Sergey Karayev

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Sergey Karayev’s goal is to develop and deploy AI systems to improve human life. In 2014, he finished a PhD in Computer Science at UC Berkeley and co-founded Gradescope, an AI-assisted platform for instructors to grade exams, homework, programming projects, and labs. In 2018, Gradescope was acquired by Turnitin in order to expand into STEM grading. Sergey is an instructor of a popular weekend program on Full Stack Deep Learning, and was recently selected for the 2019 UW Engineering Early Career Award.

machine learning deep learning ai computer vision big data data engineering software development reinforcement learning education vision object detection

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Sergey Karayev

Presentations

Attentional Object Detection - introductory slides.

AI Masterclass at ASU GSV 2019

Infrastructure and Tooling - Full Stack Deep Learning

Research Directions - Full Stack Deep Learning

Setting up Machine Learning Projects - Full Stack Deep Learning

Troubleshooting Deep Neural Networks - Full Stack Deep Learning

Machine Learning Teams - Full Stack Deep Learning

Testing and Deployment - Full Stack Deep Learning

Data Management - Full Stack Deep Learning

Lecture 1: Deep Learning Fundamentals - Full Stack Deep Learning - Spring 2021

Lab 1: Intro and Setup - Full Stack Deep Learning - Spring 2021

Lecture 2.A: Convolutional Networks - Full Stack Deep Learning - Spring 2021

Lecture 2.B: Computer Vision Applications - Full Stack Deep Learning - Spring 2021

Lecture 3: RNNs - Full Stack Deep Learning - Spring 2021

Lecture 4: Transformers (Full Stack Deep Learning - Spring 2021)

Lecture 5: ML Projects (Full Stack Deep Learning - Spring 2021)

Lecture 7: Troubleshooting Deep Neural Networks (Full Stack Deep Learning - Spring 2021)

Lecture 6: Infrastructure & Tooling (Full Stack Deep Learning - Spring 2021)

Lecture 8: Data Management (Full Stack Deep Learning - Spring 2021)

Lecture 9: AI Ethics (Full Stack Deep Learning - Spring 2021)

Lecture 10: ML Testing & Explainability (Full Stack Deep Learning - Spring 2021)

Lecture 11: ML Deployment & Monitoring (Full Stack Deep Learning - Spring 2021)

Lecture 12: Research Directions (Full Stack Deep Learning - Spring 2021)

Lecture 13: ML Teams (Full Stack Deep Learning - Spring 2021)

Likes

Notes from Coursera Deep Learning courses by Andrew Ng