Holberton ML Handbook
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Holberton ML Handbook
GitHub
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Tools
Tools
Overview
Zero day
Git & GitHub
Jupyter notebook setup
VS Code setup
Python Warm Up
Math
Math
Overview
Linear algebra
NumPy
Calculus
Probability & statistics
Data
Data
Overview
Data Foundations
Pandas essentials
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Data Processing
Data collection
SQL databases
NoSQL (MongoDB)
NoSQL (MongoDB install)
Core ML
Core ML
Overview
Introduction
ML Categories
ML Lifecycle
Regression
Classification
Classification Advanced
Unsupervised Learning Overview
Unsupervised Learning Clustering
Unsupervised Learning Dimensionality Reduction
Deep Learning Fundamentals
Deep Learning Fundamentals
Overview
Classification Using Neural Networks
Optimization
Error Analysis
Regularization
Deep Learning Architectures
Deep Learning Architectures
Overview
Convolutions and Pooling
Convolutional Neural Networks
Data Augmentation
Deep Convolutional Architectures
Transfer Learning
Object Detection
Sequential & NLP
Sequential & NLP
Overview
RNNs and LSTMs
Time Series Forecasting
Understanding NLP
Word Embeddings
Evaluation Metrics for NLP
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Generative AI & LLMs
Generative AI & LLMs
Overview
Generative AI Fundamentals
Large Language Models (LLMs)
Open Source vs Proprietary Models
Tailoring AI Chatbots
Running Models with WebGPU
OpenAI and Hugging Face
Final Portfolio
Final Portfolio
Overview
Project Requirements
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