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Chore(DPxAI): Fix format

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Oumaima Fisaoui 2024-09-05 09:30:28 +01:00
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subjects/ai/emotions-detector/README.md
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@ -9,8 +9,8 @@ The study of computer vision could make possible such tasks as 3D reconstruction
For this project we will focus on two tasks:
- emotion classification
- face tracking
- Emotion classification
- Face tracking
With the computing power exponentially increasing the computer vision field has been developing exponentially. This is a key element because the computer power allows using more easily a type of neural networks very powerful on images:
@ -38,7 +38,8 @@ The two steps are detailed below.
I suggest to focus on Week 1 and 2 and to spend less time on Week 3 and 4. Don't worry the time scoping of such MOOCs are conservative. You can attend the lessons for free!
- Participate in [this challenge](https://www.kaggle.com/c/digit-recognizer/code). The MNIST dataset is a reference in computer vision. Researchers use it as a benchmark to compare their models.
Start first with a logistic regression to understand how to handle images in Python. And then train your first CNN on this data set.
- Start first with a logistic regression to understand how to handle images in Python. And then train your first CNN on this data set.
### Face emotions classification