Covers: theory of Deep Learning

- Why does deep learning work?
- Why PyTorch?
- Why linear algebra?

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

Fail to play? Open the link directly: https://youtu.be/BDB_rekFEl4

Amir Hajian

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Contributors

- Objectives
- 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.

Resources5/5

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

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