Tales of Science and DataBooks / Free eBooks
This is an ebook written as a series of Jupyter notebooks, “intended as a collection of personally elaborated materials on Data Science. Topics span a quite large spectrum in the Data Science field: nothing will ever be fully comprehensive, but the purpose is keeping this continuously updated. Learning never ends!” Content includes: Probability & Statistics Machine Learning: Supervised Learning Unsupervised Learning Artificial Neural Networks Model Assessment Natural Language Processing Computer … Continue Reading
Python for Informatics: Exploring InformationBooks / Free eBooks / physical books or multiple formats
From Amazon: “This book is designed to introduce students to programming and computational thinking through the lens of exploring data. You can think of Python as your tool to solve problems that are far beyond the capability of a spreadsheet. It is an easy-to-use and easy-to learn programming language that is freely available on Windows, Macintosh, and Linux computers. There are free downloadable copies of this book in various electronic … Continue Reading
Data Wrangling with PythonBooks / physical books or multiple formats
From O’Reilly: “How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information that’s initially too messy or difficult to access. Through various step-by-step exercises, you’ll learn how to acquire, clean, analyze, and present data efficiently. You’ll also discover how to automate your data process, schedule file- … Continue Reading
Python Data Science Handbook: Essential Tools for Working with DataBooks / physical books or multiple formats
From Amazon: “For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this … Continue Reading
Data Science from Scratch: First Principles with PythonBooks / physical books or multiple formats
From Amazon: “Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get … Continue Reading
Clearly ErroneousBlogs / Blogs, Podcasts, Etc.
This blog follows Martina Pugliese’s “explorations in this thing they call Data Science.” Posts include personal experiences in academia and the data science field, professional advice, and tutorials for technologies including Jupyter notebooks, Python, and NLTK.
Chris Albon’s blogBlogs / Blogs, Podcasts, Etc. / References, Learning Guides, Etc.
“Notes on Data Science, Machine Learning, & Artificial Intelligence” Chris Albon is a data scientist “with a Ph.D. in quantitative political science and a decade of experience working in statistical learning, artificial intelligence, and software engineering.” Since starting the site as a home for his “personal notes on statistics, data science and programming,” the site “has grown and today is visited by thousands everyday looking for information on everything from … Continue Reading
DataQuest Data Science BlogBlogs / Blogs, Podcasts, Etc.
Written by the makers of Dataquest.io, a data science tutorial site, the blog covers topics across data science from those curious about the field to specific tips for advanced users. Posts include: tips and tutorials for using Python, R, SQL, Kaggle, cheat sheets, definitions of data science terms, links to resources, data science success stories, and general advice on entering the data science field.
Advanced Analytics with Spark: Patterns for Learning from Data at ScaleBooks / physical books or multiple formats
From Amazon: “In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques—classification, collaborative filtering, and anomaly detection among others—to … Continue Reading
Learning Spark: Lightning-Fast Big Data AnalysisBooks / physical books or multiple formats
From Amazon: “Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and … Continue Reading