Week 5: Introduction to Deep Learning in Python

An introduction to deep learning in Python by Dr. Yi-Xin Liu at Fudan University (lyx@fudan.edu.cn).

This is a part of the course: Road to Scientific Research: Powerful Computer Applications (XDSY118019.01).

Lecture date: 2024.10.10

Introduction to Deep Learning

Fundamentals of Deep Learning

Fundamentals of Deep Learning

Fundamentals of Deep Learning

Fundamentals of Deep Learning

Deep Learning Experiments

Do the following experiments in A neural network playgound (http://playground.tensorflow.org/):

  • Choose Gaussian data, use linear activation function to train.
  • Choose Circle data, use linear activation function to train. Does it succeed? How to obtain a successful training?
  • (Optional) Choose Spiral data, find a successful classification neural network model.

Deep Learning with Pytorch

Why PyTorch?

PyTorch is currently the most popular deep learning framework not only in Python but all programming languages.

  • See the overall trend for PyTorch and other competitors (TensorFlow, JAX, MxNet, Caffe2, MindSpore, etc.) here.
  • Watch the video for the current state of machine learning frameworks here.

Introduction to PyTorch

Additional Resources for PyTorch

A Simple Walkthrough

Go to 03_python_deep_learning.ipynb.

More Resources for Machine Learning

Why Biological Neurons Are Deep Neural Networks (Youtube Video)

General Machine Learning

LLM