Camille Van Hoffelen
Next training: December 13 to January 21
Join a 6-week training to take your applied and theoretical Deep Learning skills to the next level.
Keep up with the state-of-the-art to lead experiments and discussions in your Machine Learning team.
Part-time course compatible with your full-time job.
You will learn to wrestle with Deep Learning (DL) methods, and make Neural Networks (NNs) reveal all their secrets.
Explore Neural Network theory from scratch, and put it into practice with Pytorch.
Deep dive into Neural Network optimisation and regularisation methods, and debug common training issues in pytorch.
Deep Learning methods applied to image data: learn about CNNs, understand the transfer learning revolution, and discover generative models.
Deep Learning methods applied to text data: learn feature representations of symbolic sequences, tackle the almighty transformer, and experiment with generative language models.
The best of the rest: apply sequence models to time series data, explore the seq2seq paradigm, and tackle imitation learning with knowledge graphs.
This chapter tests your skills by implementing a state-of-the-art Deep Learning model from literature, and training it on a public dataset.
Camille has worked as a Machine Learning Engineer for the last 7 years (Seal, DocuSign...), with a focus on large scale Natural Language Processing systems.
Camille graduated with an MSci in Physics from Imperial College London, before catching the data science bug and diving into legal AI with Seal Software, later acquired by Docusign.
He was a lecturer in Machine Learning at Ilia State University, and remains an avid presenter at meetups and hackathons around Europe.
Camille is currently the CTO & Co-founder of Watergenics, where he strives to build a sustainable future for our blue Planet by augmenting water quality sensors with AI.
December 13 to January 21
What's included in the live course:
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We'd be happy to answer your questions, and check together if the program is a good fit for you.
Alumni, students & teachers are the heartbeat of the Jungle Program community.
Graduates are data scientists, machine learning engineers, full-stack developers and CTO of startups.