How to model using Machine Learning techniques?
Machine Learning offers a wide range of powerful prediction tools, such as neural networks or decision trees. This course aims at providing the methodological bases to take advantage of the different types of most commonly used models from diverse data.
- Learn how to prepare a set of data.
- Learn, understand and use the different families of predictive models.
- Learn how to evaluate the performance of a predictive model.
- Knowledge of mathematics and probability.
- Knowledge of Python recommended.
AUDIENCE
- R&D Engineer
- Design Office Engineer
- Operational Safety Engineer.
- June 3-4, 2021
- December 2-3, 2021
PLACE
18/20 Boulevard Reuilly, 75012, Paris ; Métro Dugommier
MANAGER
Fabien Taghon
Program
Introduction to data analysis with python
Reading of a dataset
Cleanup and preparation of a dataset
Regression and classification models
Introduction to the most common models
- Lasso and Ridge Linear Regressions
- Logistic regression
- K nearest neighbors algorithm
- Decision trees
- Neural networks
Practice with Python
catalogue_2021_incertitudeApplication form
Register or ask for further information. Personalised training courses can also be provided. The location of the training is subject to change. Training courses can be held at a distance. In this case, the training can be delivered in several short sessions (e.g. 2 hours) via videoconference software, spread over several days, in agreement with the trainer and the participants.