An overview course into supervised machine learning techniques, focusing particularly on linear and logistic regression. By working with real-world datasets, you will implement both models to predict outputs and analyze the most predictive features.
Overview
Syllabus
- Lesson 1: Diving into the Wine Quality Dataset: An In-depth Overview
- Lesson 2: Mastering Gradient Descent: Your Guide to Optimizing Machine Learning Models
- Lesson 3: Mastering Linear Regression: From Theories to Predictions
- Lesson 4: Unveiling Logistic Regression: Internals, Design, and Hands-On Implementation with Wine Quality Prediction
- Lesson 5: Assessing Model Accuracy: Comprehensive Evaluation Metrics and Techniques in Machine Learning
- Lesson 6: Unveiling Predictive Features: A Close Look at Wine Quality with Correlation Analysis
- Lesson 7: Unraveling Model Improvement and Fine-Tuning in Machine Learning