https://github.com/younes-charfaoui/machine-learning-beginner-course

This Repository Will hold The code projects 💻, data-sets 📄 and lessons slide 📚 about the MLBC 💡
https://github.com/younes-charfaoui/machine-learning-beginner-course

Last synced: 7 months ago
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This Repository Will hold The code projects 💻, data-sets 📄 and lessons slide 📚 about the MLBC 💡

• Host: GitHub
• URL: https://github.com/younes-charfaoui/machine-learning-beginner-course
• Owner: Younes-Charfaoui
• Created: 2019-01-16T20:01:30.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-01-26T20:17:33.000Z (over 5 years ago)
• Last Synced: 2025-03-17T11:03:01.474Z (7 months ago)
• Language: Jupyter Notebook
• Size: 10.8 MB
• Stars: 23
• Watchers: 5
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Machine Learning Beginner 💻📚👨‍🏫

The code of the projects will be developed, datasets and the slides of the course will be found in this repository, all pull requests, issues or any contributions are welcomed to enhance the program content.

# Introduction 🎉💯🎓

Machine Learning Beginner course (MLBC) is a course devoted to beginners in the domain of machine learning, this course will reveal the idea behind machine learning and its philosophy, the types, techniques, and tools to know as newcomers. We’ll kick off our Python and machine learning journey with the basic, yet important concepts of machine learning. We will start with what machine learning is about, why we need it. We will then discuss typical machine learning tasks and explore several essential techniques of working with data and working with models. It is a great starting point of the subject and we will learn it in a fun way. At the end of this course a final challenge will have a place to practice what we learned.

# Registration 📚✅📌

Please note that the places in this course are limited so hurry up and subscribe by providing your information and follow this [link](https://docs.google.com/forms/d/e/1FAIpQLSdWNNNypECt4ueQ6s8FucsZT3uNCgiMEET0O7QKjNFe0uOZwQ/viewform) to register into the course.

# Place & Time 🕧⏳📅

Every Wednesday on `12:30` in the Classroom Number 11 in the `B` Building Block 

# Outline 👨‍🎓📋📏

    -Introduction.

    -Python Refresher.

    -Data Preprocessing.

    -Supervised Machine Learning.

    -Model Evaluations.

    -Unsupervised Machine Learning.

    -Deep Learning.