Skip to content

Girish-Krishnan/ECE-SIPP-Python-ML

Repository files navigation

UCSD ECE Summer Internship Prep Program

Python and Machine Learning Workshop

Girish Krishnan | LinkedIn | GitHub

Python 3.9+ MIT License

This repository collects small but complete examples for learning scientific computing and machine learning with Python, for the UCSD ECE Summer Internship Prep Program.

Directory overview

  • 0_Foundations/ – introductory pandas examples for data analysis and visualization.
  • 1_Supervised_ML/ – basic supervised machine learning tutorials using scikit-learn.
  • 2_Unsupervised_ML/ – clustering and dimensionality reduction examples with scikit-learn.
  • 3_Deep_Learning/ – PyTorch based training scripts from simple MLPs to transfer learning.
  • 4_NLP/ – natural language processing tutorials using Hugging Face Transformers, covering text classification, tokenization, and more.
  • 5_OpenCV/ – webcam and image processing demos using OpenCV.
  • 6_Time_Series/ – simple time series analysis examples using pandas and statsmodels.
  • 7_Reinforcement_Learning/ – short Stable Baselines3 examples using Gym.
  • 8_Applications/ – fun demos using Mediapipe, YOLO, Segment Anything and more.

Some of my cool projects to check out

  • Implementing a Neural Network from Scratch in C++ and CUDA Link
  • Implementing Q-Learning to solve a maze from scratch in CUDA Link
  • Introductory Reinforcement Learning Assignments Link
  • Implementing a GAN for Video Prediction Link
  • Deepfake Detection using CNNs Link
  • ML for Galaxy Image Classification Link
  • Reinforcement Learning for Mobile Robot Manipulation Link
  • Physics-Informed Deep Learning for Geological Waveform Inversion Link
  • GPT + Stable Diffusion for Visual-Textual Storytelling Link
  • Semantic Segmentation for Laser Line Detection Link
  • Training a conditional GAN and VAE for generating X-Ray images Link
  • Training Transformer models for music generation Link

About

Hands-on ML tutorials in Python for the ECE Summer Internship Prep Program (SIPP) 2025

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published