Detect Emotions with Convolutional Neural Networks
Channel: The Assembly
Date: 2021-03-27

Convolutional Neural Networks (CNNs) are a special category of deep neural networks particularly suited to the analysis of visual imagery – and commonly applied in facial recognition, image classification, and medical imaging.

In this session, we’ll demonstrate how to use CNNs to detect a person’s mood and emotions based on their facial expressions. We’ll use TensorFlow in Colab to build, train, and test our model & show you how to refine the process for best results.

Prerequisites:
—Basic knowledge of Python and machine learning concepts
—Google Colab (https://colab.research.google.com/)

GitHub Link: https://github.com/The-Assembly/Detect-Emotions-with-Convolutional-Neural-Networks 

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0:00 1. Intro
2:29 2. What is deep learning?
7:26 3. What is TensorFlow?
9:21 4. Import the libraries on Colab
13:05 5. Upload the dataset
17:02 6. Train & validate the dataset
30:13 7. Build the CNN model
39:22 8. Train the model
45:38 9. Evaluate the model
52:59 10. Test the model (output)
54:28 11. Outro

#DataScience #NeuralNetworks #DeepLearning