FSPEC 101 - Machine Learning
Description
ML 101 provides a comprehensive introduction to machine learning, covering key algorithms, data preprocessing techniques, and model optimization.
Students will learn how to implement K-Nearest Neighbors, gradient descent, logistic regression, and multi-class classification while using TensorFlow.js for real-world applications such as image recognition and data analysis.
The course emphasizes hands-on projects, including CSV data handling, feature normalization, and performance optimization.
Prerequisite
None
Duration
8 weeks