Course: CSC 296S Deep Learning (Spring 2026)
Institution: California State University, Sacramento
Instructor: Dr. Haiquan Chen

Personal learning repository for the Deep Learning course. Contains lab work, notes, and practice exercises.

• Python 3.10+
• pip

# Clone the repo
git clone https://github.com/YOUR_USERNAME/deep-learning-csc296s.git
cd deep-learning-csc296s

# Create virtual environment
python3 -m venv dl-env

# Activate it
source dl-env/bin/activate

# Install dependencies
pip install -r requirements.txt

# Launch Jupyter Lab
jupyter lab

deep-learning-csc296s/
│
├── README.md                 # You are here
├── requirements.txt          # Python dependencies
├── .gitignore
│
├── labs/
│   └── lab-0/
│       ├── arraysPractice.ipynb      # NumPy practice notebook
│       └── LAB-0 NOTES.md            # Lab 0 notes
│
└── lecture notes/
    ├── Deep Learning 01.md           # Lecture 1 notes
    ├── Deep Learning 02.md           # Lecture 2 notes
    ├── Deep Learning 03.md           # Lecture 3 notes
    ├── Deep Learning 04.md           # Lecture 4 notes
    └── DL-IMAGES/                    # Lecture diagram assets

Legend: ✅ Complete | 🟡 In Progress | ⬜ Not Started

• Creating arrays (np.array, np.zeros, np.ones, np.arange, np.linspace)
• Array properties (.shape, .dtype, .size)
• Indexing and slicing
• Vectorized operations
• Matrix multiplication (@, np.dot)
• Aggregations with axis parameter
• Reshaping arrays

• Coming soon...

• Python 3.13
• NumPy - Array operations
• Pandas - Data manipulation
• Matplotlib - Visualization
• TensorFlow - Deep learning framework
• PyTorch - Deep learning framework
• Jupyter Lab - Interactive notebooks

• NumPy Docs
• TensorFlow Docs
• PyTorch Docs
• Matplotlib Docs

• NumPy Cheatsheet

Python: 3.13
NumPy: latest
TensorFlow: latest
PyTorch: latest

To check versions:

import numpy as np
import tensorflow as tf
import torch

print(f"NumPy: {np.__version__}")
print(f"TensorFlow: {tf.__version__}")
print(f"PyTorch: {torch.__version__}")

• All labs completed in Jupyter Lab
• Notes written in Obsidian, exported to Markdown
• Virtual environment (dl-env/) not included in repo - use requirements.txt to recreate

• Dr. Haiquan Chen for the course material
• California State University, Sacramento

Last updated: February 2026