I've been waiting for this course to become available for a while now, so I'm happy that it's finally here! I thought I'd share just in case there are others on Steemit who are studying machine learning.
The course is called "Convolutional Neural Networks" and it's offered free through Coursera. You'll find it useful and relevant if you want to learn how machine learning is used to perform computer vision tasks (classification, segmentation, object recognition). Convolutional neural networks (CNNs) and their variants achieve state of the art performance for image processing tasks, as recognized by various Silicon Valley projects, university research, and Kaggle competitions.
The course fee is only required if you want a certification upon completion. Here is the sign-up link: https://www.coursera.org/specializations/deep-learning.
If you are new to machine learning, you might want to consider an introduction to the subject first, such as "Neural Networks and Deep Learning," available at https://www.coursera.org/learn/neural-networks-deep-learning. The math isn't terribly difficult. You'll be fine as long as you understand the basics of summations, matrix multiplication, partial differentiation from multivariate calculus, and gradients. If not, you could learn that material from videos available from www.khanacademy.org. To tackle the programming assignments, you should already be comfortable writing code in Python.
Incidentally, these courses are from a five part specialization. If you would like to read about the entire specialization, please see https://www.coursera.org/specializations/deep-learning.
Andrew Ng has an easy going teaching style and is very popular among students. His "Machine Learning" course (also available through Coursera) has enjoyed a huge following. And his professional experience helps him add practical advice throughout the lectures, drawing from work as an adjunct professor at Stanford, former head of Baidu AI Group/Google Brain, and director at drive.ai (self-driving car company).
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