# Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow

**Repository Path**: jetaimy/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow

## Basic Information

- **Project Name**: Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow
- **Description**: Part I: Notebooks & Code "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems"  by Aurelien Geron
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 2
- **Created**: 2023-03-01
- **Last Updated**: 2023-03-01

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

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# Hands-on ML with Scikit-Learn, Keras & TF by Aurelien Geron




<div style="text-align:center"><img style="width:100%" src="static/imgs/book_cover.png"></div>

- This Books assumes you know close to nothing about machine learning.
- We will be using production-ready Python frameworks
    - Scikit-Learn
    - Keras
    - TensorFlow
- This book favors a hands-on approach through a series of working examples and just a little bit of theory.
- Prerequesites
    - Some Python programming experience
    - Familiarity with NumPy, Pandas, and Matplotlib
    - A reasonable understanding of college-level math (calculus, probability, Linear Algebra, and statistics)
- The first part of the book is mostly based on Scikit-Learn, while the 2nd part is using Keras/TensorFlow.

## Roadmap

### 1. The Fundamentals of Machine Learning
- [The Machine Learning Landscape](https://akramz.github.io/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/01.ML_Landscape)
- [End-to-End Machine Learning Project](https://akramz.github.io/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/02.End-to-End-ML-Project)
- [Classification](https://akramz.github.io/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/03.Classification)
- [Training Models](https://akramz.github.io/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/04.Training-Models)
- [Support Vector Machines](https://akramz.github.io/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/05.SVMs)
- [Decision Trees](https://akramz.github.io/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/06.Decision_Trees)
- [Ensemble Learning and Random Forests](https://akramz.github.io/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/07.Ensembles_RFs)
- [Dimensionality Reduction](https://akramz.github.io/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/08.Dim_Reduction)
- [Unsupervised Learning Techniques](https://akramz.github.io/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/09.Unsupervised_learning)
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