Edition 4: A simplified glossary for machine learning and deep learning

Hello all. Our course at the #universityofoxford on developing AI starts in the first week of June and registrations close next week

In this post, I am going to share something I am working on for this course

I created the attached glossary as a mechanism to teach AI (machine learning and deep learning) because I could not find a concise machine learning glossary for getting started in AI.

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The glossary is based on the excellent Google Machine Learning Glossary

My document is a subset of the Google glossary. I created the following categories:

· Foundations of Machine Learning

· Regression

· Classification

· Reinforcement learning

· Model evaluation

· Clustering

· Neural Network

· Natural Language Processing

I maintain this Glossary. If you want to suggest any additions, please let me know

Over time, we plan to enhance it with other references

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The link to the glossary is HERE

Again, there are some interesting jobs shared by my network

We (Digitty) – Sebastian Britz are recruiting for a data engineer

Sue Sentence – chief learning officer of the Raspberry Pi is looking up for research interns

Tansy Brook at Oracle is recruiting for senior product marketing managers

My friend and colleague Devrim Sonmez is recruiting full-stack developers for matric – on which he is on the board

Prof Christopher Lau has an interesting position: Applications welcome for a part-time academic position as Associate Director – Health Data Research UK (HDR UK)-The Alan Turing Institute Ph.D. Program in Health Data Science

Finally, not a job but a very good explanation of transformers by Nikolas Adaloglou

kind rgds

Ajit

Image source: study.com