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

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.

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

Link to 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 matrica – 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 PhD Programme 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

Frank Baia

Publisher, B2BAmericanSoutheast.com

3 年

We see a new world that is being shaped by a new consumer. Each community?a different facet of the same prism. Of course, future generations will be more and more involved in this process and market rules will be totally different in years to come, however something is changing from a consumer point of view. One focused on values like environmental protection and sustainability, the other on financial savings and opportunities to better spend their money. These smart consumers are concerned about the environment, interested in valuable and sustainable services, and indifferent to product ownership. They are looking for quality and durability, have no time to waste, and avoid waste in general, as they don’t like the very concept. Finally, consumers also expect to save money because they want to be rewarded by the system for their sustainable choices. An unstoppable, fast-growing trend has definitely accelerated consumer habits, people have been adopting new behaviors and are constantly looking for new valuable experiences. They want concrete, tangible benefits. This new category of consumers doesn't want to plant trees; they want to change the world. They want to live in a better world with more money in their pockets.

回复
EDDISON L.

@Knowledge Engineering is Evolutionary&

3 年

Ajit, the glossary is precise and accurate in content but could you include aspects relating to Causality, Robotics, and Quantum Computing.

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