Covers: theory of Deep Learning
Estimated time needed to finish: 20 minutes
Questions this item addresses:
  • Why does deep learning work?
  • Why PyTorch?
  • Why linear algebra?
How to use this item?

Watch this video to learn about Linear Algebra: Tensors, Matrices, Vectors & Scalars

Fail to play? Open the link directly:
Author(s) / creator(s) / reference(s)
Amir Hajian
0 comment

Getting Started With Mathematics Of Deep Learning

Total time needed: ~7 hours
This recipe is your starting point to understand why and how deep learning works.
Potential Use Cases
Image processing and computer vision, Natural language processing
Who is This For ?
BEGINNERData Scientists, Machine Learning Engineers
Click on each of the following annotated items to see details.
VIDEO 1. Introduction: Pytorch and Linear Algebra
  • Why does deep learning work?
  • Why PyTorch?
  • Why linear algebra?
20 minutes
RECIPE 2. Foundations of Algebra for Deep Learning
2 hours
RECIPE 3. Extracting Features using Convolution
3 hours
RECIPE 4. Deep Learning Model Training and Optimization
2 hours
VIDEO 5. Short intro of Conv Nets
  • What is the convolution operation?
  • What are the filters inside the CNN?
5 minutes

Concepts Covered

0 comment