Everything you really need to know in Machine Learning in a hundred pages!
This book provides a great practical guide to get started and execute on ML within a few days without necessarily knowing much about ML apriori. The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue. A wonderful book for engineers who want to incorporate ML in their day-to-day work without necessarily spending an enormous amount of time going through a formal degree program.
Pages : | 159 pages |
Size : | PDF files |
File type : | |
Downloads: | 130 |
Created: | 2020-08-30 |
License: | "read first, buy later " |
Author(s): | Andriy Burkov |
An Introduction to Machine Learning, 2nd Edition
Machine Learning with TensorFlow
Machine Learning for Cyber Physical Systems
Interpretable Machine Learning: A Guide for Making Black Box Models Explainable
Using Scheme, a dialect of the Lisp programming language, the book explains core computer science concepts....
Software Innovation: Eight Work-style Heuristics for Creative System DevelopersSoftware Innovation: eight work-style heuristics for creative system developers. ...
Managing Projects with GNU MakeDownload free course Managing Projects with GNU Make, pdf file on 272 pages by Robert Mecklenburg....
Fundamentals of CryptologyDownload fundamentals cryptography pdf tutorial, a complete and free training document under 603 pages by Henk C.A. van Tilborg....
GIS SuccinctlyDownload free course GIS Succinctly, pdf file on 108 pages by Peter Shaw....
Thinking Forth: A Language and Philosophy for Solving ProblemsThinking Forth is a book about the philosophy of problem solving and programming style, applied to the unique programming language Forth. Published first in 1984, it could be among the timeless classics of computer books, such as Fred Brooks' The Mythical Man-Month and Donald Knuth's The Art of Comp...
Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System DesignersMachine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of ma...
Think ComplexityDownload free course Think Complexity, pdf file on 228 pages by Allen Downey....
Computational Thinking EducationDownload free course Computational Thinking Education, pdf file on 377 pages by Siu-Cheung Kong, Harold Abelson....
Open Source Systems: Towards Robust PracticesDownload free course Open Source Systems: Towards Robust Practices, pdf file on 225 pages by Federico Balaguer, Roberto Di Cosmo, Alejandra Garrido, Fabio Kon, Gregorio Robles, Stefano Zacchiroli....