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.

Objectives

  • 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.

Prerequisites

  • Knowledge of mathematics and probability.
  • Knowledge of Python recommended.

AUDIENCE

  • R&D Engineer
  • Design Office Engineer
  • Operational Safety Engineer.

Upcoming sessions

  • 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

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Application form

Do not hesitate to register or to ask for more information. Customized training can also be offered. The location of the training is subject to change. Most of our courses can be conducted online. Once you have sent your registration request, one of our trainers will contact you to specify your needs and adapt the training.



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