Learning ML

My first foray into machine learning, comprised of Jupyter notebooks from my early undergrad years (2021-2022)

Note: I've preserved these notebooks as a time capsule into my early ML engineering thought processes and coding patterns, so you can expect inconsistent and suboptimal experimentation.

Order of Development

Avocado Prices - Fall 2021

Uses a basic Scikit Learn KNN model and cross validation to classify avos by location based on sales 🥑

Sequential Machine Learning - Fall 2021

Uses Tensorflow 2 with Keras to build a simple RNN to forecast FOREX time series data 💰

Spaceship Titanic - Fall 2021

Uses PCA and an ANN to predict the interdimensional transportation of interstellar passengers 🛸

Ships in Satellite Images - Fall 2021

Uses a CNN to detect ships in the water from satellite imagery (a fork of work from Sandrita Sarkar) 🚢

Neural Net from Scratch - Winter 2021

Uses NumPy to build an ANN from scratch for multi-class classification on the Fashion MNIST dataset 💃🏽

Pokemon MNIST PCA - Winter 2021

Uses PCA and transfer learning to compare what Pokemon embeddings look like in their own latent space vs the MNIST latent space 👾