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  • 深度学习迷你地图

    • Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

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    • Deep Learning with Python

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    • Deep Learning (Adaptive Computation and Machine Learning series)

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    • Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

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    • R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

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    • Python Data Science Handbook: Essential Tools for Working with Data

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    • Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition

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    • Python Pocket Reference: Python In Your Pocket (Pocket Reference (O'Reilly))

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    • The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

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    • An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

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    • Advances in Financial Machine Learning

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    • Introduction to Machine Learning with Python: A Guide for Data Scientists

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    • Data Science from Scratch: First Principles with Python

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    • R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics (O'reilly Cookbooks)

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    • Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)

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    • Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

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    • Learning Python, 5th Edition

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    • TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

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    • Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists

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    • Machine Learning For Absolute Beginners: A Plain English Introduction (Machine Learning For Beginners)

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    • Python Cookbook, Third edition

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    • Pattern Recognition and Machine Learning (Information Science and Statistics)

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    • Deep Learning: A Practitioner's Approach

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    • Make Your Own Neural Network: An In-depth Visual Introduction For Beginners

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    • ggplot2: Elegant Graphics for Data Analysis (Use R!)

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    • Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)

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    • Pro Deep Learning with TensorFlow: A Mathematical Approach to Advanced Artificial Intelligence in Python

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    • Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning

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    • Python Crash Course: A Hands-On, Project-Based Introduction to Programming

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    • Machine Learning For Dummies

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    • Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

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    • Fluent Python: Clear, Concise, and Effective Programming

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    • Introducing Python: Modern Computing in Simple Packages

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    • Naked Statistics: Stripping the Dread from the Data

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    • Machine Learning with R - Second Edition: Expert techniques for predictive modeling to solve all your data analysis problems

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    • Web Scraping with Python: Collecting More Data from the Modern Web

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    • R Graphics Cookbook: Practical Recipes for Visualizing Data

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    • Predictive Analytics For Dummies

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    • R For Dummies

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    • Natural Language Processing with TensorFlow: Teach language to machines using Python's deep learning library

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    • Deep Learning with R

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    • The Art of R Programming: A Tour of Statistical Software Design

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    • Artificial Intelligence For Dummies (For Dummies (Computer/Tech))

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    • Applied Predictive Modeling

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    • Text Mining with R: A Tidy Approach

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    • Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

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    • Hands-On Programming with R: Write Your Own Functions and Simulations

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    • Artificial Intelligence with Python: A Comprehensive Guide to Building Intelligent Apps for Python Beginners and Developers

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    • Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)

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    • Automate the Boring Stuff with Python: Practical Programming for Total Beginners

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    • Learning R: A Step-by-Step Function Guide to Data Analysis

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    • Effective Python: 59 Specific Ways to Write Better Python (Effective Software Development Series)

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    • The Math of Neural Networks

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    • Reinforcement Learning with TensorFlow: A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym

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    • Decision Trees and Random Forests: A Visual Introduction For Beginners

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    • Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies (The MIT Press)

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    • A Smarter Way to Learn Python: Learn it faster. Remember it longer.

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    • Make Your Own Neural Network

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    • Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

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    • Think Python: How to Think Like a Computer Scientist

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    • Numsense! Data Science for the Layman: No Math Added

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    • Python for Finance: Analyze Big Financial Data

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    • Data Smart: Using Data Science to Transform Information into Insight

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    • Artificial Intelligence: A Modern Approach

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    • Competing on Analytics: Updated, with a New Introduction: The New Science of Winning

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    • Think Stats: Exploratory Data Analysis

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    • Building Winning Algorithmic Trading Systems, + Website: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading (Wiley Trading)

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    • Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

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    • Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

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    • Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies

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    • Flask Web Development: Developing Web Applications with Python

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    • Think Bayes: Bayesian Statistics in Python

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    • Feature Engineering Made Easy: Identify unique features from your dataset in order to build powerful machine learning systems

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    • Python Machine Learning, 1st Edition

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    • Storytelling with Data: A Data Visualization Guide for Business Professionals

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    • Python Machine Learning By Example: The easiest way to get into machine learning

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    • Neuro-Dynamic Programming (Optimization and Neural Computation Series, 3)

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    • R for Excel Users: An Introduction to R for Excel Analysts

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    • Deep Learning with Keras: Implementing deep learning models and neural networks with the power of Python

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    • Bash Pocket Reference: Help for Power Users and Sys Admins

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    • Linux Pocket Guide: Essential Commands

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    • Naked Economics: Undressing the Dismal Science (Fully Revised and Updated)

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    • Git Pocket Guide: A Working Introduction

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    • Best Practices in Data Cleaning: A Complete Guide to Everything You Need to Do Before and After Collecting Your Data

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    • Blockchain For Dummies (For Dummies (Computers))

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    • Machine Learning (McGraw-Hill International Editions Computer Science Series)

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    • Convex Optimization, With Corrections 2008

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    • Statistics for Machine Learning: Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

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    • Reproducible Research with R and R Studio (Chapman & Hall/CRC The R Series)

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    • Algorithms For Dummies (For Dummies (Computer/Tech))

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    • The Cartoon Guide to Statistics

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    • Machine Learning with TensorFlow

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    • Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow

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    • Modeling Techniques in Predictive Analytics with Python and R: A Guide to Data Science (FT Press Analytics)

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    • Naked Money: A Revealing Look at Our Financial System

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    • Python Data Science Essentials - Second Edition: Become an efficient data science practitioner by understanding Python's key concepts

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    • Regression Modeling with Actuarial and Financial Applications (International Series on Actuarial Science)

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    • Think Complexity: Complexity Science and Computational Modeling

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    • Deep Learning Cookbook: Practical Recipes to Get Started Quickly

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    • Illustrated Guide to Python 3: A Complete Walkthrough of Beginning Python with Unique Illustrations Showing how Python Really Works. Now covering Python 3.6 (Treading on Python) (Volume 1)

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    • Algorithmic Trading and DMA: An introduction to direct access trading strategies

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    • Artificial Intelligence: 101 Things You Must Know Today About Our Future

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    • Django for Beginners: Build websites with Python and Django

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    • Big Data For Dummies

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    • Database Systems: A Practical Approach to Design, Implementation, and Management (6th Edition)

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    • The Statistical Sleuth: A Course in Methods of Data Analysis

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    • Programming Python: Powerful Object-Oriented Programming

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    • The Signal and the Noise: Why So Many Predictions Fail--but Some Don't

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    • Advanced and Multivariate Statistical Methods: Practical Application and Interpretation

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    • Python Essential Reference (4th Edition)

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    • Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!)

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    • Practical Web Scraping for Data Science: Best Practices and Examples with Python

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    • Head First Python: A Brain-Friendly Guide

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    • The Accounting Game: Basic Accounting Fresh from the Lemonade Stand

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    • How to Lie with Statistics

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    • Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More

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    • Algorithms for Reinforcement Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning)

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    • Python Machine Learning From Scratch: Step by Step Guide with Scikit-Learn and TensorFlow

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    • Neural Networks with R: Smart models using CNN, RNN, deep learning, and artificial intelligence principles

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    • Python Deep Learning

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  • 原文地址:https://www.cnblogs.com/Eufisky/p/9692422.html
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