I'm a beginner in the world of machine learning. I'll be practicing and experimenting in this repository. I've made it public for others interested in seeing my learning process.
- Machine Learning Tests - Playing with recommendation systems and image classification
- Dog V Cat Classifier - Classifies images of dogs and cats, I used a lot of Sentdex's tutorials
- Sentiment Analysis - My rough attempt at a naive bayes sentiment classifier from scratch (results are poor)
- Improved Sentiment Analysis - Followed a tutorial and used libraries. Random tree classifier + word2vec to perform sentiment analysis. Trained on a 25k movie rating dataset.
- MNIST Beginner - Logistic regression classifier by tensorflow tutorial
- Neural Network Library - A Python Neural Network library w/ numpy
- Genetic Algorithm - While genetic algo's fall under the category of AI, I don't have an AI repository, so I'm putting this here. Really basic example for me to grasp concepts
- Recurrent Neural Network - Creating a RNN with numpy (additionally with docker, which I just started using recently)
- Python Machine Learning
- Deep Learning (recommended)