The second semester of 2021 (ML)
Understand how NN works while implementing Perceptron Python class directly.
It is possible to understand and explain the data preparation, development, learning, verification, and visualization process of the machine learning model.
Implemented using the pytorch mlp structure to understand and can be modified.
Fashinon dimneoning, develop homegrown solutions to problems - mnist hyper tuning parameters can do it and understand the learning process.
A classifier for classifying linearly classifiable data may be learned using the SVM model.
A model learning and verification process may be implemented using Scikit-Learn.
It can be understood while directly implementing the K-Means model.