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Machine Learning Ai Books Categories
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Artificial Intelligence: A Modern Approach (Hardcover)
By:
Stuart Russell
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Hands-On Machine Learning with Scikit-Learn and TensorFlow (ebook)
By:
Aurélien Géron
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Nexus: A Brief History of Information Networks from the Stone Age to AI (Hardcover)
By:
Yuval Noah Harari
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The Coming Wave: Technology, Power, and the Twenty-first Century's Greatest Dilemma (Hardcover)
By:
Mustafa Suleyman
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Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch (Paperback)
By:
Maxime Labonne
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Natural Language Processing with Transformers: Building Language Applications with Hugging Face (Paperback)
By:
Lewis Tunstall
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Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python (Paperback)
By:
Sebastian Raschka
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Build Your Own AI Investor : With Machine Learning and Python, Step by Step (A.I. Investor Series Book 2)
By:
Damon Lee
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Deep Learning from Scratch: Building with Python from First Principles (Paperback)
By:
Seth Weidman
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Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence (Addison-Wesley Data & Analytics Series)
By:
Jon Krohn
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Fundamentals of Deep Learning: Designing Next-Generation Artificial Intelligence Algorithms (Kindle Edition)
By:
Nikhil Buduma
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Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning (ebook)
By:
Alex J. Gutman
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Markov Models: Master Data Science and Unsupervised Machine Learning in Python (Kindle Edition)
By:
LazyProgrammer
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Superforecasting: The Art and Science of Prediction (Hardcover)
By:
Philip E. Tetlock
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Understanding Machine Learning (Hardcover)
By:
Shai Shalev-Shwartz
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Information Theory and Statistics (Dover Books on Mathematics)
By:
Solomon Kullback
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Reinforcement Learning and Optimal Control (ebook)
By:
Dimitri P. Bertsekas
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Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs, Series Number 5)
By:
Bradley Efron
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Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking (Paperback)
By:
Foster Provost
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An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
By:
Gareth James
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In All Likelihood: Statistical Modelling and Inference Using Likelihood (Hardcover)
By:
Yudi Pawitan
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Hardcover)
By:
Trevor Hastie
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Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play (Paperback)
By:
David Foster
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Linguistic Fundamentals for Natural Language Processing: 100 Essentials from Morphology and Syntax (Synthesis Lectures on Human Language Technologies, 20)
By:
Emily M. Bender
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Human Compatible: Artificial Intelligence and the Problem of Control (Hardcover)
By:
Stuart Russell
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Machine Learning for Absolute Beginners: A Plain English Introduction (First Edition)
By:
Oliver Theobald
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The Signal and the Noise: Why So Many Predictions Fail—But Some Don't (Hardcover)
By:
Nate Silver
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Introduction to Machine Learning with Python: A Guide for Data Scientists (Paperback)
By:
Andreas C. Müller
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Information Theory, Inference, and Learning Algorithms (Paperback)
By:
David J.C. MacKay
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The Hundred-Page Machine Learning Book (Paperback)
By:
Andriy Burkov
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How Smart Machines Think (Hardcover)
By:
Sean Gerrish
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The Book of Why: The New Science of Cause and Effect (Hardcover)
By:
Judea Pearl
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Grokking Deep Learning (ebook)
By:
Andrew W. Trask
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Python Machine Learning (Paperback)
By:
Sebastian Raschka
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Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference (Paperback)
By:
Cameron Davidson-Pilon
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Quantum Machine Learning: What Quantum Computing Means to Data Mining (Hardcover)
By:
Peter Wittek
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Doing Data Science: Straight Talk from the Frontline (Paperback)
By:
Cathy O'Neil
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Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
By:
Richard S. Sutton
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Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition (Hardcover)
By:
Dan Jurafsky
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Machine Vision: Theory, Algorithms, Practicalities (Signal Processing and its Applications)
By:
E.R. Davies
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AIQ: How People and Machines are Smarter Together (Kindle Edition)
By:
Nick Polson
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Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (Hardcover)
By:
Cathy O'Neil
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The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World (Hardcover)
By:
Pedro Domingos
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Too Big to Ignore: The Business Case for Big Data (Wiley & SAS Business)
By:
Phil Simon
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Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World (Hardcover)
By:
Leslie Valiant
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Naked Statistics: Stripping the Dread from the Data (Paperback)
By:
Charles Wheelan
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Cybernetics 2.0: A General Theory of Adaptivity and Homeostasis in the Brain and in the Body (Springer Series on Bio- and Neurosystems, 14)
By:
Bernard Widrow
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Understanding Understanding: Essays on Cybernetics and Cognition (Hardcover)
By:
Heinz von Foerster