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Lec 01. Introduction to Deep Learning

Lec 01. Introduction to Deep Learning

03:30 678,121 views

2: Training Deep NNs (cont.); Introduction to Keras/Tensorflow; Application to Tabular Data

2: Training Deep NNs (cont.); Introduction to Keras/Tensorflow; Application to Tabular Data

03:30 200,096 views

1: Introduction to Neural Networks and Deep Learning; Training Deep NNs

1: Introduction to Neural Networks and Deep Learning; Training Deep NNs

57:05 476,778 views

MIT Introduction to Deep Learning | 6.S191

MIT Introduction to Deep Learning | 6.S191

56:16 906,267 views

Lec 02. How to Train a Neural Net

Lec 02. How to Train a Neural Net

03:30 948,499 views

7: Deep Learning for Natural Language – Transformers

7: Deep Learning for Natural Language – Transformers

03:30 750,370 views

3: Deep Learning for Computer Vision – Building Convolutional Neural Networks from Scratch

3: Deep Learning for Computer Vision – Building Convolutional Neural Networks from Scratch

03:30 326,863 views

9: Generative AI – Large Language Models (LLMs) and Retrieval Augmented Generation (RAG)

9: Generative AI – Large Language Models (LLMs) and Retrieval Augmented Generation (RAG)

03:30 500,019 views

MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention

MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention

57:34 693,097 views

🎓 Featured Course Guide & Lesson Notes: Lec 01. Introduction to Deep Learning

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Instructor: MIT OpenCourseWare  |  Runtime: 03:30 mins  |  Students / Views: 678,121

MIT 6.7960 Deep Learning, Fall 2024 Instructor: Sara Beery View the complete course: https://ocw.mit.edu/courses/6-7960-deep-learning-fall-2024/ YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63URZnh5iqBzDTDYPUTQT-8 This video provides a course overview and introduces deep neural networks, covering their fundamental concepts and basic building blocks. It sets the stage for understanding how these models work and what components they are built from. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu Support OCW at http://ow.ly/a1If50zVRlQ We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments. Key Highlights & Overview: Mastering <strong>Mit Deep Learning Course</strong> requires clear step-by-step guidance and practical hands-on visual demonstrations. Explore curated video courses, expert walkthroughs, and detailed lesson notes today on <strong>TutorTube</strong>.