A unified repository of coursework fragments from UC Berkeley MIDS Program 2022-2024. This is a collection of my adapted assignment submissions, classwork notebooks, and other relevant materials. It serves to showcase the scope of work, and also for personal reference.
🏗 Under Construction - Notebook Addition in Progress
I've taken the following core ML courses during my time at MIDS:
-
- Course Info: Barebones ML, Breadth of Models
- Course Project: 🍃 Leafydex - Leaf Classification
-
- Course Info: Data Engineering & Model Training with Apache Spark
- Course Project: 🛬 US Flight Delay Prediction
-
- Course Info: Neural Network Models with Transformers
- Course Project: 🏂 Snowplough - News Topic Classification & Bias Analysis
-
- Course Info: LLMs, Stable Difussion, RAGs, Prompt Engineering
| Notebook | Description |
|---|---|
| Stable Diffusion & Image Validation | Multimodal image generation and captioning with diffusers, CLIP, BLIP and Llava |
| Prompt Engineering | Prompt Engineering Examples with Mistral7B |
| Retrieval Augmented Generation Proof-of-Concept | Google Colab notebook and report using Mistal7B, Cohere and Qdrant to develop a simple RAG system and iterate on performance |
| Notebook | Description |
|---|---|
| Introduction to Supervised Learning | Road to Linear Regression with Generalization and MSE (Mean Squared Error) calculation |
| Notebook | Description |
|---|---|
| PyTorch Introduction | A basic introduction to tensors, classes, and operations in PyTorch |