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:
Similar tags include Neural Networks, Computer Vision, and Random Forests.
Happy Reading!
A beginner-friendly series on using Keras to build, train, and evaluate Neural Networks in Python.
View SeriesA beginner-friendly guide on using Keras to implement a simple Recurrent Neural Network (RNN) in Python.
ReadCo-Authored by Phillip Wang
A gentle introduction to Visual Question Answering (VQA) using neural networks.
ReadA quick, easy introduction to the Bag-of-Words model and how to implement it in Python.
ReadGuest Post by Ravi Rai
A brief guide on the fundamentals of linear algebra to get you started on your machine learning journey!
ReadGuest Post
A survey of the best programming languages for Artificial Intelligence and Machine Learning.
ReadGuest Post by Owen Leeks
A survey of the best programming languages for Artificial Intelligence and Machine Learning.
Read