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 (KNN), 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
Duration
None8 weeks