Artificial Intelligence, Machine Learning, and Deep Learning (Mercury Learning)
Friday, 06 March 2020

Beginning with an introduction to AI, machine learning, deep learning, NLP, and reinforcement learning, Oswald Campesato  covers machine learning classifiers such as logistic regression, k-NN, decision trees, random forests, and SVMs. The book also covers deep learning architectures such as CNNs, RNNs, LSTMs, and auto encoders. Keras-based code samples are included to supplement the theoretical discussion and has appendices for Keras, TensorFlow 2, and Pandas.

 

Author: Oswald Campesato
Publisher: Mercury Learning
Date: February 2020
Pages: 300
ISBN: 978-1683924678
Print: 1683924673
Kindle: B084P1K9YP
Audience: Developers interested in machine learning
Level: Introductory/Intermediate
Category: Artificial Intelligence

 

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Software Mistakes and Tradeoffs (Manning)

Author: Tomasz Lelek and Jon Skeet
Publisher: Manning
Date: June 2022
Pages: 426
ISBN: 978-1617299209
Print: 1617299200
Audience: C# developers
Rating: 4
Reviewer: Mike James
We all make mistakes - do you want to read about them?



Administering Relational Databases on Microsoft Azure

Author: Prashanth Jayaram et al
Publisher: Independent
Pages: 622
ISBN: 979-8706128029
Print: B08Y4LBTP4
Kindle: B08XZQJHMK
Audience: Azure DBAs
Rating: 2 or 4 (see review for details)
Reviewer: Ian Stirk

This book aims to help you pass the Azure Relational Database exam DP-300, how does it fare?


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