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A Gentle Introduction to Machine Learning

Course Overview

Getting Started

Installation
Jupyter Notebooks
Colab
GitHub

Crash Course in Python

Overview
Python Essentials
Tutorial 1: Introduction to Python
Tutorial 2: Reading CSV files
Tutorial 3: Brief Introduction to Pandas
Thinking in Python: Key Concepts and Pitfalls
Classes

First Steps in Machine Learning

A Brief Introduction to Numpy
Tutorial 4
Introduction to Linear Classification
Finding a Decision Boundary
Tutorial 5: Linear Classifiers
Gradient Descent

Classification

Beyond Linear Classification
Loss Functions for Binary Classification
Example: Classifying Movie Reviews
Example: Multiclass Classification Problem
Example: Classifying Digits
Midterm Project

Regression

Regression Problems
Example: Predicting House Prices

Image Classification

Convnets - Convolutional Neural Networks
Example: Classifying Images - Dogs vs. Cats
Using Pretrained Models
Tutorial 6: CIFAR-10 CNN Assignment

Topics in Machine Learning

Overfitting
GPU vs. CPU

Natural Language Processing

Encoding Text
Recurrent Neural Networks (RNNs)
Encoding Text
Encoding Text - Using Predefined Word Embeddings
Tutorial 7: Part-of-speech tagging with RNNs

Introduction to Transformers

A First Look at Self-Attention
Mini GPT
Fine-Tuning: Pre-Processing the Data
Fine-Tuning GPT

Final Project

Final Project: Independent Model Development

Repository
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By Eric Pacuit

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