we focus on the personalization aspect of model building and explain the modeling principle as well as how to implement Photon-ML so that it can scale to hundreds of millions of users. by linkedin. 8 min read.
Neural networks are not just another classifier, they represent the beginning of a fundamental shift in how we write software. They are Software 2.0. by Andrej Karpathy. 5 min read.
Explained why blockchain and decentralization are important to the current and future technology. by Chris Dixon. 8 min read. Continue reading “Why Blockchain and Decentralization Matters”
What are Markov chains, when to use them and how they work. by Devin Soni. 5 min read. Continue reading “Markov Chains Explained”
This post explains why neural network is actually easy and simple to do, not hard as your thought. by Brandon Wirtz. 5 min read Continue reading “Neural network AI is simple”
Additional commonly used machine learning algorithms explained. by Shashank Gupta. 10 min read. Continue reading “Machine Learning Algorithms Every Data Scientist Should Know – Part 2”
This is a whirlwind tour of common machine learning algorithms and quick resources about them which can help you get started on them. by Reena Shaw. 15 min read.
In order to cope with this overwhelming speed of evolution and innovation, a good way to stay updated and knowledgeable on the advances of ML, is to engage with the community by contributing to the many open-source projects and tools. by KDNugget. 5 min read.