Teaching

Generative Models, Q4 2019

class, ML Boot Camp, Criteo Research, 2019

This course was given as part of the ML Boot Camp for Q4, 2019 aims to introduce the audience to Generative Models. The core intuition of latent spaces and manifolds and generative modeling are introduced. The subsequent assignment based on interpolation in latent spaces allows them to practice their understanding on the subject.

Classification and Decision Trees, Q4 2019

class, ML Boot Camp, Criteo Research, 2019

This course was given as part of the ML Boot Camp for Q4, 2019 and aims to introduce the audience to Classification. Additionally it allows the audience to work through different classification algorithms to understand the difference between them as well as get a feel for the implicit bias each algorithm has. The subsequent assignment allows them to practice their understanding on the subject.

Generative Models, Q2 2019

class, ML Boot Camp, Criteo Research, 2019

This course was given as part of the ML Boot Camp for Q2, 2019 aims to introduce the audience to Generative Models. The core intuition of latent spaces and manifolds and generative modeling are introduced. The subsequent assignment based on interpolation in latent spaces allows them to practice their understanding on the subject.

Classification and Decision Trees, Q2 2019

class, ML Boot Camp, Criteo Research, 2019

This course was given as part of the ML Boot Camp for Q2, 2019 and aims to introduce the audience to Classification. Additionally it allows the audience to work through different classification algorithms to understand the difference between them as well as get a feel for the implicit bias each algorithm has. The subsequent assignment allows them to practice their understanding on the subject.

Classification and Decision Trees, Q4 2018

class, ML Boot Camp, Criteo Research, 2018

This course was given as part of the ML Boot Camp for Q4, 2018 and aims to introduce the audience to Classification. Additionally it allows the audience to work through different classification algorithms to understand the difference between them as well as get a feel for the implicit bias each algorithm has. The subsequent assignment allows them to practice their understanding on the subject.