Introduction to deep learning
Deep learning methods have revolutionized the machine learning field. They have encountered tremendous success in computer vision, audio application or natural language processing. They draw their success, among other things, because they are able to provide automatic feature engineering thanks to their hidden layers. The goal of this course is to gain a first understanding of such models and learn how to train and use them. Transfer learning a standard technique to train models more efficiently will be covered.
9 in stock
October 31, 2023
November 3, 2023
Language(s) of the training
Languages spoken by the coach(es)
M. Cetinsoy Laurent
- Introduction to Deep Learning: Understanding its principles, techniques, and applications.
- Feature Engineering: Understanding how hidden layers in deep learning models provide automatic feature engineering.
- Deep Learning Model Training: Techniques and methods for training deep learning models.
- Transfer Learning: An efficient technique for training models by leveraging pre-trained models.
- Applications : Hands-on exercises in using deep learning models.
- Introduction to the concepts and techniques of deep learning and its applications in various fields.
- Hands-on experience with training and using deep learning models.
- Understanding the concept and practical application of transfer learning.
Upon completion of this course, learners are able to :
- train deep learning model in simple setting
- do image classification with deep learning
- understand the basic theory of deep neural networks
- grasp the various sub-fields of deep learning
This course has a total duration of 21 hours and takes place over 3 days
- 31-10-2023: 09:00 – 17:00
- 02-11-2023: 09:00 – 17:00
- 03-11-2023: 09:00 – 17:00
Format and Location
This course takes place ON-SITE
Terres Rouges building
14, porte de France
- Python for data-science
- Basics of machine learning
This training does not have any assessment or exams; a certificate of participation will be issued to participants.