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:
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.
Here are the latest articles from Microsoft regarding cloud data science products and updates. This week it includes Measuring Model Goodness, a free ebook, AI discovery days, and more AI goodness.
Measuring Model Goodness – Part 2 – Measurability is an important aspect of the Team Data Science Process (TDSP) as it quantifies how good the machine learning model is for the business and helps gain acceptance from the key stakeholders. In part 1 of this series, we defined a template for …[Read More]
AI Discovery Days at a Microsoft Location Near You – Join us to learn how to start building intelligence into your solutions with the Microsoft AI platform, including pre-trained AI services like Cognitive Services and Bot Framework, as well as deep learning tools like Azure Machine Learning.[Read More]
Describe, diagnose, and predict with IoT Analytics – … in IoT Analytics Machine learning (ML) is playing an increasingly important role in IoT analytics. One could argue that the recent emergence of real-world applications of ML in manufacturing is thanks to the explosion of data, most of which we can …[Read More]