Deep Learning: Visual Exploration

Deep neural networks visually explained in plain english & without complex math

Created by: Vladimir Grankin
Software Engineer

What Will I Learn?

• Deep understanding of what is deep neural network and how exactly it works under the hood to come up with good predictions in real life problems (we will only explore feedforward deep neural network for binary classification in our course, but we discuss fundamentals so knowledge you will get is also applicable to all the other network types!)
• Understand what is decision boundary and how exactly it is formed by a deep neural network
• Understand why deep neural networks are also knows as function approximators

Requirements

• Basic python skills - optional, you will need python if you want to run the code we discuss yourself
• Familiarity with neural networks at high level (terms like bias, weight and activation function should be familiar)
• Jupyter notebook (optional and is needed if you want to run all the demos yourself)

Target audience

• People who like to understand things visually
• People who like simple explanations against mathematical and formal ones
• If you are just starting with Deep Learning or AI in general, this course if for you!
• If you think what is happening under the hood of deep neural network is a mystery, this course is for you! - we totally demystify DNNs in this course!
• If you wonder how exactly weights, biases and activation functions are working, this course is for you!
• Experienced deep learning users who want to improve their understanding on how exactly Deep Neural network is able to come up with complex function approximations