Get started with Machine Learning with Python - An introduction with Python programming examples

Overview

Machine Learning With Python

Get started with Machine Learning with Python

An engaging introduction to Machine Learning with Python

TL;DR

  • Download all Jupyter Notebooks from repo (zip-file-download).
  • Unzip download (main.zip) appropriate place.
  • Launch Ananconda and start JuPyter Notebook (Install it from here if needed)
  • Open the first Notebook from download.
  • Start watching the first video lesson (YouTube).

Machine Learning (ML)

Goal of Course

  • Learn the advantages of ML
  • Master a broad variety of ML techniques
  • Solve problems with ML
  • 15 projects with ML covering:
    • k-Nearest-Neighbors Classifier
    • Linear Classifier
    • Support Vector Classification
    • Linear Regression
    • Reinforcement Learning
    • Unsupervised Learning
    • Neural Networks
    • Deep Neural Networks (DNN)
    • Convolutional Neural Networks (CNN)
    • PyTorch classifier
    • Recurrent Neural Networks (RNN)
    • Natural Language Processing
    • Text Categorization
    • Information Retrieval
    • Information Extraction

Course Structure

  • The course puts you on an exciting journey with Machine Learning (ML) using Python.
    • It will start you off with simple ML concepts to understand and build on top of that
    • Taking you from simple classifier problems towards Deep Neural Networks and complex information extractions
  • The course is structured in 15 sessions, where each session is composed of the following elements
    • Lesson introducing new concepts and building on concepts from previous Lessons
    • Project to try out the new concepts
    • YouTube video explaining and demonstrating the concepts
      • A walkthrough of concepts in Lesson with demonstrating coding examples
      • An introduction of the Project
      • A solution of the project

Are You Good Enough?

Worried about whether you have what it takes to complete this course?

  • Do you have the necessary programming skills?
  • Mathematics and statistics?
  • Are you smart enough?

What level of Python is needed?

What about mathematics and statistics?

  • Fortunately, when it comes to the complex math and statistics behind the Machine Learning models, you do not need to understand that part.
  • All you need is to know how they work and can be used.
    • It's like driving a car. You do not have to be a car mechanic to drive it - yes, it helps you understand the basic knowledge of an engine and what the engine does.
    • Using Machine Learning models is like driving a car - you can get from A to B without being a car mechanic.

Still worried?

  • A lot of people consider me a smart guy - well, the truth is, I'm not
    • I just spend the hours learning it - I have no special talent
  • In the end, it all depends on whether you are willing to spend the hours
  • Yes, you can focus your efforts and succeed faster
    • How?
    • Well, structure it with focus and work on it consistently.
    • Structure your learning - many people try to do it all at once and fail - stay focused on one thing and learn well.
    • Yes, structure is the key to your success.

Any questions?

  • I try to answer most questions. Feel free to contact me.
Owner
Learn Python with Rune
Learn Python with Rune
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