AI workshops to introduce the student to AI with exercises in notebooks.
You will need to install Jupyter Notebook. We recommend you also use Anaconda to avoid any dependencies issue.
In each directory, you will find the exercises, a README explaining the purpose of the workshop and the slides used during the workshop.
Basics of python and usage of Jupyter Notebook. You will:
- Learn to use iPython notebooks
- Learn Python Syntax
- Solve complex algorithm exercises
- Master the different programming paradigms of Python
Basics of Data Science and introduce Pandas. You will:
- learn to use Pandas
- analyze huge datasets
- clean datasets
- visualize data analyses
Usage of PyTorch. You will:
- create a model
- solve fashion_mnist
Usage of Tensorflow. You will:
- create a Sequential model
- use Dense layers
- predict house pricing
- classify fashion_mnist
- classify mnist
Discover the effect and usage of convolution. You will:
- understand the point to use convolutional neural network
- use Conv2D
- use Maxpooling2D
- Create a Gradio interface
- Share your app on the Gradio platform
Basics of Reinforcement Learning. You will:
- use Gym environment
- use Q learning
- solve Frozen Lake
Advanced Reinforcement Learning. You will:
- use Gym environment
- use Deep Q Networks
- solve Lunar Lander
Discover one of the most popular supervised learning methods for classification problems. You will:
- Use Scikit-learn
- Create a Decision Tree
- Create a Decision Tree Forest
Use different machine learning techniques to predict house prices. You will:
- Use Scikit-learn
- Create neural networks with PyTorch
- Evaluate your algorithms
Feel free to ask us any questions.
- Bases Python:
- Data Analysis & Data Visualization:
- Bases IA:
- Hidden Layers:
- Données non linéaires:
- Tensorflow:
- Convolution:
- Value Fonction:
- Q-Learning:
- Decision Tree:
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