Get In Touch with ISAE Supaero
Address
10, avenue Édouard-Belin
BP 54032 - 31055 Toulouse CEDEX 4
Phone
+33 (0)5 61 33 80 80
Quick Links
© AIBT-HandsOn. All Rights Reserved. Designed by HTML Codex
Classes
This optional class serves as a comprehensive review of Object-Oriented Programming (OOP) concepts in Python.
In this first class, we will reintroduce the taxonomy, cover the format of the class and introduce some tools.
This class focuses on the Data Exploration phase of a Machine Learning project. You will see through practical applications an end to end exploratory phase. You will also improve skills with common ML tools.
It is easy to misunderstand AI and ML while the truth is that ML is a part of all AI techniques. Therefore, this lesson aims to give you example of AI methods that are not related to ML but still very useful and interesting!
This class will cover some of the most famous Machine Learning algorithms. You will have the opportunity to learn and use them on a medical dataset! Even though you will use scikit-learn prepare yourself to code from scratch!
Time series data are all around us! Learning to analyze them properly unlocks valuable insights and helps make accurate predictions in industry and research. In this class, you will learn how to explore and analyze time series data, unlock insights, and make informed predictions.
In the previous classes you got a flavor of Machine Learning for Supervised Learning. Here, we will introduce you to Unsupervised Learning and cover different Use Cases through notebooks and famous datasets!
In this class you will finally get in touch with Artificial Neural Networks and their wide range of applications! Namely, you will get a hand on the famous Deep Learning framework: PyTorch. Then, you will train your first Deep Neural Networks. Enjoy!
Reinforcement learning is learning how to map situations to actions so as to maximize a numerical reward signal. The learner is not told which actions to take, but instead must discover which actions yield the most reward by trying them.
Nowadays, AI applications are widening. However, it is still difficult to get guarantees from black-box models such as deep neural networks (DNN). We will try here to cover two areas that are significant to demystify DNN: Robustness and Explainability!
10, avenue Édouard-Belin
BP 54032 - 31055 Toulouse CEDEX 4
+33 (0)5 61 33 80 80
© AIBT-HandsOn. All Rights Reserved. Designed by HTML Codex