Udemy Data Science: Machine Learning algorithms in Matlab Udemy
Price: USD 35

    Course details

    In recent years, we've seen a resurgence in AI, or artificial intelligence, and machine learning.

    Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts.

    Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning.

    Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.

    Google famously announced that they are now "machine learning first", and companies like NVIDIA and Amazon have followed suit, and this is what's going to drive innovation in the coming years.

    Machine learning is embedded into all sorts of different products, and it's used in many industries, like finance, online advertising, medicine, and robotics.

    It is a widely applicable tool that will benefit you no matter what industry you're in, and it will also open up a ton of career opportunities once you get good.

    Machine learning also raises some philosophical questions. Are we building a machine that can think? What does it mean to be conscious? Will computers one day take over the world?

    This course will go from basics to advance. Step by step approach will make its easy to understand Machine Learning.

    TIPS (for getting through the course):

    • Watch it at 2x.
    • Take handwritten notes. This will drastically increase your ability to retain the information.
    • Write down the equations. If you don't, I guarantee it will just look like gibberish.
    • Ask lots of questions on the discussion board. The more the better!
    • Realize that most exercises will take you days or weeks to complete.
    • Write code yourself, don't just sit there and look at my code.


    Updated on 18 February, 2018
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