)
Machine Learning for Economics and Finance in TensorFlow 2: Deep Learning Models for Research and Industry
Optimization for Machine Learning (Hard) <Neural Information Processing Series>
Encyclopedia of 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
Trustworthy Machine Learning
Data Mining : Practical Machine Learning Tools and Techniques
Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists
Machine Learning: The New AI (The MIT Press Essential Knowledge Series)
Machine Learning
Structural Health Monitoring: A Machine Learning Perspective
Python for Probability Statistics and Machine Learning
MACHINE LEARNING (Int'l Ed)
Introduction to Machine Learning with Python: A Guide for Data Scientists
Thoughtful Machine Learning: A Test-Driven Approach
Approaching (Almost) Any Machine Learning Problem
Exploring Zynq MPSoC: With PYNQ and Machine Learning Applications
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>
Boosting: Foundations and Algorithms (Adaptive Computation and Machine Learning series)
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data Second Edition
Probability and Statistics for Machine Learning: A Textbook
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
Hands-On Data Science for Marketing: Improve your marketing strategies with machine learning using Python and R
Density Ratio Estimation in Machine Learning (Soft)
Sparse Modeling: Theory Algorithms and Applications (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting (Image Processing Computer Vision Pattern Recognition and Graphics)
Learning With Kernels: Support Vector Machines Regularization Optimization and Beyond (Adaptive Computation and Machine Learning Series)
Machine Learning Refined : 2nd Edition Foundations, Algorithms, and Applications
Building Machine Learning Powered Applications : Going from Idea to Product
Machine Learning Approaches to Bioinformatics (Science Engineering and Biology Informatics 4)
Machine Learning for Tomographic Imaging (Programme: Iop Expanding Physics)
Optimization for Machine Learning (Neural Information Processing Series)
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