One of the biggest obstacles to successful projects has been getting access to interesting data. Here are some more cool public data sources you can use for your next project.
As 2016 comes to a close and we prepare for a new year, check out the final instalment in our "Main Developments in 2016 and Key Trends in 2017" series, where experts weigh in with their opinions.
Also 20 Questions to Detect Fake Data Scientists; Software used for Analytics, Data Science, Machine Learning projects; Top Algorithms and Methods Used by Data Scientists
Read this engaging overview of a report from the Stanford University 100 year study of Artificial Intelligence, “a long-term investigation of the field of Artificial Intelligence (AI) and its influences on people, their communities, and society.”
Key themes included the polling failures in 2016 US Elections, Deep Learning, IoT, greater focus on value and ROI, and increasing adoption of predictive analytics by the "masses" of industry.
Two free ebooks: "Building Machine Learning Systems with Python" and "Practical Data Analysis" will give your skills a boost and make a great start in the New Year.
A Funny Look at Big Data and Data Science
Machine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017
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