Machine-Learning-by-Python-course-projects

presented by professor naser razavi

University of Tabriz, Fall 2024

Linear classification
Implementing Loss functions (Softmax loss and SVM loss)
Implementing gradient descent, Backpropagation and Artifitial Neural Networks (MLP)
Advanced topics including dropout, batch normalization, weight initialization and other optimization methods(Adam, RMSProp)
Inroduction to Deep Learning and implementing a Convolutional Neural Network (CNN) for image classification.

Name		Name	Last commit message	Last commit date
Latest commit History 13 Commits
.vscode		.vscode
Machine-learning-course-projects-University-of-Tabriz		Machine-learning-course-projects-University-of-Tabriz
__pycache__		__pycache__
classification_function_folder		classification_function_folder
datasets/cifar-10-batches-py		datasets/cifar-10-batches-py
fig_code_folder		fig_code_folder
figs_folder		figs_folder
figure square function.png		figure square function.png
.gitignore		.gitignore
1_numpy & matplotlib packge.ipynb		1_numpy & matplotlib packge.ipynb
2_scikit learn package.ipynb		2_scikit learn package.ipynb
3_supervised learning.ipynb		3_supervised learning.ipynb
4_unsupervised learning.ipynb		4_unsupervised learning.ipynb
5_linear classification.ipynb		5_linear classification.ipynb
README.md		README.md
my array in text format.data		my array in text format.data
my array.npy		my array.npy

Provide feedback