Learn to implement 10 Machine Learning algorithms from scratch with just Python and NumPy. A library hides the implementation details and if you're really looking to understand what goes behind the covers and understand how things work, this course has you covered. This is a course by AssemblyAI where you don't rely on libraries like Pytorch or Tensorflow to implement the Machine learning algorithms but you implement them yourself from scratch with nothing but Python and NumPy. You need basic Python, object oriented programming and the basics of NumPy to follow along as it's a practical course with a lot of code. However scary math formulas are referred too.If you do have experience with Andrew Ng's deep learning courses which require high school level math and teach the basics of the notations you should not face any issues even on that part.

Early Bird Rego closes 16th February 2018. Course Overview: This course will teach you how popular machine learning algorithms work by stepping you through a series of workshops to create genetic algorithms and artificial neural networks from scratch without the need for any special plugins. Once you've learnt all the threshold concepts you'll move onto installing the Unity ML-Agents system and explore the use of Tensorflow and reinforcement learning with the Q-learning algorithm.