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Machine Learning Basics
The chapter focuses on the construction of a machine learning model aimed at predicting student performance based on various parameters. Key components include data loading, exploration, preprocessing, model building using logistic regression, and model evaluation with appropriate metrics. It culminates in visualizing results and even predicting outcomes for new data.
9 Chapters
25 hr
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Course Chapters
Chapter 1
Chapter 1: What is Machine Learning?
Chapter 2
Chapter 2: Types of Machine Learning
Chapter 3
Chapter 3: Understanding NumPy for Machine Learning
Chapter 4
Chapter 4: Understanding Pandas for Machine Learning
Chapter 5
Chapter 5: Data Preprocessing for Machine Learning
Chapter 6
Chapter 6: Supervised Learning – Linear Regression
Chapter 7
Chapter 7: Supervised Learning – Logistic Regression
Chapter 8
Chapter 8: Model Evaluation Metrics
Chapter 9