Instructors
Metehan Seyran
Computer Engineering #4 @I.T.U
Prerequisities
- Basic knowledge about Python programming language.
- Basic knowledge about Calculus and Linear Algebra.
Goal
- Make attendees familiar to basic Machine Learning Topics such as Classification and Regression
- Make attendees familiar with concepts of Neural Networks
- Introduce basics of computational libraries such as PyTorch and NumPy
Syllabus
| #Date | #Topic | #Description |
|---|---|---|
| 09.11.2020 | Basic Machine Learning Pipeline | Basic pipeline for a general Machine Learning project |
| 16.11.2020 | Optimization algorithms for ML | Widely used optimization algorithms and their implementations |
| 23.11.2020 | Linear Regression | Introduction of Linear Regression and implementation using PyTorch |
| 30.11.2020 | NonLinear Regression and Classification | Introduction of Classification algorithms and implementation using PyTorch |
| 7.12.2020 | Neural Networks 1 | Basic introduction of Neural Networks and implementations 1 |
| 14.12.2020 | Neural Networks 2 | Neural Network implementation 2 |
Lessons will be around 1:30 - 2 hours (May Change)
(Lectures will be held online using Zoom)
Important Links
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Suggested Readings
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Project
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