Maths for Machine Learning BootCamp 2024

This repo will contain all the relevant materials for the WiMLDS Accra Maiden Maths Bootcamp with AIMS Ghana.

Introduction

Welcome to The Mathematics for Machine Learning BootCamp, a dynamic collaboration between Accra Women in Machine Learning & Data Science (WiMLDS) and the African Institute of Mathematical Sciences (AIMS). Our focus is on current university students, undergraduates or graduates aspiring to deepen their grasp of mathematics in the context of machine learning, this program promises an enriching learning experience.

The BootCamp is structured to include two-hour session for 4 consecutive Sundays (i.e 2 hours every Sunday) focused on essential Machine Learning topics crucial for foundational understanding. To enhance learning, the program integrates practical applications, providing students with an opportunity to explore real-world implementations of the curriculum. Furthermore, the course includes assignments to evaluate students' comprehension and incorporates a capstone project, which serves as a valuable addition to their career portfolios.

Preliminary Materials

• Introduction To Python
• Introduction To Jupyter Notebooks (Specifically, Google Colab)

Curriculum

1. Introduction to Linear Algebra

   • Vectors & vector spaces
   • Matrix operations
   • Eigenvalues & Eigenvectors
   • Use Case in PCA

2. Introduction to Statistics and Probability Theory

   • Measures of central tendencies
   • Discrete & Continuous Probability Distributions
   • Inferential Statistics(Hypothesis testing)
   • Use cases in descriptive statistics and interpretations of different distribution types
   • Overview of Exploratory Data Analysis (EDA)

3. Introduction to Optimization

   • Cost functions
   • Gradient Descent
   • Use case of gradient descent in optimizing a function

4. Introduction to Machine Learning

   • Concept of Machine Learning and Types
   • Machine Learning Workflow
   • Linear Regression Models
   • Logistic Regression Models

Bootcamp Materials

Week	Slides	Code	Recording
Week 1	Introduction to Linear Algebra	Colab notebook for week 1	Recording Link
Week 2	Introduction to Probability Theory	Colab notebook for week 2	Recording Link
Week 3	Introduction to Optimization	Colab notebook for week 3	Recording Link
Week 4	Introduction to Machine Learning	Colab notebook for week 4	Recording Link

Assignment Solutions

• Week 1 | Colab Notebook | PDF
• Week 2 | Colab Notebook | PDF
• Week 3 | Colab Notebook | PDF

Capstone Project

Resources

• Machine Learning Books
  • The hundred-page machine learning book by Burkov, A. (2019).
  • Introduction to machine learning with Python: a guide for data scientists by Müller, A. C., & Guido, S. (2016)
  • Data science from scratch: first principles with python by Grus, J. (2019).
  • Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow by Géron, A. (2022).