Online courses are a great way to share knowledge with others; that is why I have decided to launch a few courses. The first course is Intro to Azure ML Studio – Regression. This is a smaller course and should take about 2 hours to complete.
Azure ML Studio is a drag-and-drop interface for doing machine learning.
Topics are all based upon Azure ML Studio, and they include:
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:
Microsoft Build 2019 – This is a huge conference hosted by Microsoft for the developer community. Many of the presentation are available to watch online. Not all are data science/AI related, but many are.
Google I/O 2019 Videos – Google’s big annual conference. Nearly all of the sessions are recorded. There are lots of AI talks and demos.
AWS DeepRacer – Learn reinforcement learning by programming an autonomous car and competing in races.
While it is not one of the popular programming languages for data science, The Go Programming Language (aka Golang) has surfaced for me a few times in the past few years as an option for data science. I decided to do some searching and find some conclusions about whether golang is a good choice for data science.
Popularity of Go and Data Science
As the following figure from Google Trends demonstrates, golang and data science became trendy topics at about the same time and grew at a similar rate.
The timely trends may have created the desire to merge the two technologies together.
Golang Projects for Data Science
Some internet searching will reveal a number of interesting Golang/Data Science projects on Github. Unfortunately, many of the projects had good initial traction but have dwindled in activity over the last couple years. Below is a listing of some of the data science related projects for Golang.
Gopher Data – Gophers doing data analysis, no schedule events, last blog post was 2017