Machine Learning Specialization

Deeplearning.ai | Stanford University

Taught by Prof. Andrew Ng on Coursera

• C1 - Supervised Machine Learning - Regression and Classification

  • Introduction to Machine Learning
  • Regression with multiple input variables
  • Classification

• C2 - Advanced Learning Algorithms

  • Neural Networks
  • Neural network training
  • Advice for applying machine learning
  • Decision trees

• C3 - Unsupervised Learning, Recommenders, Reinforcement Learning

  • Unsupervised learning
  • Recommender systems
  • Reinforcement learning

ML examples:

1. Houce price prediction
2. Malignant Tumor Classification
3. Digits Recognition
4. Images Recognition
5. Decision Tree of Classification for Cats
6. Spaceship Landing Simulation

Course Review :

This Course is the best place towards becoming a Machine Learning Engineer. Even if you're an expert, many algorithms are covered in depth such as decision trees which may help in further improvement of skills.

Special thanks to Professor Andrew Ng for structuring and tailoring this Course.

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An insight of what you might be able to accomplish at the end of this specialization :

• Write an unsupervised learning algorithm to Land the Lunar Lander Using Deep Q-Learning

  • The Rover was trained to land correctly on the surface, correctly between the flags as indicators after many unsuccessful attempts in learning how to do it.
  • The final landing after training the agent using appropriate parameters :

lunar_lander.mp4

• Write an algorithm for a Movie Recommender System

  • A movie database is collected based on its genre.
  • A content based filtering and collaborative filtering algorithm is trained and the movie recommender system is implemented.
  • It gives movie recommendentations based on the movie genre.

• And Much More !!

Concluding, this is a course which I would recommend everyone to take. Not just because you learn many new stuffs, but also the assignments are real life examples which are exciting to complete.

Keep Learning :)