.NET .NET Blog Application Models Web Mobile Desktop Microservices Gaming Machine Learning Cloud Internet of Things Language Version C# Visual Basic F# 4.7 Platform Version Feature .NET Core 3.0 (runs anywhere!) Windows, Linux, and macOS .NET Framewo…

Awesome Reinforcement Learning A curated list of resources dedicated to reinforcement learning. We have pages for other topics: awesome-rnn, awesome-deep-vision, awesome-random-forest Maintainers: Hyunsoo Kim, Jiwon Kim We are looking for more contri…

A beginner’s introduction to Deep Learning I am Samvita from the Business Team of HyperVerge. I joined the team a few months back to help out on User Growth, PR and Marketing. From when I first heard about HyperVerge, I had one question – What is thi…

Why are very few schools involved in deep learning research? Why are they still hooked on to Bayesian methods? First, this question assumes that every university should have a "deep learning" person.  Deep learning is mostly used in vision (and…

Complete Small Focused Projects and Demonstrate Your Skills (完成小型针对性机器学习项目,证明你的能力) A portfolio is typically used by designers and artists to show examples of prior work to prospective clients and employers. Design, art and photography are examples wh…

https://www.quora.com/How-do-I-learn-machine-learning-1?redirected_qid=6578644   How Can I Learn X? Learning Machine Learning Learning About Computer Science Educational Resources Advice Artificial Intelligence How-to Question Learning New Things Lea…

https://www.quora.com/How-do-I-learn-mathematics-for-machine-learning   How do I learn mathematics for machine learning? Promoted by Time Doctor Software for productivity tracking. Time tracking and productivity improvement software with screenshots…

A Gentle Guide to Machine Learning Machine Learning is a subfield within Artificial Intelligence that builds algorithms that allow computers to learn to perform tasks from data instead of being explicitly programmed. Got it? We can make machines lear…

博客已经迁移至Marcovaldo's blog (http://marcovaldong.github.io/) Andrew Ng的Machine Learning比較简单,已经看完.林田轩的机器学习基石很多其它的是从概率论的角度来介绍机器学习,之前的视频已经听了大半.但好多都是模棱两可. 如今从头開始,认真整理笔记.笔记的结构遵从课程视频的结构. 以下是机器学习基石的第一讲:the learning problem Course Introduction 机器学习是一门理论和实践相结合的课…

Problems[show] Classification Clustering Regression Anomaly detection Association rules Reinforcement learning Structured prediction Feature engineering Feature learning Online learning Semi-supervised learning Unsupervised learning Learning to rank…