Weekly Roundup: March 3rd - 8th
> Doing machine learning the right way by Rob Matheson | MIT News Office, March 7, 2020
A fascinating story on how professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable, and robust.
> Best Machine Learning Books (Updated for 2020) Alessio Gozzoli | March 3
If you enjoy reading, you will find this article helpful. The best positions you should read on machine learning.
> Step-By-Step Framework for Imbalanced Classification Projects by Jason Brownlee, March 9
A detailed tutorial on a systematic framework for working through an imbalanced classification dataset. An interesting read for those who want to learn techniques specifically designed for imbalanced classification.
- You can also check out Jason Brownlee’s book Imbalanced Classification with Python: Better Metrics, Balance Skewed Classes, Cost-Sensitive Learning for a longer read on the imbalanced classification
> 20 women doing fascinating work in AI, machine learning and data science by Elaine Burke, March 9
Here’s a little inspiration for all the ladies (and gentlemen) working in the ML field.
> Best 13 Machine Learning Methods And Techniques For Newbies by Nasir Hawlader, March 7
If you’re new to the world of machine learning and not sure which way to go, this article will be your guide.
> KDnuggets™ News of the week with top stories and tweets of the past week, plus opinions, tutorials, events, webinars, meetings, and jobs
> Don’t forget about the reliable Reddit thread on ML for more news on machine learning!
That’s all folks! I hope you found something of interest in this weekly roundup. Don’t forget to check our blog for more inspiring articles.
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