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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.

The top networking commands covered in this demo session are:
00:00 introduction
00:59 ipconfig
01:36 hostname
01:53 ping
02:22 nslookup
02:56 tracert
03:17 arp
03:31 pathping
03:52 netstat
04:09 netshare
04:20 route
04:40 netsh
04:58 tasklist
05:26 taskkill
05:47 systeminfo
06:01 wmic

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✅ About Advanced Executive Program in Cybersecurity:

Become an industry-ready professional with an Advanced Executive Program in Cybersecurity and transform your career in 6 months. This course provides a high-engagement learning experience with real-world applications and is designed for individuals who want to start a new, more fulfilling career. This Advanced Executive Program in Cybersecurity will help you develop expertise in defensive cybersecurity, application security, malware analysis, ethical hacking, and much more.

Key Features:

✅ Advanced Executive Program in Cybersecurity completion certificate from IIIT Bangalore
✅ 8X higher interaction in live online classes conducted by industry experts
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✅ Virtual Internship Certificate from NPCI
✅ Masterclasses from top faculty of IIIT Bangalore
✅ Get noticed by the top hiring companies

✅ What are the eligibility criteria's for this Advanced Executive Program in Cybersecurity?

For admission to this Advanced Executive Program in Cybersecurity, candidates:
- Should have a bachelor's degree in any discipline with an average of 50% or higher marks
- Prior work experience of 1 years or more
- May have a non-programming background

✅ Will financial aid be provided for this Advanced Executive Program in Cybersecurity?

To ensure money is not a limiting factor in learning, we offer various financing options to help make this cyber security certification in India financially manageable. For more details, please refer to our "Admissions Fee and Financing" section.

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In this video on" What is Generative Ai" we dive into the exciting realm of Generative AI, a cutting-edge field at the intersection of artificial intelligence and creativity. Join us on a journey to understand the underlying principles and techniques behind Generative AI. We'll explore Generative AI, how Generative AI works, Use cases of Generative AI, and the advantages & disadvantages of Generative AI. Below are the topics covered in this Introduction to Generative AI Video.

00:00 What is Generative AI
01:34 How does Generative AI work?
02:28 Generative AI applications
04:45 Use Cases of Generative AI
06:14 Advantages of Generative AI
08:17 Limitations of Generative AI

Generative AI, a form of artificial intelligence, possesses the capability to generate a wide range of content, including text, visuals, audio, and synthetic data. The recent excitement surrounding generative AI stems from the user-friendly interfaces that allow users to effortlessly create high-quality text, graphics, and videos within seconds.

✅ Learn the Basics of AI for free & get a Completion Certificate, Enroll Now: https://www.simplilearn.com/learn-ai-basics-skillup?utm_campaign=POS-WhatIsGenerativeAI23May2023&utm_medium=Description&utm_source=youtube

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#GenerativeAI #OpenAI #GenerativeModels #GenerativeAICourse #AIAndML #GoogleBard #ChatGPT #BingAI #ArtificialIntelligenceCourse #MachineLearningCourse #AIEngineer #ArtificialIntelligence #AICareer #MLCareer #MachineLearning #ML #2023 #Shorts #Simplilearn

✅ AI ML Course Overview

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

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- Post Graduate Program certificate and Alumni Association membership
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- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more
- Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools

✅ Skills Covered

- ChatGPT
- Generative AI
- Explainable AI
- Generative Modeling
- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- NLP
- Neural Networks
- Computer Vision
- GANs

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6 Reasons Why ChatGPT Can Make Your Business by simplilearn is a tutorial based in Artificial Inteliigence and Large Learning Models. This AI tutorial will discuss the top 6 reasons why chatGPT and AI can help you build a successful business.. The video cover How to Use ChatGPT to Grow Your Business and to tap out the best out of your business. This Simplilearn tutorial will cover the following six reasons.

00:00:00 Introduction to 6 Reasons Why chatGPT can make your business
00:02:00 Decision Making Capabilities
00:02:50 Customer Services
00:03:45 Content Creation
00:04:24 AI and ChatGPT for Data analysis
00:05:38 Sales and Marketing
00:06:49 Automation

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#ArtificalIntelligence #ChatGPT #MachineLearning #ChatGPTForBusiness #AI #ML #GPT3 #GPT4 #HowToUseChatGpt #ChatBotOpenAI #Simplilearn

✅ AI ML Course Overview

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

✅ Key Features

- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
- 3 Capstones and 25+ Projects with industry data sets from Twitter, Uber, Mercedes Benz, and many more
- Master Classes delivered by Purdue faculty and IBM experts
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more
- Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools

✅ Skills Covered

- ChatGPT
- Generative AI
- Explainable AI
- Generative Modeling
- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- NLP
- Neural Networks
- Computer Vision

👉Learn more at: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=6ReasonsWhyChatGPTCanMakeYourBusiness25May2023&utm_medium=ShortsDescription&utm_source=youtube
🔥🔥 *Interested in Attending Live Classes? Call Us:* IN - 18002127688 / US - +18445327688

✅ Know our learners and their journeys: https://www.simplilearn.com/reviews?utm_campaign=6ReasonsWhyChatGPTCanMakeYourBusiness25May2023&utm_medium=Description&utm_source=youtube

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Get the Simplilearn app: https://simpli.app.link/OlbFAhqMqgb

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3BcmeEA

Jure Leskovec
Computer Science, PhD

Having defined a GNN layer, the next design step is how to stack GNN layers together. To motivate different ways of stacking GNN layers, we first introduce the issue of over-smoothing that prevents GNNs learning meaningful node embeddings. We learn 2 lessons from the problem of over-smoothing: (1) We should be cautious when adding GNN layers; (2) we can add skip connections in GNNs to alleviate the over-smoothing problem. When the number of GNN layers is small, we can enhance the expressiveness of GNN by creating multi-layer message / aggregation computation, or adding pre-processing / post-processing layers in the GNN.

To follow along with the course schedule and syllabus, visit:
http://web.stanford.edu/class/cs224w/

✍ My book : https://www.amazon.com/dp/B0915RP5XK

Contact me ✔
✉ Email: [email protected]

Welcome to this No Black Box Machine Learning Course in JavaScript. It’s a course where we code without using libraries because it’s the best way to learn all inner workings of a machine learning system and you’ll greatly improve your software development skills as well.

The goal in this course is to build a web app that learns to recognize drawings. This is phase 2, where we increase the accuracy of the method we developed in Phase 1. We do this by implementing more sophisticated features and using other classification methods (like the Neural Network). In Phase 2 we also learn about Data Cleaning, Confusion Matrices, Geometry and the difference between Vector and Raster data (pixels).

🎥 No Black Box Phase 1 Course: https://youtu.be/vDDjtwQDw2k

✏️ Course created by @Radu (PhD in Computer Science)

📁 Data: https://github.com/gniziemazity/drawing-data
💻 Code: https://github.com/gniziemazity/ml-course-phase-2
💻 Ilya's code: https://gist.github.com/id-ily....ch/8630fb273e5c5a0b6
💻 Neural Network Code: https://github.com/gniziemazity/neural-network
Phase 3 Poll: https://forms.office.com/e/QTMCLLaV24

⭐️ Other Resources ⭐️
Recognizer we build in this course: https://radufromfinland.com/projects/ml/recognizer
Euclidean Distance Video: https://youtu.be/3rPwfmrCwVw
Interpolation Video: https://youtu.be/J_puRs40GhM
Draw the Portal Game Tutorial (Inspired from Dr. Strange): https://youtu.be/0SxiyLk2IMM
Why the Circle has the Largest Area: https://youtu.be/CFBa2ezTQJQ
Recognizing drawings via webcam: https://youtu.be/QXB1ytG95gs
Self-driving Car Course: https://youtu.be/Rs_rAxEsAvI
Discord Server: https://discord.com/invite/gJFcF5XVn9
Scikit-learn documentation: http://scikit-learn.org/stable..../modules/generated/s

⭐️ Contents ⭐️
0:00:00 Introduction
0:04:07 Phase 1 Code Review
0:23:11 Data Cleaning
0:41:30 Confusion Matrix
1:16:00 Euclidean Distance Marker
1:16:06 Measuring the Elongation
1:39:23 Measuring the Roundness
1:59:20 Vector vs Raster (Pixels)
2:22:40 Neural Networks
3:04:49 Optimizing Neural Networks
3:25:15 Deep Neural Networks

🎉 Thanks to our Champion and Sponsor supporters:
👾 davthecoder
👾 jedi-or-sith
👾 南宮千影
👾 Agustín Kussrow
👾 Nattira Maneerat
👾 Heather Wcislo
👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan
👾 Oscar Rahnama

--

Learn to code for free and get a developer job: https://www.freecodecamp.org

Read hundreds of articles on programming: https://freecodecamp.org/news

🔥 Prompt Engineering Course: https://www.edureka.co/prompt-....engineering-generati
This informative video on Prompt Engineering for Code Generation will help you understand prompt engineering for code generation, its principles, and a few practical questions. Gain insights into how prompt engineering for code generation is shaping various industries and staying ahead in the dynamic field of artificial intelligence. In this informative video of Prompt Engineering For Code Generation, we will cover essential topics such as:

✅ 00:00 - Introduction
✅ 00:58 - Prompt engineering for code generation
✅ 01:32 - Principles of Prompt Engineer
✅ 05:15 - Prompt engineering for coding practical examples

✅ Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

📝Feel free to share your comments below.📝

𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
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📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_learning/
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📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

- - - - - - - - - - - - - -

About Prompt Engineering Course
A streamlined curriculum covering fundamental engineering concepts in physics, electronics, and mathematics is provided by the Prompt Engineering Course. Through projects and assessments, it places a strong emphasis on experiential learning, preparing students for careers in entry-level engineering or for further study.
- - - - - - - - - - - - - -

Who should go for this course?
The Prompt Engineering Course is appropriate for people who want to work in engineering or related fields and need a structured introduction to basic ideas and practical experience. It serves both novices and those seeking to reinforce their grasp of fundamental engineering concepts.

- - - - - - - - - - - - - -
What are the Prerequisites for this course?
Although there are no formal prerequisites for the Prompt Engineering Course, it usually helps to have a basic understanding of mathematics and physics. It is intended for people who want to learn the fundamentals of engineering in order to pursue careers or further education in engineering-related fields.

For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: +18338555775 (toll-free).
#edureka #edurekatraining #promptengineer #code generation #prompt #promptcodegeneration #edurekacourse"

MIT Introduction to Deep Learning 6.S191: Lecture 4
Deep Generative Modeling
Lecturer: Ava Amini
*New 2024 Edition*

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

Lecture Outline
0:00​ - Introduction
6:10- Why care about generative models?
8:16​ - Latent variable models
10:50​ - Autoencoders
17:02​ - Variational autoencoders
23:25 - Priors on the latent distribution
32:31​ - Reparameterization trick
34:36​ - Latent perturbation and disentanglement
37:40 - Debiasing with VAEs
39:37​ - Generative adversarial networks
42:09​ - Intuitions behind GANs
44:57 - Training GANs
48:28 - GANs: Recent advances
50:57 - CycleGAN of unpaired translation
55:03 - Diffusion Model sneak peak

Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!

🔥CompTIA Security+ (Plus) Certification - SY0-701 Exam Training - https://www.simplilearn.com/comptia-security-plus-certification-training?utm_campaign=xtnMQKpLgcc&utm_medium=DescriptionFirstFold&utm_source=Youtube
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In this cybersecurity Full course for beginners, you will learn the importance of cybersecurity, cybersecurity skills, what cybersecurity means, and the types of cyberattacks with a hands-on demo for each. This video also covers cryptography, ethical hacking, and the top cybersecurity certifications.

Below are the topics covered in this Cyber Security full course video:

00:00:00 Introduction to Cybersecurity Full Course
00:14:24 What is Cyber Security
00:15:15 Toughest Cybersecurity Certifications
03:12:01 Cyber Security Basics
03:23:52 Phishing Attacks
03:24:35 Top 7 Dangerous Hacking Gadgets
08:06:37 Live Demonstrations
08:24:06 ChatGPT For Ethical Hacker
08:24:34 Common Cybersecurity Mistakes
09:16:10 Cybersecurity Interview Questions

✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Cyber Security training videos: https://www.youtube.com/playli....st?list=PLEiEAq2VkUU

#CyberSecurity #CyberSecurityFullCourse #CyberSecurityCourse #LearnCyberSecurity #CyberSecurityTrainingForBeginners #CyberSecurityExplained #CyberSecurityTutorial #Simplilearn

What Is Cyber Security?
Cyber Security involves techniques that help in securing various digital components, networks, data, and computer systems, from unauthorized digital access. There are several ways to implement cybersecurity, depending on the kind of network you are connected to and the type of cyberattacks you are prone to. A few ways to implement cybersecurity are defining clear boundaries, using network security control devices like Firewalls and IDS, and carrying out security testing.

➡️ About Post Graduate Program In Cyber Security

This Post Graduate Program in Cyber Security will help you learn comprehensive approaches to protecting your infrastructure and securing data, including risk analysis, mitigation, and compliance. You will get foundational to advanced skills through industry-leading cyber security certification courses that are part of the program.

Key Features

✅ Simplilearn Post Graduate Certificate
✅ Masterclasses from MIT Faculty
✅ Featuring Modules from MIT SCC and EC-Council
✅ 8X higher interaction in live online classes conducted by industry experts
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Industry case studies in cyber security
✅ Access to CEH Pro Version
✅ 25+ hands-on projects
✅ Capstone project in 3 domains
✅ MIT CSAIL Professional Programs Community

Skills Covered

✅ Advanced Hacking Concepts
✅ Network Packet Analysis
✅ Ethical Hacking
✅ IDS Firewalls and Honeypots
✅ Security and Risk Management
✅ Network Security
✅ Software Development Security
✅ Cryptography OSI and TCPIP Models
✅ Identity and Access Management
✅ Security Assessment and Testing
✅ Trojans Backdoors and Countermeasures
✅ Mobile and Web Technologies

Learning Path
✅ CS - Induction for Professional Certificate Program in Cyber Security
✅ CS - Operating Systems and Networking Essentials
✅ CS - Enterprise Infrastructure Security
✅ CS - Application Security, Vulnerability Management, and Cyber Resilience
✅ CS - Ransomware and Malware ✅ Defense, Analysis and Response
✅ CS - Ethical Hacking ✅ From Recon to Attack
✅ CS - Vulnerability Assessment and Penetration Testing (VAPT)
✅ CS - Cyber Capstone Project
Electives:
✅ CS - Academic Masterclass
✅ CS - Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ CS - Generative AI with Cybersecurity
✅ IBM : Network Security & Database Vulnerabilities
✅ IBM : Penetration Testing, Incident Response and Forensics

👉 Learn More at: https://www.simplilearn.com/pgp-cyber-security-certification-training-course?utm_campaign=xtnMQKpLgcc&utm_medium=Description&utm_source=youtube

In this video, Dr. Raj Dandekar (MIT PhD) teaches you how to build a production level SLM entirely from scratch.

You will learn the following:

(1) Creating the dataset
(2) Tokenizing the dataset
(3) Creating input-target pairs
(4) Creating the entire SLM architecture
(5) Setup the SLM for pre-training
(6) Pre-training the SLM
(7) Inference

Google Colab Notebook: https://colab.research.google.....com/drive/1k4G3G5MxY

How To Train AI Models using Unsloth
Unlock the secrets to training powerful AI models that can outperform giants like Chat GPT and Claude, right from your personal computer and for less than $5! This video reveals how specialized, fine-tuned models can achieve superior accuracy on specific tasks compared to their larger counterparts. Discover the critical, yet often overlooked, aspects of AI training that big companies don't talk about, including the most effective ways to structure your data for success with tools like Unsloth. Whether you're a business owner, developer, or AI enthusiast, learn the practical steps to build your own custom AI solutions efficiently.

🔗 What We Cover:
- The Underdog Advantage: Understand why smaller, fine-tuned AI models can surpass large language models like GPT-4 in specialized tasks, backed by surprising accuracy stats.
- Cost-Effective AI Training: Learn how to train high-performing AI models in just a couple of hours on your personal computer for minimal cost (even free using Google Colab with a T4 GPU!).
- The Data Structuring Secret: Master the simple yet crucial two-column (instruction/input and output) data format required for effective model training with Unsloth, avoiding common pitfalls.
- Practical Fine-Tuning Examples: See real-world data structuring for an AI gym trainer and a customer service response bot.
- Step-by-Step Unsloth Tutorial: Follow along as we build an AI workout generator using Unsloth in a Google Colab notebook, from data preparation to model training and testing.
- Beyond the Hype: Uncover the techniques that companies like Google, DeepMind, and OpenAI use, adapted for your own projects.

💡 Embrace the Future of AI:
Step into the world of custom AI model training! This guide empowers you to bypass the need for massive datasets and expensive infrastructure. Learn the secrets to creating specialized AI that truly understands your unique context and delivers exceptional results.

Join me as I demystify AI model training, showing you exactly how to achieve remarkable performance without breaking the bank. Don't forget to like, share, and subscribe for more insights into practical AI implementation!

👨‍💻 Follow Me:
Website: https://www.rolandburke.com
Be there first to know when the community drops: https://www.rolandburke.com/join-now
Twitter: https://twitter.com/rjburkejr
LinkedIn: https://www.linkedin.com/in/rolandburke

Videos I Think You'll ❤️:
How To Install Text Generation Web UI
https://youtu.be/Lm2xpJ5TQBo

How To Use ChatGPT Inside Of Airtable
https://youtu.be/extjQChhE-M
========================

🎥 Video Breakdown
0:00 - Introduction: Training AI Better Than ChatGPT for Cheap
0:06 - The High Cost of Traditional AI Training
0:25 - The Big Secret: Smaller Models, Better Results?
0:47 - Why Fine-Tuned Models Outperform Giants (Study Results)
2:09 - The Power of Small Datasets (200-500 Examples)
2:20 - Why Specialization Beats Generalization in AI
2:34 - Critical Mistake: The Importance of Training Data Structure
3:14 - Simplifying Data Structure with Unsloth: The Two-Column Method
3:54 - Example 1: Structuring Data for an AI Gym Trainer
4:44 - Example 2: Structuring Data for Customer Service AI
5:43 - Step-by-Step: Training Your AI Model with Unsloth in Google Colab
6:01 - Demo: Building an AI Workout Generator - Data Prep
6:25 - Colab Setup: Choosing a Model (Meta Llama 3.1 8B) & Lora Adapters
7:39 - Training the Model: Settings & Process (Max Steps, Epochs, Learning Rate)
8:25 - Analyzing Training Results & Loss Rate
8:31 - Testing Your Fine-Tuned AI Model: Workout Generator in Action
9:01 - Conclusion: Train Your Own AI for Free/Cheap!
9:14 - Beyond Fine-Tuning: Access a Suite of AI Tools
9:29 - Join the AI Community & Waitlist

Learn more: https://bit.ly/4mVUPyF

Building effective Agentic AI systems is one of the most valuable skills in AI today.

Introducing Agentic AI, a new course from Andrew Ng, now available on DeepLearning.AI.

While most developers build AI that just responds to prompts, the most productive teams are building AI that executes multi-step workflows autonomously. 

In this course, you'll learn how to build 4 key agentic workflows using raw Python so that you'll see how each step actually works.

Skills you’ll gain: 

- Build agentic design patterns: reflection, tool use, planning, and multi-agent workflows
- Integrate AI with external tools: databases, APIs, web search, and code execution
- Evaluate and optimize AI systems: performance metrics, error analysis, and production deployment

Build everything from scratch in Python—no frameworks, no black boxes.

Agentic AI is available exclusively on DeepLearning.AI. With a Pro membership you get access to quizzes, code labs, and Professional Certifications along with early access to our available catalog of advanced AI courses.

Enroll in Agentic AI on DeepLearning.AI: https://bit.ly/4mVUPyF

MIT 14.02 Principles of Macroeconomics, Spring 2023
Instructor: Ricardo J. Caballero

View the complete course: https://ocw.mit.edu/courses/14....-02-principles-of-ma
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

This lecture covers an introduction to the topic of macroeconomics, which is the study of the behavior of an economy as a whole. The instructor also talks about the objectives of the course.

License: Creative Commons BY-NC-SA
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This video introduces the fundamentals of protein design and summarizes the trajectory of the course with a focus on (1) the foundational biochemistry that protein structure prediction and design hinge on and (2) deep learning / machine learning principles overview.

Video from the Rosetta Commons PPI Workshop (February 2025)
Video Instructor: Amrita Nallathambi (UNC Chapel Hill)

Credits:
Instructor: Amrita Nallathambi
Teaching Assistants: Yehlin Cho, Cyrus Haas, and Matthew Hvasta,
RC Leadership and NSF Sponsor Grant PIs: Julia Koehler Leman & Jeffrey Gray
RC Education Director: Ashley Vater
Videographer: Canyon Florey
Rosetta Workshop Participants

00:00 - Introduction
00:20 - Deep Learning Revolution for Proteins
01:50 - The Transformer
03:38 - AlphaFold2 Overview
06:22 - AlphaFold2 Inputs
09:48 - AlphaFold2 Outputs
13:29 - Graph Neural Networks
16:24 - ProteinMPNN Loss
17:35 - Diffusion models
18:30 - RFDiffusion
19:52 - Inputs and Outputs
20:43 - Potentials