Machine Learning Exercises

Some example codes I wrote while studying concepts and a few small projects.

Also some snippets of coursework codes I wrote in the optimization and model-based image processing courses (just snippets as the lecturers may still be using the same exercises).

• linear regression in numpy
• logistic regression in numpy
• deep learning 1: feedforward and backpropagation in numpy
• deep learning 2: complete neural network implementation in Theano, TensorFlow
• CNN in Theano and TensorFlow
• expression recognition project using regression and CNN
• computer vision in keras: vgg, class activation map, keras cnn, object detection
• neural style transfer project
• Bayes classifier using scipy and scikit-learn
• single hidden layer autoencoder and deep convolutional Generative Adversarial Networks (dcGANs) in TensorFlow
• image classification TensorFlow sample project
• PPT made for short group discussion: intro_to_deep_learning.pdf

I used the textbook: Deep Learning (Ian Goodfellow, Yoshua Bengio, and Aaron Courville) for more detailed theory.

Machine Learning Workspace on Linux

Working examples and projects focused on image-to-image deep learning. Trained on Ubuntu 18.04.

• Densenet
• keras
• cnn using tensorflow

Specs and Software Versions:

• 12 core Intel i7 8700K
• Nvidia GeForce RTX 2070
• Ubuntu 18.04
• python 3.6
• Tensorflow 1.12
• Keras 2.2.4
• CUDA 10.0
• CUDNN 7.3.1
• OpenCV 3.31