Emanuele Ghelfi

Machine Learning and Computer Vision Engineer @ ZURU Tech Italy

Emanuele received the M.Sc. Degree in Computer Science and Engineering at Politecnico di Milano with 110L/110 in December 2018. In particular, he followed the Artificial Intelligence (AI) track. The AI track includes courses like Game Theory, Machine Learning, Robotics, Image Analysis and Computer Vision, Autonomous Agent and Multi-Agent Systems and Natural Language Processing.
His thesis is located in the Machine Learning field, and more precisely in the Reinforcement Learning field. The paper from his thesis has been accepted at the International Conference on Machine Learning (ICML) 2019.

Since November 2018, he has been working as a Machine Learning and Computer Vision Engineer at Zuru Tech Italy.
Currently, he's working on Generative Models (GANs) and on Recurrent Models (LSTM). In addition, he deals with Computer Vision tasks applied to complex industrial processes.

GitHub: https://github.com/EmanueleGhelfi
Website: emanueleghelfi.github.io

Institute / Company – Zuru Tech Italy Twitter handle – @manughelfi Homepage – emanueleghelfi.github.io Git*hub|lab – https://github.com/EmanueleGhelfi


Deep Diving into GANs: From Theory to Production with TensorFlow 2.0

GANs are one of the hottest topics in the ML arena; however, they present a challenge for the researchers and the engineers alike. This workshop will guide you through both the theory and the code needed to build a GAN and put into production.