What you'll learn
Learn how a neural network is built from basic building blocks (the neuron)
Learn how Deep Learning works
Code a neural network from scratch in Python and numpy
Describe different types of neural networks and the different types of problems they are used for

Requirements
Basic math (calculus derivatives, matrix arithmetic, probability)
Install Numpy and Python
Don't worry about installing TensorFlow, we will do that in the lectures.
Being familiar with the content of my logistic regression course (cross-entropy cost, gradient descent, neurons, XOR, donut) will give you the proper context for this course

Description
Artificial intelligence is growing exponentially. There is no doubt about that. Self-driving cars are clocking up millions of miles, IBM Watson is diagnosing patients better than armies of doctors and Google Deepmind's AlphaGo beat the World champion at Go - a game where intuition plays a key role. But the further AI advances, the more complex become the problems it needs to solve. And only Deep Learning can solve such complex problems and that's why it's at the heart of Artificial intelligence. Deep learning is increasingly dominating technology and has major implications for society. From self-driving cars to medical diagnoses, from face recognition to deep fakes, and from language translation to music generation, deep learning is spreading like wildfire throughout all areas of modern technology. But deep learning is not only about super-fancy, cutting-edge, highly sophisticated applications. Deep learning is increasingly becoming a standard tool in machine-learning, data science, and statistics. Deep learning is used by small startups for data mining and dimension reduction, by governments for detecting tax evasion, and by scientists for detecting patterns in their research data. Deep learning is now used in most areas of technology, business, and entertainment. And it's becoming more important every year.Learn how Deep Learning works (not just some diagrams and magical black box code)Learn how a neural network is built from basic building blocks (the neuron)Code a neural network from scratch in Python and numpyCode a neural network using Google's TensorFlowDescribe different types of neural networks and the different types of problems they are used forDerive the backpropagation rule from first principles