An enlightening video about how a single pixel change can fool a neural network.
Recently updated, is the March 2019 Machine Learning Study Path. It contains links and resources to learn Tensorflow and Scikit-Learn.
If you are interested in details on the study path and how to best use the resources. There is a livestream on Facebook, Sunday March 17 on the Math for Data Science Facebook page.
Machine Learning for Kids is a site for children and teachers to explore machine learning with the Scratch Programming language. It includes numerous lessons and tutorials for building fun programs which incorporate machine learning.
Brandon Rohrer (along with others) created an excellent resource for academic programs, Industry recommendations for academic data science programs. The resource is authored by a number of industry data scientists and university faculty. It is collection of useful information for college data science programs. Here are some of the topics:
- What do Industry data scientists do?
- What makes someone a good data scientist?
- How can universities partner with companies?
- and others
Plus, the site is growing, and new information is frequently being added. If your college/university is launching a data science program, this resource is a must read.
A new community for data visualization professionals has launched. It is called the Data Visualization Society. According to the website,
The Data Visualization Society aims to collect and establish best practices and foster community to support its members as they develop their data visualization skills.
Currently, membership is free and they are looking for help growing the community. If data visualization is your thing, this society is worth exploring.
Looking for datasets for your next project? You are in luck because Google just launched Dataset Search. The name is self-explanatory. Go try it out.
The University of California at Berkeley is offering its very popular undergraduate data science course, Foundations of Data Science: Computational Thinking with Python, online via EdX. The course can be taken for free and it starts Monday April, 2 , 2018.
This course is actually part of a larger certificate program, Foundations of Data Science. You must pay to receive the certificate.