This repository contains course materials and three lab projects for the "Deep Learning I" - DS-télécom-6 course followed at Télécom Paris for the Master 2 Data Science during the academic year 2023-2024.
Deep Learning (machine learning based on deep artificial neural networks) has become extremely popular over the last years due to the very good results it allows for tasks such as regression, classification or genera- tion. The objective of this course is to provide a theoretical understanding and a practical usage of the three main types of networks (Multi-Layer- Perceptron,Recurrent-Neural-Network and Convolutional Neural Network). The content of this course rangesfrom the perceptron to the generation of adversarial images. Each theoretical lecture is followed by a practical lab on the corresponding content where student learn to implement these networks using the currently three popular frameworks: pytorch, tensorflow and keras.
The repository includes three lab projects, each focusing on a different architecture of deep learning:
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Lab 1: MLP - Multi Layer Perceptron
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Lab 2: RNN - Recurrent Neural Network
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Lab 3: CNN - Convolutional Neural Network