Yann LeCun : Deep Learning & Convolutional Neural Network Ai God

Yann LeCun

Deep Learning God Yann LeCun – Rebellion Research – YouTube
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Yann LeCun : Deep Learning & Convolutional Neural Network Ai God : Professor LeCun teaches at New York University and is Facebook’s Chief Ai Scientist. Previously Yann worked for Bell Labs and is globally known as the CNN Godfather. A convolutional neural networks (CNN) is a biologically-inspired development of Machine Learning Processing. Convolutional neural networks are widely used for image classification, image clustering and object detection in images. They are also employed for optical character recognition and natural language processing.

Machine Learning Image Recognition

Yann LeCun is Director of AI Research at Facebook, and Silver Professor of Dara Science, Computer Science, Neural Science, and Electrical Engineering at New York University, affiliated with the NYU Center for Data Science, the Courant Institute of Mathematical Science, the Center for Neural Science, and the Electrical and Computer Engineering Department.

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Research Interests: AI, machine learning, computer vision, robotics, image compression

Current Projects, Research Labs, and Groups

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Systems and Control Group (SCG)

Our mission is to model and design intelligent and autonomous systems. Initially developed in the context of electric circuits, recent applications have focused on complex, dynamic and networked systems, such as unmanned vehicles and power system networks.

Yann LeCun is one of the national science heroes of France.

Yann LeCun’s Deep Learning Course at CDS

DS-GA 1008 · SPRING 2020 · CDS

Instructors​: Lectures – Yann LeCun | Practicum – Alfredo Canziani
Lectures​: ​Mondays, 16:55 – 18:35
Practica: ​Tuesdays, 19:10 – 20:00
Material​: ​Google Drive, Notebooks
NYU Deep Learning Reddit

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This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include: DS-GA 1001 Intro to Data Science or a graduate-level machine learning course.

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