Lec 01. Introduction to Deep Learning
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1: Introduction to Neural Networks and Deep Learning; Training Deep NNs
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Deep Learning Basics: Introduction and Overview
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3: Deep Learning for Computer Vision – Building Convolutional Neural Networks from Scratch
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3: Deep Learning for Computer Vision – Building Convolutional Neural Networks from Scratch
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Lec 02. How to Train a Neural Net
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29:00
PyTorch Tutorial
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5: Deep Learning for Natural Language – The Basics
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Lec 09. Hacker's Guide to Deep Learning
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Lec 08. Architectures: Transformers
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Lec 24. Inference Methods for Deep Learning
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Lec 18. Transfer Learning: Models
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2: Training Deep NNs (cont.); Introduction to Keras/Tensorflow; Application to Tabular Data
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MIT 6.S191 (2025): Deep Generative Modeling
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Lec 19. Transfer Learning: Data
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MIT 6.S191 (2025): Large Language Models (Liquid AI)
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Lec 21. Language Models
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MIT 6.S191 (2020): Introduction to Deep Learning
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Course Introduction of 18.065 by Professor Strang
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