Summarizing Mathematical Machine Learning Topic from Graduate Level Mathematics Books


I would like to collect all definitions, lemmas and theorems from several chapters (~30 pages overall) from books (in pdf) in the area of machine learning.

Example of the mathematical material can be found for example by looking at SVM on wikipedia.

The final document should contain definitions and theorems, in short language, and in bullets, divided by sections to topics. No need to explain, just put summarized items in bullets, so it will contain the essential information in definitions and theorems at least technically.

A method of similar summarizing and organizing can be found at Schaum's Outline series' books, without excersices (they don't have a book on this subject though).

It is also possible to receive several books on the same topic, in order to understand better when needed.

The notation should be consistent across the document and the document should contain a Notation section.

The document should be written using the open-source LyX word processor.

The purpose of this document it to give practical machine learning software engineers a short handbook of some topics. The final length of the document for this project is about 2-3 loose pages.

Skills: Article Rewriting, Editing, Ghostwriting, Mathematics, Research Writing

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About the Employer:
( 17 reviews ) Tel Aviv, Israel

Project ID: #2575195