Artificial Intelligence

Hello! Welcome to this guide to machine learning pipeline. If you want to get up-to-speed with some of the most data modeling techniques and gain experience using them to solve challenging problems, this is a good book for you!

Data Science is a growing field. Want to learn the popular java programming language and Stanford NLP to do text mining and Natural Language Processing, this is the book to grab.

In this dissertation, we present hypothesis-based collaborative filtering (HCF) to expose individuals to products which best fits their preferences. HCF retrieves like-minded individuals based on the similarity of their hypothesized preferences by means of machine learning algorithms hypothesizing individuals’ preferences.

This book introduces a formal framework for measuring ignorance (or nescience) and for guiding scientific discovery. Grounded in computability theory, Kolmogorov complexity, and artificial intelligence, the book analyzes how representations and models encode knowledge, and how their limitations can be quantified. The result is a new perspective on unknown unknowns, perfect knowledge, and the limits of science. For readers interested in artificial intelligence, scientific discovery, and the foundations of knowledge.