In this video we go through how to code the GoogLeNet or InceptionNet from the original paper in Pytorch. I explain how the network works in the first couple of videos and then how to implement it from scratch.

Paper:
https://arxiv.org/abs/1409.4842


People often ask what courses are great for getting into ML/DL and the two I started with is ML and DL specialization both by Andrew Ng. Below you'll find both affiliate and non-affiliate links if you want to check it out. The pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
ML Course (affiliate): https://bit.ly/3qq20Sx
DL Specialization (affiliate): https://bit.ly/30npNrw
ML Course (no affiliate): https://bit.ly/3t8JqA9
DL Specialization (no affiliate): https://bit.ly/3t8JqA9

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PyTorch Playlist:
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Reviewing Lambda and Razer's Tensorbook, a laptop aimed at deep learning, with 16GB of VRAM (GPU memory), 64GB of RAM, 2TB of NVMe storage and an 8-core intel i7 11800H CPU.
https://lambdalabs.com/deep-le....arning/laptops/tenso

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¿Queres aprender a sobre machine learning y deep learning? en este video vamos a hablar de la inteligencia artificial, deep learning y machine learning, vas a aprender mucho.

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In this interactive session on "Top Networking Commands," we will look at some of the preferred commands applied in the window's command prompt application to access information and configure network settings for our respective devices. In this demo session, you will understand the execution and the functioning of multiple network commands for better handling of our systems.

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GPT3 & Beyond: Key concepts and open questions in a golden age for natural language understanding

Listen in as Professor Christopher Potts discusses the significance and implications of recent Natural Language Understanding developments including GPT-3. He describes the fundamental building blocks of these systems and describes how we can reliably assess and understand them.

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View the slides for this webinar here: https://stanford.io/potts-GPT3-webinar2023

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Chapters:
0:00 Opening
00:09 Introduction for Chris Potts
1:09 Chris Potts - Welcome to the webinar
03:43 Quick Demo of GPT-3
06:41 GLUE benchmark
10:26 How can you contribute to NLU in this era of these gargantuan models?
11:44 The last mile problem
13:35 GPT example
14:50 Contrast In-Context learning with the standard paradigm of standard supervision
16:47 What are the mechanisms behind this?
18:18 Why does this work so well?
18:35 Self-Supervision
21:08 The role of human feedback
21:32 Chat GPT Diagram
23:42 Step-by-step reasoning
28:13 LLMs for everything approach
41:29 AI Courses at Stanford
46:28 Predictions about the future