Schmidt Eric. Grokking Algorithms: Simple and Effective Methods to Grokking Deep Learning and Machine Learning

Independently published, 2023. — 102 p.In the past decade, Artificial Intelligence has been making waves. From self-driving cars to Siri to Alexa, Artificial Intelligence (AI) is everywhere. But what exactly is it?The term "artificial intelligence" was coined in 1956 by John McCarthy, a computer scientist at Dartmouth College. His work was based on the idea that computers could be made to exhibit intelligent behavior if they were programmed correctly.Since then, many people have taken up the mantle of creating intelligent machines-from engineers and computer scientists like Alan Turing and John von Neumann to psychologists like B. F. Skinner and Ivan Pavlov. And today, dozens of different types of artificial intelligence algorithms are being used by companies worldwide: deep learning algorithms, machine learning algorithms… even genetic algorithms!One of these techniques is called deep learning. Deep learning allows computers to learn from huge amounts of data, and it's been used to help computers recognize images, understand language, and even drive cars. This book will teach you all about the Grokking algorithms behind machine learning and deep learning: what they are, how they work, and where they come from. We'll start with the basics of what an algorithm is in general - what it does, how it works - and then move into more specific details about what makes these particular algorithms so powerful.Introduction to Deep Learning.
How Do Machines Learn?
Introducing Neural Prediction via Forward Propagation.
Introducing Neural Learning Via Gradient Descent.
Let’s Talk Gradient Descent.
Let’s Talk Backpropagation.
Introducing Regularization and Batching.
Probabilities and Nonlinearities with Activation Functions.
Introducing Convolutional Neural Networks.
Recurrent Layers for Variable-Length Data.
Introducing Automatic Optimization.