If you’re here, you already know the truth: Machine Learning is the future of everything.
In the coming years, there won’t be a single industry in the world that hasn’t been affected by machine learning. As a transforming force, you can choose to understand it now or lose yourself in a wave of incredible change.
You are likely to use apps based on machine learning techniques several times a day. So why stay in the dark longer?
There are already many machine learning courses. I created this course as the best introduction to the topic. No topic remains unaffected and we don’t leave any area in the dark. By completing this course, you are ready to enter and understand every sub-discipline in the world of machine learning.
A single line of Python can contain many functions. This is great when you understand the language and subject, but not so much when trying to learn a whole new subject.
Does this course focus on algorithms, or math, or Tensorflow, or what?
Let’s be honest: The vast majority of ML courses available online dance around confusing topics. They encourage you to use precompiled algorithms and functions that do all the heavy lifting for you.
Although this can lead to quick successes, in the end, it will hinder your ability to understand LD. You can only understand how to apply ML techniques if you understand the underlying algorithms.
This is the goal of this course: I want you to understand the exact math and programming techniques used in the most common Machine Learning algorithms.
Once you have this knowledge, you can easily choose new algorithms on the go and create much more interesting projects and applications than other engineers who only understand how data is delivered to a magical library.
Don’t have a background in math? That’s OK!
I take special care to make sure that no lecture gets too far into ‘mathy’ topics without giving a proper introduction to what is going on.
A short list of what you will learn:
- Advanced memory profiling to enhance the performance of your algorithms
- Build apps powered by the powerful Tensorflow JS library
- Develop programs that work either in the browser or with Node JS
- Write clean, easy to understand ML code, no one-name variables or confusing functions
- Pick up the basics of Linear Algebra so you can dramatically speed up your code with matrix-based operations. (Don’t worry, I’ll make the math easy!)
- Comprehend how to twist common algorithms to fit your unique use cases
- Plot the results of your analysis using a custom-build graphing library
- Data loading techniques, both in the browser and Node JS environments
Benefits of this course
Who this course is for
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