Avrim Blum, John Hopcroft, and Ravindran Kannan wrote the book, Foundations of Data Science (PDF download). It is free and available for download. It can be useful for academic work or in business. It covers topics such as:
The textbook for the UC Berkeley Data Science course is available for free online at Computational and Inferential Thinking.It is an online textbook and appears to be created as a collection of Jupyter notebooks. Here are some of the topics covered:
Amazon just launched ‘Machine Learning University’ to all developers. It is the same training available for internal Amazon Employees. If you are looking to learn about Amazon Web Services (AWS) offerings for data science, now might be a great time to learn. Plus, Amazon announced some new certifications for machine learning. There are 4 different learning paths available, depending upon your goals and future job aspirations:
Reinforcement Learning: An Introductionby Rich Sutton and Andrew Barto was recently released on October 15, 2018. The authors were kind enough to put a late draft version of the book online as a PDF. If you are hoping to learn about Reinforcement Learning, this is a great place to start.
This month, The Data Incubator is hosting another free webinar on data science. This time it features an interview with Jake Porway, founder of DataKind. Jake and DataKind are doing amazing things, so I hope you can check out the webinar.
Below are the webinar details:
Data Science in 30 Minutes: Using Data Science in the Service of Humanity
Abstract: With his non-profit, DataKind, Jake Porway connects data scientists with social causes. Picture Doctors Without Borders for data nerds—with machine learning and AI engineers parachuting in to help the UN with humanitarian tasks, like tracking virus outbreaks using mobile data. “Data is like a bucket of crude oil,” Porway says. “Potentially great, but only if someone knows how to refine it (data scientists) and someone else has vehicles that will run on it (the social sector).” In this talk, Porway discusses the strategies of DataKind, its projects and the future of big data to service humanity.