Free Reinforcement Learning Textbook

Reinforcement Learning: An Introduction by 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.

Full text is available on a Google Drive at Reinforcement Learning. Take a look.

Good Luck and Happy Learning.

Data Science in 30 Minutes with Jake Porway of DataKind

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.

The free online webinar is:

Thu, November 15, 2018 @ 5:30 PM – 6:30 PM EST

You can register at Data Science in 30 minutes.

Microsoft Weekly Data Science News for September 07, 2018

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.

Microsoft Weekly Data Science News for August 31, 2018

Here are the latest articles from Microsoft regarding cloud data science products and updates. Find the latest on AI, Azure Functions, IoT and more.

Microsoft Weekly Data Science News for August 24, 2018

The latest articles from Microsoft regarding cloud data science products and updates.

  • Build Intelligent Web App with Machine Learning ServiceIn an earlier article: How to operationalize TensorFlow models in Microsoft Machine Learning Server, we showed how you can deploy a TensorFlow image classification model pre-trained using ImageNet as service in Machine Learning Server, and download a …[Read More]
  • Measuring Model Goodness – Part 1Data and AI are transforming businesses worldwide from finance … actionable insights. This is where data science and machine learning come in. This entire process has been documented as the Team Data Science Process (TDSP) at Microsoft, captured in …[Read More]
  • Driving industry transformation with Azure – Getting started – Edition 1Banking customers want more from their services … using AI and machine learning to detect patient risk and identify disease faster while maintaining privacy and protecting against fraud. IoT in manufacturing isn’t just about collecting data.[Read More]
  • Speech Services August 2018 updateWe are pleased to announce the release of another update to the Cognitive Services Speech SDK (version 0.6.0 … dev kits to significantly improve the audio quality of the audio data collected via the dev kits’ microphones, for high speech recognition …[Read More]
  • Introducing yet another approach for iot compiler toolchains – iotziotz is an extension based containerized wrapper for other IoT compiler toolchains. There are many toolchains with specific needs and way of using. We developed this experimental tool to make compiling things easier. – cross compiling tools are mostly …[Read More]
  • Design against crime & Microsoft Azure with ShinyIt is this app we will later learn how to deploy a shiny app onto Microsoft Azure services … including a review of data available via We engaged with UCL to find a student from the Security and Crime Science course who could help us to …[Read More]
  • Simplifying big data analytics architecturemanufacturing, retail education, nonprofit, government, healthcare, media, banking, telecommunication, insurance, and many more industries ranging in use cases from ETL to Data Warehousing, from Machine Learning to IoT, and more.[Read More]
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