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WiMLDS-Ghana/MathsBootCamp25

Domain:

education

Record type:

project
Creator:
WiM
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This repository would contain all the 2025 bootcamp materials for WiMLDS. # Maths for Machine Learning BootCamp 2025 This repo will contain all the relevant materials for the WiMLDS Accra 2nd Edition Maths Bootcamp. # Introduction Welcome to The Mathematics for Machine Learning BootCamp, a comprehensive program designed to provide a solid foundation in Mathematics for Machine Learning. 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 | …

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