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Build a Machine Learning Model

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Overview

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Learn to build machine learning models with Python. Includes **Python 3**, **PyTorch**, **scikit-learn**, **matplotlib**, **pandas**, **Jupyter Notebook**, and more.

Syllabus

  • Introduction to Machine Learning
    • Welcome to the world of machine learning! You will learn some of the fundamental concepts behind machine learning.
  • Supervised Learning: Regression
    • Use linear regression or multiple linear regression to fit a line to data. Using this line, you can make predictions about future data.
  • Regression Cumulative Project
    • Practice your regression skills on a real-world dataset provided by Yelp!
  • Supervised Learning: Introduction to Classification
    • Learn to classify data using some of the most famous supervised machine learning models.
  • Supervised Learning: Advanced Classification
    • Learn some of the more complicated supervised machine learning models.
  • Supervised Machine Learning Cumulative Project
    • In this cumulative project, use your understanding of a variety of supervised machine learning models to analyze social media data.
  • Unsupervised Learning
    • Learn how unsupervised machine learning models work by implementing the K-Means clustering algorithm.
  • Unsupervised Machine Learning Cumulative Project
    • Create a project on your own computer that demonstrates your understanding of unsupervised machine learning!
  • Intro to Neural Networks
    • Learn the basics of Neural Networks in PyTorch.
  • Machine Learning Capstone Project
    • Use a dataset from OkCupid and the machine learning skills you have learned to try to find true love!

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