Machine Learning in MATLAB
The Following algorithms are tentatively planned to be discussed and detailed tutorials/examples will be worked out in the class.
- Parametric and Non-parametric Machine Learning Algorithms
- The Supervised, Unsupervised and semi-supervised Learning
- The Bias-Variance Trade-off
- Overfitting and Underfitting
- Gradient Descent.
- Linear Regression.
- Logistic Regression.
- Linear Discriminant Analysis.
- Classification and Regression Trees.
- Naive Bayes.
- K-Nearest Neighbors.
- Learning Vector Quantization.
- Support Vector Machines.
- Bagged Decision Trees and Random Forest.
- Boosting and AdaBoost.
|Dates||11th - 12th Aug, 18th- 19th Aug, 25th - 26th Aug 2018|
|Saturday Time:||2:30 PM - 5:30 PM|
|Sunday Time:||11:30 AM - 1:30 PM + TUT: 9:00 - 11:00 AM|