Machine Learning - Page 2
← Back to All Tags
Machine Learning is, put simply, getting computers to generalize from examples. And that's what I try to do: put [seemingly complicated] things simply. My posts on Machine Learning (ML) consist primarily of beginner-focused introductions to common ML models or concepts. I felt like too many ML tutorials weren't accessible enough, so I strove to make my guides as clear and beginner-friendly as possible.
Unsure where to start? Here are some of my best / most popular posts:
- An Introduction to Neural Networks
- An Introduction to Convolutional Neural Networks
- An Introduction to Recurrent Neural Networks
- Random Forests for Complete Beginners
Similar tags include Neural Networks, Computer Vision, and Random Forests.
Happy Reading!
Keras for Beginners: Implementing a Convolutional Neural Network
A beginner-friendly guide on using Keras to implement a simple Convolutional Neural Network (CNN) in Python.
ReadNeural Networks From Scratch
A 4-post series that provides a fundamentals-oriented approach towards understanding Neural Networks.
View SeriesAn Introduction to Recurrent Neural Networks for Beginners
A simple walkthrough of what RNNs are, how they work, and how to build one from scratch in Python.
ReadA Simple Explanation of the Softmax Function
What Softmax is, how it's used, and how to implement it in Python.
ReadKeras for Beginners: Building Your First Neural Network
A beginner-friendly guide on using Keras to implement a simple Neural Network in Python.
ReadA Simple Explanation of Information Gain and Entropy
What Information Gain and Information Entropy are and how they're used to train Decision Trees.
ReadCNNs, Part 2: Training a Convolutional Neural Network
A simple walkthrough of deriving backpropagation for CNNs and implementing it from scratch in Python.
ReadCNNs, Part 1: An Introduction to Convolutional Neural Networks
A simple guide to what CNNs are, how they work, and how to build one from scratch in Python.
Read