Mastering Machine Learning: From Basics to Advanced

Mastering Machine Learning: From Basics to Advanced

Learning Objectives

Understand the fundamentals of machine learning and its various algorithms, including data preprocessing, regression, overfitting, decision trees, and unsupervised learning.

What do you already know about machine learning?

Introduction to Machine Learning

Definition of machine learning, its importance, and real-world applications. Types of machine learning - supervised, unsupervised, and reinforcement learning.

Data Preprocessing Methods

Exploring data cleaning, normalization, encoding categorical data, handling missing values, and splitting the data into training and testing sets.

Regression Algorithms

Understanding linear, multiple, and polynomial regression algorithms, and their applications in predicting continuous outcomes.

Splitting Methods

Explaining the importance of splitting data into training and testing sets for model evaluation and validation.

Overfitting and Underfitting Models

Defining overfitting and underfitting, and their effects on model performance. Strategies to address overfitting and underfitting.

Decision Tree and Naive Bayes

Understanding decision tree for classification and Naive Bayes for probability estimation based on Bayes' Theorem.

KNN and Logistic Regression

Exploring K-nearest neighbors algorithm for classification and regression, and logistic regression for binary classification.

Evaluation Metrics and Unsupervised Learning

Introduction to evaluation metrics for assessing model performance and understanding K-means clustering for unsupervised learning.

Write down 3 things you learned in this lesson.

Have students enter three things they learned in this lesson. With this they can indicate their own learning efficiency of this lesson.

Write down 2 things you want to know more about.

Here, students enter two things they would like to know more about. This not only increases involvement, but also gives them more ownership.

Ask 1 question about something you haven't quite understood yet.

The students indicate here (in question form) with which part of the material they still have difficulty. For the teacher, this not only provides insight into the extent to which the students understand/master the material, but also a good starting point for the next lesson.