MIT Introduction to Deep Learning 6.S191: Lecture 2
Recurrent Neural Networks
Lecturer: Ava Amini
2023 Edition

For all lectures, slides, and lab materials: http://introtodeeplearning.com

Lecture Outline
0:00​ - Introduction
3:07​ - Sequence modeling
5:09​ - Neurons with recurrence
12:05 - Recurrent neural networks
13:47 - RNN intuition
15:03​ - Unfolding RNNs
18:57 - RNNs from scratch
21:50 - Design criteria for sequential modeling
23:45 - Word prediction example
29:57​ - Backpropagation through time
32:25 - Gradient issues
37:03​ - Long short term memory (LSTM)
39:50​ - RNN applications
44:50 - Attention fundamentals
48:10 - Intuition of attention
50:30 - Attention and search relationship
52:40 - Learning attention with neural networks
58:16 - Scaling attention and applications
1:02:02 - Summary
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Palo Alto Networks Senior Vice President for Unit 42 Wendi Whitmore joins Caroline Hyde and Ed Ludlow to discuss ChatGPT's latest bugs and the cybersecurity concerns surrounding OpenAI's product. Plus, a look at cybersecurity trends from Palo Alto Network's latest report.
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Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. This program, driven by GPT-4, autonomously develops and manages businesses to increase net worth. As one of the first examples of GPT-4 running fully autonomously, Auto-GPT pushes the boundaries of what is possible with AI.

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00:00 - Introduction to Auto-GPT
02:09 - Setting up the Super Assistant AI
09:42 - Setting up the Private Investigator AI
14:38 - Creating an AI for Gardening YouTube Channel
17:30 - Outro

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In this Edureka live session, you will understand the fundamental concepts of Bitcoin and Blockchain with a demo of Bitcoin transactions. This session helps you to learn the following topics:
00:00:00 Introduction
00:01:00 Agenda
00:01:35 What is Bitcoin?
00:03:56 Bitcoin Transaction
00:06:40 What is Blockchain?
00:07:35 Features of Blockchain
00:13:33 Demo: Bitcoin Transaction

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Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

Welcome to this course about development with Large Language Models, or LLMs. Throughout this course, you will complete hands-on projects will help you learn how to harness LLMs for your own projects. You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.

This course was developed by @Luup.ai123

Colab notebook for introduction to the API:https://colab.research.google.....com/drive/1gi2yDvvhU
Github : https://github.com/pythononthe....plane123/LLM_course_

Join the Discord: https://discord.com/invite/Hq39QgRU
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⭐️ Contents ⭐️
⌨️ (0:00:00) Brief introduction to LLMs
⌨️ (0:11:49) Quick note from the future
⌨️ (0:12:04) Chatgpt playground (skip this is you know this already)
⌨️ (0:18:21) GPT API basics (skip this is you know this already)
⌨️ (0:30:43) Brief intro to chainlit
⌨️ (0:31:33) Cloning chatgpt user interface
⌨️ (0:45:37) Limitations of our interface
⌨️ (0:47:48) Adding streaming, backend view, stop sequence button
⌨️ (0:58:42) Introduction to vector databases
⌨️ (1:04:42) Vector databases hands on
⌨️ (1:12:10) QnA with Documents - .txt and .pdf
⌨️ (1:23:32) Testing out our Q&A system
⌨️ (1:27:22) Introduction to web-browsing and agents
⌨️ (1:32:52) AI researcher
⌨️ (1:42:23) Human as a tool
⌨️ (1:44:44) Mini code interpreter plugin(Replit tool)
⌨️ (1:46:29) Searching youtube using agents
⌨️ (1:49:19) Guide to explore more
⌨️ (1:50:33) Shell Tool
⌨️ (1:55:43) Create your own tools
⌨️ (2:01:19) Ending Notes

🎉 Thanks to our Champion and Sponsor supporters:
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This video explores Artificial General Intelligence and how it will change the world. Watch this next video called Super Intelligent AI: 10 Ways It Will Change The World: https://youtu.be/cVjq53TKKUU.
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Open AI’s Sam Altman - formerly CEO until his departure in November 2023 - sits down with Azeem Azhar to give his perspective on the evolution of artificial intelligence and its impact on politics, education and inequality.

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This video on Mathematics for Machine Learning will give you the foundation to understand the working of machine learning algorithms. You will learn linear algebra, statistics, probability, and calculus with hands-on demonstrations in Python.

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In this Top 5 AI Technologies 2021 video, you will see the most popular AI technologies that are widely used. You will get a glance at these technologies and learn where artificial Intelligence can be used. You will get an idea of the different domains where AI has found its applications.


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What is Artificial Intelligence?
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Welcome to Intellipaat's Artificial Intelligence Full Course 2024— an in-depth guide designed for absolute beginners looking to master AI and machine learning! This course covers everything you need to kickstart your journey in AI, from foundational concepts in artificial intelligence and machine learning to hands-on tutorials. Throughout this AI course for beginners, you'll explore different types of machine learning, Artificial Neural Networks, Deep Learning Fundamentals, Keras Library for AI, RNNs, GPU in Deep Learning, etc. to excel in today’s AI-driven world. Our course is ideal for anyone who wants to learn artificial intelligence from scratch and gain practical knowledge for real-world AI projects.

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00:00:00 - Introduction to Artificial Intelligence Course
00:03:29 - What is Artificial Intelligence
00:07:17 - Why Artificial Intelligence
00:57:05 - Machine Learning Types
01:07:35 - Introduction to Deep Learning
02:45:16 - Benefits of Using Artificial Neural Network
02:50:26 - Deep Learning Frameworks
03:02:57 - Data Handling with NumPy
03:20:28 - Introduction to TensorFlow
05:23:00 - Understanding Epoch
05:50:38 - Introduction to Keras
06:43:35 - Predefined Neural Network Layers
08:43:11 - Problem With a Fully Connected Network
08:52:56 - Convolutional Neural Network
10:13:25 - Rectified Linear Units
10:45:45 - Artificial Intelligence Interview Questions

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In 2024, becoming a Data Analyst is one of the smartest career choices you can make! With the demand for data-driven decisions soaring, companies like Google, Amazon, and IBM are on the lookout for skilled data analysts who can turn raw data into actionable insights. This role is future-proof, offering a perfect blend of technology and business. You don’t need to be a coding expert to start; mastering the basics of Python or R, along with tools like Tableau and Power BI, will set you on the right path.

In this video, we’ll walk you through everything you need to know to become a Data Analyst in 2024—from the essential skills and education to industry opportunities and salary expectations. Plus, you’ll get a glimpse into real-world applications of data analysis across various sectors, and how you can advance your career with continuous learning and specialization.
Following are the topics covered in this video:

00:00 - Introduction
01:45 - What does data analyst do
02:45 - How to become Data Analyst
03:30 - Skills
06:22 - Where do they work?
07:07 - How much do they make?
07:27 - How to learn in 2024
09:37 - Networking
11:07 - Job Outlook in 2024

✅Do I need a degree to become a Data Analyst?
Ans : While a degree in fields like statistics or computer science is helpful, practical experience and certifications can also open doors.

✅How much coding do I need to know?
Ans: Basic knowledge of Python or R is enough to get started, with tools like Tableau and Power BI minimizing the need for heavy coding.

✅What is the salary range for Data Analysts in 2024?
Starting salaries typically range from $60,000 to $100,000 or more, depending on experience and location.

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➡️ About Post Graduate Program In Data Analytics
This Data Analytics Program is ideal for all working professionals and prior programming knowledge is not required. It covers topics like data analysis, data visualization, regression techniques, and supervised learning in-depth via our applied learning model with live sessions by leading practitioners and industry projects.

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MIT 3.020 Thermodynamics of Materials, Spring 2021
Instructor: Rafael Jaramillo

View the complete course: https://ocw.mit.edu/courses/3-....020-thermodynamics-o
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

This first class session introduces entropy and spontaneous processes, molecular interactions, and enthalpy, as well as the scope and use of thermodynamics.

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In this tutorial we build a Sequence to Sequence (Seq2Seq) model from scratch and apply it to machine translation on a dataset with German to English sentences, specifically the Multi30k dataset. There was a lot of things to go through and explain so the video is a bit longer than my normal videos, but I really felt I wanted to share my thoughts, explanations and the details of the implementation!

Resources I used and read to learn about Seq2Seq:
https://github.com/bentrevett
https://arxiv.org/abs/1409.3215
https://pytorch.org/tutorials/....intermediate/seq2seq

Comment on resources:
I think bentrevett on Github is awesome and I was heavily inspired in this video by his Seq2Seq Tutorials and I really recommend checking him out, he puts out a lot of great tutorials on his Github.

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
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DL Specialization (no affiliate): https://bit.ly/3t8JqA9

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OUTLINE:
0:00 - Introduction
1:27 - Imports
2:05 - Data processing using Torchtext
5:55 - Implementation of Encoder
11:02 - Implementation of Decoder
19:43 - Putting it togethor to Seq2Seq
27:57 - Setting up training of the network
41:03 - Fixing Errors
42:18 - Evaluation of the model
49:32 - Ending and Bleu score result