Recommended Books

Here is an opinionated list of great books for those interested in growing as data and machine learning professionals.

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“Our job is obvious: We need to get out of the way, shine a light, and empower a new generation to teach itself and to go further and faster than any generation ever has.”
~ Seth Godin

	Applied Predictive Modeling by Kuhn, Max, & Johnson, Kjell			Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann
	Practical Simulations for Machine Learning: Using Synthetic Data for AI by by Paris Buttfield-Addison, Mars Buttfield-Addison, Tim Nugent, & Jon Manning			Advanced R, Second Edition (Chapman & Hall/CRC The R Series) by Hadley Wickham
	Deep Learning (Adaptive Computation and Machine Learning Series) by Ian Goodfellow, Yoshua Bengio, & Aaron Courville			Data Engineering with Python: Work with massive datasets to design data models and automate data pipelines using Python by Paul Crickard
	Practical Statistics for Data Science: 50 Essential Concepts by Peter Bruce, & Andrew Bruce			An Introduction to Statistical Learning: with Applications in R by Gareth James, Daniela Witten, Trevor Hastie, & Robert Tibshirani
	The Hundred-Page Machine Learning Book by Andriy Burkov			Machine Learning Engineering by Andriy Burkov
	Data Science from Scratch: First Principles with Python by Joel Grus			Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
	Data Science Projects with Python: A case study approach to gaining valuable insights from real data with machine learning, 2nd Edition by Stephen Klosterman			The Art of R Programming: A Tour of Statistical Software Design by Norman Matloft
	Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking by Foster Provost & Tom Fawcett			Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst by Dean Abbott
	A General Introduction to Data Analytics by João Moreira, Andre Carvalho, & Tomás Horvath			Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing, and Presenting Data by EMC Education Services
	Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics by James Taylor			Systems Analysis and Design Shelly Cashman by Scott Tilley & Harry Rosenblatt
	Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic			Learn Python 3 the Hard Way: A Very Simple Introduction to the Terrifying Beautiful World of Computer and Code by Zed Shaw
	Python for Data Analysis: Data Wrangling with Pandas, Numpy, and IPython by William McKinney			R For Data Science: Import, Tidy, Transform, Visualize, and Model Data by Garrett Grolemund & Hadley Wickham
	Mastering Shiny: Build Interactive Apps, Reports, and Dashboards Powered by R			The Proximity Principle: The Proven Strategy That Will Lead to a Career You Love
	Spark: The Definitive Guide: Big Data Processing Made Simple			Build a Career in Data Science
	Hands-On Data Analysis with Pandas: A handbook for data collection, wrangling, analysis, and visualization			Handbook of Parametric and Nonparametric Statistical Procedures, Fifth Edition