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Learn about AI at Tesla from Senior Director, Andrej Karpathy, in this less than 1-hour material from The Full Stack.
Learn about Deep Learning Frameworks from Yangqing Jia, VP AI/Big Data at Alibaba and co-creator of Caffe2 and Caffe, in less than an hour with The Full Stack.
Learn about the lifecycle of a deep learning model and data science strategies from Jai Ranganathan, SVP Product at KeepTruckin and former VP at Uber. Less than 1-hour workload.
Learn how to structure a Machine Learning team within an organization in less than an hour with The Full Stack. Understand different ML organizations and key design choices.
Learn from Chip Huyen, creator of Stanford's TensorFlow for Deep Learning Research, as she shares insights on machine learning interviews. This less than 1-hour material from The Full Stack covers research roles, interview tips, and more.
Explore state-of-the-art deep learning methods with Professor Pieter Abbeel in this 1-2 hour material from The Full Stack. Dive into reinforcement learning, imitation learning, and more.
Explore the nuances of choosing hardware for computing needs, comparing NVIDIA cards, cloud providers like AWS and Google Cloud, and strategies for different work environments. Offered by The Full Stack.
Explore practical deep learning systems with Xavier Amatriain in this under 1-hour material from The Full Stack. Learn about data transfer, model architecture, and machine learning infrastructure.
Learn from Richard Socher, Chief Scientist at Salesforce, about using deep learning for NLP tasks in this less than 1-hour material from The Full Stack.
Learn from Jeremy Howard's expertise in machine learning, data labeling, and deep learning successes in less than an hour with The Full Stack.
Explore exciting research directions in deep learning with Professor Pieter Abbeel in a 1-2 hour lecture from The Full Stack.
Learn to test and deploy machine learning projects with Sergey Karayev from The Full Stack. Topics include AB testing, software engineering, Docker, and serverless deployment.
Learn to transform ML models into products with The Full Stack's short video. Covers prototype deployment, various architectures, optimization, and edge deployment.
Learn data management from The Full Stack in under an hour. Topics include data storage, processing, annotation, and versioning, with a focus on best practices.
Learn to test ML codebases and troubleshoot deep neural networks in under an hour with The Full Stack. Gain knowledge on testing tools, clean code tools, and automation.
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