Machine learning basics This repository contains implementations of basic machine learning algorithms in plain Python (Python Version 3.6+). All algorithms are implemented from scratch without using ...

In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised ...

Though we're living through a time of extraordinary innovation in GPU-accelerated machine learning, the latest research papers frequently (and prominently) feature algorithms that are decades, in ...

Machine learning algorithms can also predict financial risks by raising alarms about fraudulent activities. Business managers can tighten security by setting alerts including duplicate payments to ...

A machine learning algorithm trained to carry out unsupervised learning tasks must be able to infer the relevant patterns in the data for itself. Supervised learning algorithms are typically used for ...

But as Pedro Domingos points out in The Master Algorithm, machines that learn have been deeply involved with our lives for a while. If you use Google, Netflix, Amazon, Pandora, Yelp, Xbox or just ...

Machine learning approaches fall into three main categories: heuristic models, statistical models, and models inspired by biology (such as neural networks and evolutionary algorithms).

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing ...

Machine learning algorithms are used in many industries, such as finance, healthcare and so on. Content marketing is one of the most popular industries where machine learning can be applied.