
Abstract
This workshop, "Introduction to Machine Learning", is designed to provide participants with a foundational understanding of machine learning concepts and basic methods. The workshop will cover topics such as supervised and unsupervised learning, model training and evaluation, loss functions, optimization, density estimation, and neural networks. By the end of the workshop, attendees will be equipped with the knowledge and basic understanding of machine learning, preparing them to participate in academic seminars.
Modules
Module 1General Concepts | 29 Bahman (Hosein Hasani)Feb 18, 2024, 2:30 PM – 4:00 PM
Module 1General Concepts | 29 Bahman (Hosein Hasani)Feb 18, 2024, 2:30 PM – 4:00 PM
- Concept of Learning
- Supervised Learning
- Classification
- Regression
- Unsupervised Learning
- Clustering
- Dimensionality Reduction
- Concept of Optimization
- Generalization and Over-fitting
- Model Selection and Validation
Module 2Learning | 30 Bahman (Hosein Hasani)Feb 19, 2024, 2:30 PM – 4:00 PM
Module 2Learning | 30 Bahman (Hosein Hasani)Feb 19, 2024, 2:30 PM – 4:00 PM
- Maximum Likelihood Estimation
- Optimization
- Loss functions
- Classification
- Regression
- Regularization
- Loss functions
Module 3Neural Networks | 1 Esfand (Hosein Hasani)Feb 20, 2024, 2:30 PM – 4:00 PM
Module 3Neural Networks | 1 Esfand (Hosein Hasani)Feb 20, 2024, 2:30 PM – 4:00 PM
- Biological Backgrounds
- Multilayer Perceptron
- Optimization
- Gradient Descent
- Error Backpropagation
- Introduction to More Advanced Architectures
- Convolutional Neural Networks
- Recurrent Neural Networks
- Transformers
About the presenter

