Machine Learning Week 1 Overview

Welcome to the first week of our Machine Learning course! This week, we'll be covering the basics of machine learning and setting the foundation for the rest of the course.

Learning Objectives

  • Understand the basics of machine learning.
  • Learn about different types of machine learning algorithms.
  • Gain hands-on experience with machine learning tools and libraries.

Course Content

  • Introduction to Machine Learning

    • What is machine learning?
    • Types of machine learning: Supervised, Unsupervised, and Reinforcement Learning.
    • History of machine learning.

  • Machine Learning Algorithms

    • Linear Regression
    • Logistic Regression
    • Decision Trees
    • Support Vector Machines
    • K-Nearest Neighbors

  • Hands-on Practice

    • Using Python for machine learning
    • Introduction to popular machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch)

Additional Resources

For further reading and practice, check out our Python for Machine Learning course.

Week 1 Assignment

Complete the following assignment to solidify your understanding of the material covered this week:

  1. Implement a simple linear regression model using scikit-learn.
  2. Analyze the results and interpret the output.

Good luck, and happy learning! 🎓

Machine Learning Intro