🔥Purdue - Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=Ot1Q1fuLNuw&utm_medium=Lives&utm_source=Youtube
🔥Professional Certificate Program in Generative AI and Machine Learning - IITG (India Only) - https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=Ot1Q1fuLNuw&utm_medium=Lives&utm_source=Youtube
🔥Advanced Executive Program In Applied Generative AI - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=Ot1Q1fuLNuw&utm_medium=Lives&utm_source=Youtube

This Generative AI Full Course 2025 by Simplilearn provides a structured learning path, starting with the fundamentals of Generative AI and a detailed roadmap to mastering it. Learners explore top AI technologies, including DeepSeek R1, Deep Learning, and Search GPT, followed by essential tools like LangChain. The course dives into Generative Adversarial Networks (GANs), Transformers, and Long Short-Term Memory (LSTM) networks, forming the foundation of modern AI models. It then introduces Large Language Models (LLMs), Machine Learning concepts, and Reinforcement Learning, leading into practical applications like ChatGPT analysis and OpenAI Sora. Advanced topics include LLM benchmarking, Hugging Face tutorials, and OpenAI's ChatGPT O1 model. Practical insights into Generative AI tools for job interviews, Agentic AI, and AI monetization strategies help learners stay ahead in the field. The course concludes with a look at Google Quantum AI and Machine Learning interview preparation, ensuring a strong grasp of both theoretical and applied AI concepts.

Following are the topics covered in the Generative AI Full Course 2025:

00:00:00 Introduction to Gen AI Full Course 2025
00:04:37 What is Gen AI ?
00:05:22 Gen AI Tutorial for beginners
00:16:01 Roadmap to become a Gen AI Engineer
00:25:51 Introduction to LLM
01:27:04 What is Machine Learning?
02:23:36 Machine Learning Tutorial
04:28:59 Reinforcement Learning
04:45:04 Deepseek r1
04:52:03 Deep Learning
05:00:20 Search GPT
05:02:35 Langchain
05:59:10 Generative Adversarial Tutorial
06:08:32 What are Gans
06:09:33 Transformers in AI
06:22:02 LSTM
06:41:53 CHatgpt analyse
06:52:49 Openai sora
07:01:42 LLM Benchmarkeing
07:52:25 Hugging Face and its tutorial
08:07:49 Open ai chatgpt o1 model
08:44:51 Agentic AI
08:53:14 Google Quantam AI
08:58:23 Gen ai tools for job interview
10:58:44 Deep learning Interview questions

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

⏩ Check out the Artificial Intelligence training videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULa5a

#genai #generativeai #artificialintelligence #ai #machinelearning #llm #simplilearn #2025

➡️ About Professional Certificate Program in Generative AI and Machine Learning

Dive into the future of AI with our Generative AI & Machine Learning course, in collaboration with E&ICT Academy, IIT Guwahati. Learn tools like ChatGPT, OpenAI, Hugging Face, Python, and more. Join masterclasses led by IITG faculty, engage in hands-on projects, and earn Executive Alumni Status.

Key Features:
✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
✅ Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
✅ Opportunity to earn an 'Executive Alumni Status' from E&ICT Academy, IIT Guwahati
✅ Eligibility for a campus immersion program organized at IIT Guwahati
✅ Exclusive hackathons and “ask-me-anything” sessions by IBM
✅ Certificates for IBM courses and industry masterclasses by IBM experts
✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
✅ Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered:
✅ Generative AI
✅ Prompt Engineering
✅ Chatbot Development
✅ Supervised and Unsupervised Learning
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Machine Learning Algorithms
✅ Speech Recognition
✅ Statistics

Learning Path:
✅ Program Induction
✅ Programming Fundamentals
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning with TensorFlow (IBM)
✅ Deep Learning Specialization
✅ Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ Advanced Generative AI
✅ Capstone
Electives:
✅ ADL & Computer Vision
✅ NLP and Speech Recognition
✅ Reinforcement Learning
✅ Academic Masterclass
✅ Industry Masterclass

👉 Learn More At: https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=Ot1Q1fuLNuw&utm_medium=Lives&utm_source=Youtube

In this video, I dive into the world of agentic AI, a concept that's set to be a major buzzword in 2025. We explore how agentic AI combines multiple agents—some of which are language models (LLMs) and others that are tools—to create more sophisticated and effective AI workflows. We walk through a simple example of how an AI agent can draft a marketing plan, another can critique it, and a third can refine it based on the feedback. We also discuss how some agents can be tools, like a Google search to gather data, and how an orchestrator agent can manage the entire process, adjusting steps as needed.

Leave me a comment if you have new topics I should be discussing.

Check out my LinkedIn: https://www.linkedin.com/in/donwoodlock/

---

YouTube Timestamps
0:00 – 0:20 Welcome
0:21 – 0:50 Introduction to the concept of Agentic AI
0:51 – 3:50 Explanation of how Agentic AI works
3:50 – 4:08 Advertisement plug-in
4:08 – 5:20 Example of using compound LLM’s
5:21 – 5:55 Why you should use a compound LLM approach
5:57 – 6:45 Best way to train and use LLM’s for optimal outcome
6:45 – 7:40 How to think of LLM as agents
7:41 – 10:05 Not every agent needs to be an LLM
10:06 - 10:50 Possibility of having an orchestrator agent
10:51 – 12:50 How to use these agents
12:51 – 13:26 Closing remarks

---

ABOUT INTERSYSTEMS
Established in 1978, InterSystems Corporation is the leading provider of data technology for extremely critical data in healthcare, finance, and logistics. It’s cloud-first data platforms solve interoperability, speed, and scalability problems for large organizations around the globe. InterSystems Corporation is ranked by Gartner, KLAS, Forrester and other industry analysts as the global leader in Data Access and Interoperability. InterSystems is the global market leader in Healthcare and Financial Services.

Website: https://www.intersystems.com/
Youtube: https://www.youtube.com/@InterSystemsCorp
LinkedIn: https://www.linkedin.com/company/intersystems/
Twitter: https://twitter.com/InterSystems

#agenticai #aiagents #LLM

🚀 Complete Claude Code Resources & Course: https://skool.com/scrapes
Don't miss the next build - https://www.youtube.com/@simon....scrapes?sub_confirma
Grab the full resources for this video here (free): https://scrapeshq.notion.site/....Every-Level-of-Claud

Think you're getting the most out of Claude Code? You're probably just scratching the surface. In this video, we break down the 7 levels of mastery, guiding you from basic prompting all the way to building fully autonomous systems. Stop the trial-and-error and start unlocking Claude Code's true potential today.

00:00 - Every Level of Claude Code Explained in 39 Minutes
00:41 - Level 1: The One Thing You Need To Know
03:25 - Level 2: Personalizing CLAUDE for better responses
10:25 - Level 3: Slash Commands, Skills & Hooks - Repeatability
21:21 - Level 4: Connecting Claude Code to Your Apps (MCPs)
26:18 - Level 5: Move from Executor to Supervisor
29:34 - Level 6: Agent Teams
35:57 - Level 7: Fully Autonomous Systems


#claudecodetutorial #masterclaudecode #claudecode

#BestOfVocalDeepHouse #RelaxingMusic #HouseMusic2024

Mega Hits 2024 🌱 The Best Of Vocal Deep House Music Mix 2024 🌱 Summer Music Mix 2024 #136
Mega Hits 2024 🌱 The Best Of Vocal Deep House Music Mix 2024 🌱 Summer Music Mix 2024 #136
Mega Hits 2024 🌱 The Best Of Vocal Deep House Music Mix 2024 🌱 Summer Music Mix 2024 #136

@ImagineDeep68 @rammor @sensualdeep82 @raylefauneee-THR-Music

✔️Submit music: https://spoti.fi/2TJ4Dyj
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🎶Music By :

🌿Follow Deep Disco Records
➤https://www.youtube.com/@DeepdiscoRecords
➤https://www.deepdiscomusic.com

00:00:00 | 1. Ace of Base - Beautiful Life (Mentol Remix)
00:02:42 | 2. Zonoma & Sara Farell - Somebody Else
00:06:00 | 3. Sistek - Pitfalls (feat Tudor & Amy J Pryce)
00:09:13 | 4. Shoby - Dance Monkey (Remix)
00:12:14 | 5. Diamonds (Housenick Remix) - Tommy , Pete Bellis
https://youtu.be/e7osfyzMRWs?si=r-L32KsHluLsf3LV
00:17:34 | 6. Deserve It - Housenick
https://youtu.be/Yjr3dPOkNSA?si=savlusDq5oULSj5n
00:21:37 | 7. Don't Close Your Eyes - Millios
https://youtu.be/JOI7a8s9Too?si=JGBC8jqG90F25eGu
00:26:41 | 8. Heaven - Paul Lock
https://youtu.be/qYKktoJdhLc?si=y4HYuMJ4qjaD8AUq
00:32:42 | 9. Lead The Way - NICCKO
https://youtu.be/xpXl_Sb65hg
00:38:04 | 10. My Truth - Housenick
https://youtu.be/1xUdx8dFXqA?si=tqkEguKFM8epEZwz
00:43:43 | 11. Peace In Me - Nando Fortunato
https://youtu.be/gas5I0KyZT4?si=K7LzvcP0q7_t9-Go
00:48:49 | 12. Time Of My Life - NICCKO
https://youtu.be/43jnVkm-NZQ?si=wwXEZsLNQCaq35fX
00:54:01 | 13. Without You (Original Mix) - Housenick
https://vibe.deepdiscomusic.com/ddr296
00:57:57 | 14. Break Away - Costa Mee
https://youtu.be/qBN05pOS82w?si=LBG5NVK5Gyei4EE8
01:01:37 | 15. To Love Again - Nando Fortunato
https://youtu.be/qH_1Irp7nsE?si=MWGhCg9r8YNhgMoo
01:05:50 | 16. Paradise - Pete Bellis & Tommy, Costa Mee
https://youtu.be/FJpiLy1iaQY?si=cNc-o48HoXpFaw9D
01:10:01 | 17. Infinity Heart (Marc Philippe Remix) - Nando Fortunato
https://vibe.deepdiscomusic.com/dancehouse
01:13:20 | 18. Dance In The Rain - Tommy , Marc Philippe, Pete Bellis
https://youtu.be/c2HxC8ycU3w?si=6E-zTXblmTKhgl4T

📷 Picture credit:
@unknown (if you know, please share the info with us).

♦ If any manufacturer, record label, artist or photographer has trouble uploading music or videos, please contact us and we will delete your work immediately. Thanks! ♦ We try to find the best and most interesting song for you! We hope to make your day more beautiful with the music we share! Peace, love and music. I am also a music producer, I am working on this project!


🚫 If you have any problem with copyright issues, or question please do not report me, take your time to contact us via mail, and we will respond within 48h - 💌 [email protected] 💌

Want to get resources from this livestream? Sign up here so I can email them to you: https://www.lonelyoctopus.com/workshop

🤝 Business Inquiries: https://tally.so/r/mRDV99

🖱️Links mentioned in video
========================

🔗Affiliates
========================
My SQL for data science interviews course (10 full interviews):
https://365datascience.com/lea....rn-sql-for-data-scie

365 Data Science:
https://365datascience.pxf.io/WD0za3 (link for 57% discount for their complete data science training)

Check out StrataScratch for data science interview prep:
https://stratascratch.com/?via=tina

🎥 My filming setup
========================
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💡 lights: https://amzn.to/3LmOhqk

⏰Timestamps
========================
00:00 intro

📲Socials
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instagram: https://www.instagram.com/hellotinah/
linkedin: https://www.linkedin.com/in/tinaw-h/
discord: https://discord.gg/5mMAtprshX

🎥Other videos you might be interested in
========================
How I consistently study with a full time job:
https://www.youtube.com/watch?v=INymz5VwLmk

How I would learn to code (if I could start over):
https://www.youtube.com/watch?v=MHPGeQD8TvI&t=84s

🐈‍⬛🐈‍⬛About me
========================
Hi, my name is Tina and I'm an ex-Meta data scientist turned internet person!

📧Contact
========================
youtube: youtube comments are by far the best way to get a response from me!
linkedin: https://www.linkedin.com/in/tinaw-h/
email for business inquiries only: [email protected]

========================
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MIT 18.642 Topics in Mathematics with Applications in Finance, Fall 2024
Instructors: Vasily Strela, Jake Xia, and Peter Kempthorne
View the complete course: https://ocw.mit.edu/courses/18....-642-topics-in-mathe
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

This video provides an introductory overview of a course combining mathematical theory and real-world financial applications, featuring lectures by academics and industry experts. The instructors emphasize the practical use of mathematics in finance, covering topics like bond math, portfolio optimization, and machine learning, while utilizing tools such as RStudio Cloud for data analysis. Additionally, the course includes guest speakers from prominent financial institutions, offering students exposure to cutting-edge quantitative finance concepts and industry practices.

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.

Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng discusses the topic of reinforcement learning, focusing particularly on continuous state MDPs, discretization, and policy and value iterations.

This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include supervised learning, unsupervised learning, learning theory, reinforcement learning and adaptive control. Recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing are also discussed.

Complete Playlist for the Course:
http://www.youtube.com/view_pl....ay_list?p=A89DCFA6AD

CS 229 Course Website:
http://www.stanford.edu/class/cs229/

Stanford University:
http://www.stanford.edu/

Stanford University Channel on YouTube:
http://www.youtube.com/stanford

Master the HTTP networking protocol by completing over 80 coding exercises and quizzes in JavaScript. Once you’ve learned it all, we’ll build a real web crawler using Node.js to put all the concepts into practice.

HTTP is the backbone of the modern web, and in this course we’ll do a deep dive into all of the fundamentals you’ll need to know to master web networking. We’ll use the Fetch API to interact with a live RESTful server in order to connect the different components of a video game.

💻 Code: https://github.com/bootdotdev/....fcc-learn-http-asset

🔗 Follow this course interactively on Boot.dev: https://boot.dev/learn/learn-http

✏️ Lane Wagner created this course.
Boot.dev: https://boot.dev
Lane on Twitter: https://twitter.com/wagslane
Lane’s YouTube: https://www.youtube.com/@bootdotdev
New to JavaScript? Beginner course: https://boot.dev/learn/learn-javascript

⭐️ Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:03:32) Ch 1 - Why HTTP
⌨️ (0:27:31) Ch 2 - DNS
⌨️ (0:48:11) Ch 3 - URIs and URLs
⌨️ (1:16:21) Ch 4 - Async JavaScript
⌨️ (1:49:48) Ch 5 - Errors in JS
⌨️ (2:04:54) Ch 6 - HTTP Headers
⌨️ (2:21:04) Ch 7 - JSON
⌨️ (2:41:09) Ch 8 - HTTP Methods
⌨️ (3:17:01) Ch 9 - URL Paths
⌨️ (3:36:33) Ch 10 - HTTPS security
⌨️ (3:48:24) Proj - Setup Dev Environment
⌨️ (3:51:28) Proj - Hello World
⌨️ (3:56:29) Proj - Normalize URLs
⌨️ (4:11:05) Proj - URLs from HTML
⌨️ (4:27:49) Proj - The main.js file
⌨️ (4:33:10) Proj - Using Fetch
⌨️ (4:45:16) Proj - Recursively crawling the web
⌨️ (4:55:33) Proj - Print an SEO report
⌨️ (5:06:59) Proj - Conclusion
⌨️ (5:08:04) Congratulations

Documentation used:
Fetch API: https://developer.mozilla.org/....en-US/docs/Web/API/F
URL constructor: https://developer.mozilla.org/....en-US/docs/Web/API/U
Fetch Rseponse: https://developer.mozilla.org/....en-US/docs/Web/API/R

🎉 Thanks to our Champion and Sponsor supporters:
👾 Nattira Maneerat
👾 Heather Wcislo
👾 Serhiy Kalinets
👾 Erdeniz Unvan
👾 Justin Hual
👾 Agustín Kussrow
👾 Otis Morgan

--

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

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

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

A friendly explanation of how computer recognize images, based on Convolutional Neural Networks.
All the math required is knowing how to add and subtract 1's. (Bonus if you know calculus, but not needed.)
For a brush up on Neural Networks, check out this video: https://www.youtube.com/watch?v=BR9h47Jtqyw

For a code implementation, check out this repo:
https://github.com/luisguiserr....ano/manning/tree/mas

0:00 Introduction
0:22 Simple World
1:05 Keyboard
1:33 Image recognition software
4:39 Image Recognition Classifier
6:12 Artificial Intelligence
8:47 Gradient Descent
10:26 Slightly More Complex World
11:47 Previous Knowledge
24:27 Convolutional Neural Network
28:27 Advanced World

A quick look at CBOW and how it looks like it in code. I explained how this model works in the previous example so check that out before you look at this one to get a better understanding.

Timestamps:
0:00 - Introduction
0:48 - Imports
0:53 - CBOW model
5:10 - Example of how to train it
8:52 - Ending

🔥Post Graduate Program in Data Analytics: https://www.simplilearn.com/pgp-data-analytics-certification-training-course?utm_campaign=DataAnalytics-OOWAk2aLEfk&utm_medium=DescriptionFirstFold&utm_source=youtube
This Excel Data Analytics Full Course video will help you understand the various crucial functions available in Excel, such as lookup, H lookup, sumif/s, counif/s, if error, and others. Finally, you will see how to use the Data Analysis Toolpak to perform various data analysis operations. So, let's begin.

00:00:00 Basic of excel data analysis
00:04:20 Lookup & functions in excel data analysis
01:37:58 Conditional formating in excel data analysis
01:54:30 Data validation in excel data analysis
02:36:30 Sorting and filtering in excel data analysis
03:23:55 Data analysis using toolpak in excel data analysis

Dataset Link: https://drive.google.com/drive..../folders/1U8CF0Xx3Ni

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

⏩ Check out the Business Analytics tutorial videos: https://bit.ly/3hQFfDP

#DataAnalyticsInExcel #DataAnalyticsInExcelFullCourse #DataAnalyticsWithExcel #DataAnalyticsUsingExcel #DataAnalyticsCourse #DataAnalyticsCourseForBeginners #ExcelForDataAnalysis #ExcelForBeginners #ExcelBasicsForBeginners #ExcelTutorial #ExcelTutorialForBeginners #BusinessAnalystCourse #BusinessAnalyst #BusinessAnalytics #Simplilearn

What is Microsoft Excel?
Excel is one of the best applications available for creating spreadsheets to crunch numbers and dashboard reports and storing and administering data. This software first appeared on the scene back in 1987, and since then it has grown to become one of the most popular pieces of software for home or business. Excel can be used for data entry to store data in the form of a table, such as recording your daily expenses or business expenditure. It can also be used for inventory management.

✅ Professional Certificate 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.

✅ Key Features:

- Professional Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
- 8X higher live interaction in live online classes by industry experts
- Capstone from 3 domains and 14+ Data Analytics Projects with Industry datasets from Google PlayStore, Lyft, World Bank etc.
- Master Classes delivered by Purdue faculty and IBM experts
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Resume preparation and LinkedIn profile building
- 1:1 mock interview
- Career accelerator webinars

✅ Skills Covered

- Data Analytics
- Statistical Analysis using Excel
- Data Analysis Python and R
- Data Visualization Tableau and Power BI
- Linear and logistic regression modules
- Clustering using kmeans
- Supervised Learning

Learn more at: https://www.simplilearn.com/pgp-data-analytics-certification-training-course?utm_campaign=DataAnalytics-OOWAk2aLEfk&utm_medium=DescriptionFirstFold&utm_source=youtube

For more information about Simplilearn’s courses, visit:
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In this video I show you how to setup and install GPT4All and create local chatbots with GPT4All and LangChain! Privacy concerns around sending customer and organizational data to OpenAI APIs is a huge issue in AI right now but using local models like GPT4All, LLaMa, Alpaca etc can be a viable alternative.

I did some research and figured out how to make your own version of ChatGPT trained on your own data (PDFs, docs etc) using only open source models like GPT4All which is based on GPT-J or LLaMa depending on the version you use. LangChain has great support for models like these so in this video we use LangChain to integrate LLaMa embeddings with GPT4All and a FAISS local vector database to store out documents.

My AI Consulting Services 👋🏼
Want to speak with me about your next big project? Book here:
https://calendly.com/liamottley/consulting-call

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My Links 🔗
👉🏻 Subscribe: https://www.youtube.com/channe....l/UCui4jxDaMb53Gdh-A
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👉🏻 Instagram: https://instagram.com/liamottley

Mentioned in the video:
Code: https://github.com/wombyz/gpt4....all_langchain_chatbo
GPT4ALL (Pre-Converted):
https://huggingface.co/mrgaang..../aira/blob/main/gpt4
Embedding Model:
https://huggingface.co/Pi3141/....alpaca-native-7B-ggm
Mac User Troubleshooting: https://docs.google.com/docume....nt/d/1JDMBTOjbRtJo49

Timestamps:
0:00 - What is GPT4All?
2:28 - Setup & Install
7:13 - LangChain + GPT4All
11:42 - Custom Knowledge Query
19:42 - Chatbot App
24:19 - My Thoughts on GPT4All

About Me 👋🏼
Hi! My name is Liam Ottley and I’m an AI developer and entrepreneur, founder of my own AI development company: Morningside AI (https://morningside.ai). You’ve found my YouTube channel where I help other entrepreneur’s wrap their heads around AI with tutorials on how to get started with building AI apps!

With developments in AI moving so fast, I’m constantly working on my own projects and those of clients and sharing my learnings with my viewers 2-3x per week.

I don’t have anything to sell you, my only hope is that one day some of you will learn enough from my videos to see an exciting opportunity in the AI space and want to work with my development company to make it a reality.

MIT 15.773 Hands-On Deep Learning Spring 2024
Instructor: Rama Ramakrishnan
View the complete course: https://ocw.mit.edu/courses/15....-773-hands-on-deep-l
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

Introduction and overview of the course covering the history and background of the field.

License: Creative Commons BY-NC-SAMore information at https://ocw.mit.edu/termsMore courses at https://ocw.mit.eduSupport 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.

In this video we do a paper walk through of the GCN (Graph Convolutional Network) paper that is the most cited and one of the impactful in graph neural networks. We understand how they derived it and how it works in detail.

Big thanks to MakinaRocks for sponsoring this video, and I encourage you to check out Link which is a jupter lab extension they have developed to make notebooks more intuitive and easier to use. A few of the features I’ve found useful are:
1️⃣ Caching result from running cells in notebooks to avoid re-running them
2️⃣ Visualizing cell dependencies
3️⃣ Integrated version control

Check it out⬇️
https://bit.ly/3F4COvv

Link Demo Video 👉 https://youtu.be/uM2uPG-1eQQ
Link Documentation 👉https://makinarocks.gitbook.io/link/

Timestamps:
0:00 - Introduction
1:00 - Sponsored Segment: Link
2:09 - Abstract and overview
4:13 - Introduction to the problem
8:53 - How GCNs work
13:47 - Theory of GCN derivation
21:25 - GCN Node classification example
24:33 - Conclusions & Results
25:13 - Ending thoughts

#link #gcn

We build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3. We talk about connections to ChatGPT, which has taken the world by storm. We watch GitHub Copilot, itself a GPT, help us write a GPT (meta :D!) . I recommend people watch the earlier makemore videos to get comfortable with the autoregressive language modeling framework and basics of tensors and PyTorch nn, which we take for granted in this video.

Links:
- Google colab for the video: https://colab.research.google.....com/drive/1JMLa53HDu
- GitHub repo for the video: https://github.com/karpathy/ng-video-lecture
- Playlist of the whole Zero to Hero series so far: https://www.youtube.com/watch?v=VMj-3S1tku0&list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ
- nanoGPT repo: https://github.com/karpathy/nanoGPT
- my website: https://karpathy.ai
- my twitter: https://twitter.com/karpathy
- our Discord channel: https://discord.gg/3zy8kqD9Cp

Supplementary links:
- Attention is All You Need paper: https://arxiv.org/abs/1706.03762
- OpenAI GPT-3 paper: https://arxiv.org/abs/2005.14165
- OpenAI ChatGPT blog post: https://openai.com/blog/chatgpt/
- The GPU I'm training the model on is from Lambda GPU Cloud, I think the best and easiest way to spin up an on-demand GPU instance in the cloud that you can ssh to: https://lambdalabs.com . If you prefer to work in notebooks, I think the easiest path today is Google Colab.

Suggested exercises:
- EX1: The n-dimensional tensor mastery challenge: Combine the `Head` and `MultiHeadAttention` into one class that processes all the heads in parallel, treating the heads as another batch dimension (answer is in nanoGPT).
- EX2: Train the GPT on your own dataset of choice! What other data could be fun to blabber on about? (A fun advanced suggestion if you like: train a GPT to do addition of two numbers, i.e. a+b=c. You may find it helpful to predict the digits of c in reverse order, as the typical addition algorithm (that you're hoping it learns) would proceed right to left too. You may want to modify the data loader to simply serve random problems and skip the generation of train.bin, val.bin. You may want to mask out the loss at the input positions of a+b that just specify the problem using y=-1 in the targets (see CrossEntropyLoss ignore_index). Does your Transformer learn to add? Once you have this, swole doge project: build a calculator clone in GPT, for all of +-*/. Not an easy problem. You may need Chain of Thought traces.)
- EX3: Find a dataset that is very large, so large that you can't see a gap between train and val loss. Pretrain the transformer on this data, then initialize with that model and finetune it on tiny shakespeare with a smaller number of steps and lower learning rate. Can you obtain a lower validation loss by the use of pretraining?
- EX4: Read some transformer papers and implement one additional feature or change that people seem to use. Does it improve the performance of your GPT?

Chapters:
00:00:00 intro: ChatGPT, Transformers, nanoGPT, Shakespeare
baseline language modeling, code setup
00:07:52 reading and exploring the data
00:09:28 tokenization, train/val split
00:14:27 data loader: batches of chunks of data
00:22:11 simplest baseline: bigram language model, loss, generation
00:34:53 training the bigram model
00:38:00 port our code to a script
Building the "self-attention"
00:42:13 version 1: averaging past context with for loops, the weakest form of aggregation
00:47:11 the trick in self-attention: matrix multiply as weighted aggregation
00:51:54 version 2: using matrix multiply
00:54:42 version 3: adding softmax
00:58:26 minor code cleanup
01:00:18 positional encoding
01:02:00 THE CRUX OF THE VIDEO: version 4: self-attention
01:11:38 note 1: attention as communication
01:12:46 note 2: attention has no notion of space, operates over sets
01:13:40 note 3: there is no communication across batch dimension
01:14:14 note 4: encoder blocks vs. decoder blocks
01:15:39 note 5: attention vs. self-attention vs. cross-attention
01:16:56 note 6: "scaled" self-attention. why divide by sqrt(head_size)
Building the Transformer
01:19:11 inserting a single self-attention block to our network
01:21:59 multi-headed self-attention
01:24:25 feedforward layers of transformer block
01:26:48 residual connections
01:32:51 layernorm (and its relationship to our previous batchnorm)
01:37:49 scaling up the model! creating a few variables. adding dropout
Notes on Transformer
01:42:39 encoder vs. decoder vs. both (?) Transformers
01:46:22 super quick walkthrough of nanoGPT, batched multi-headed self-attention
01:48:53 back to ChatGPT, GPT-3, pretraining vs. finetuning, RLHF
01:54:32 conclusions

Corrections:
00:57:00 Oops "tokens from the _future_ cannot communicate", not "past". Sorry! :)
01:20:05 Oops I should be using the head_size for the normalization, not C

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
This Edureka video on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐫𝐚𝐬𝐡 𝐂𝐨𝐮𝐫𝐬𝐞 will explain what ChatGPT is all about. In this ChatGPT tutorial, you will learn about how ChatGPT works and the language model that ChatGPT uses.

ChatGPT is an artificial intelligence chatbot developed by OpenAI and launched in November 2022. It is built on top of OpenAI's GPT-3 family of large language models and has been fine-tuned using both supervised and reinforcement learning techniques.

📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟒 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢
⏩ NEW Top 10 Technologies To Learn In 2024 - https://www.youtube.com/watch?v=vaLXPv0ewHU

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🔵 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3Ov52lT

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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/


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🔥Purdue - Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=W7Yrx_IdIiY&utm_medium=DescriptionFirstFold&utm_source=Youtube
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🔥Advanced Executive Program In Applied Generative AI - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=W7Yrx_IdIiY&utm_medium=DescriptionFirstFold&utm_source=Youtube

This Gen AI Full Course video by simplilearn helps us learn everything about Generative AI. The Introduction to Gen AI Full Course covers key topics such as What is AI and How it Works, the Evolution of AI, and a Roadmap to Become a Gen AI Engineer, along with advanced subjects like Generative Adversarial Tutorial, Transformers in AI, Langchain, ML Projects for Resume, and Top 10 AI Technologies, including deep dives into OpenAI ChatGPT-01 Model, LLM Benchmarking, and AI Career Opportunities.

Following are the topics covered in the Gen AI Full Course:

00:00:00 Introduction to Gen AI Full Course
00:08:08 Introduction to What is AI and How it works
00:08:53 What is Gen AI
00:19:32 Roadmap to become a Gen AI Engineer
00:35:11 AI Trends for future
00:36:31 Evolution of AI
01:00:50 Open ai chatgpt o1 model
01:02:40 AI Carrer opportunities
01:10:03 Top 10 AI Technologies
01:25:03 Deep Learning
01:33:20 Search GPT
01:35:35 Langchain
01:48:06 ML Projects for resume
02:50:29 Generative Adversarial Tutorial
02:59:51 What are Gans
03:00:52 Transformers in AI
03:13:21 LSTM
03:14:36 Gen Ai vs AI
03:23:39 Introduction to LLM
04:24:52 What is ML
05:21:24 ML Tutorial for beginners
07:26:47 Reinforcement Learning
08:56:26 Recurrent Neural Network
09:16:17 CHatgpt analyse
09:25:10 LLM Benchmarkeing
10:15:53 Hugging Face and its tutorial

✅ What is Gen AI?
Generative artificial intelligence, also known as generative AI or gen AI for short, is a type of artificial intelligence (AI) that can create new content and ideas, including conversations, stories, images, videos, and music. It can learn human language, programming languages, art, chemistry, biology, or any complex subject matter. It reuses what it knows to solve new problems.

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

⏩ Check out More AI Videos By Simplilearn: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULyr_

#generativeai #genai #ai #machinelearning #llm #simplilearn #2024

➡️ About Professional Certificate Program in Generative AI and Machine Learning

The Generative AI and Machine Learning course enriches your career journey with comprehensive coverage of machine learning, deep learning, NLP, generative AI, reinforcement learning, computer vision, and more. Combining theory with hands-on practice, it offers live virtual sessions, projects with integrated labs, and masterclasses by IIT Guwahati faculty.

Key Features

✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
✅ Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
✅ Opportunity to earn an Executive Alumni Status from E&ICT Academy, IIT Guwahati
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✅ IITG AI: Program Induction
✅ IITG AI: Programming Fundamentals
✅ IITG AI: Python for Data Science (IBM)
✅ IITG AI: Applied Data Science with Python
✅ IITG AI: Machine Learning
✅ IITG AI: Deep Learning with TensorFlow (IBM)
✅ IITG AI: Deep Learning Specialization
✅ IITG AI: Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ IITG AI: Advanced Generative AI

Skills Covered

✅ Generative AI
✅ Prompt Engineering
✅ Chatbot Development
✅ Supervised and Unsupervised Learning
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Machine Learning Algorithms
✅ Speech Recognition
✅ Statistics

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CORRECTION: at 13:41, the probability is 6.1e-5 and not 4.8e-4 (however, the entropy is 1.75, which is correct). Thank you @dlyChimi!

Learn Shannon entropy and information gain by playing a game consisting in picking colored balls from buckets.

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Accompanying blog post: https://medium.com/p/5810d35d54b4/

0:00 Shannon Entropy and Information Gain
2:22 What ball will we pick?
4:33 Quiz
5:06 Question
5:14 Game
7:17 Probability of Winning
7:45 Products
11:00 What if there are more classes?
12:34 Sequence 2
13:44 Sequence 3
14:57 Naive Approach
15:34 Sequence 1
19:44 General Formula

What exactly is Agentic AI? In this video, we will go through an extremely simple explanation of Agentic AI. We will compare Agentic AI systems with Workflows that use LLMs but are not agentic in nature.

00:00 Introduction
00:13 RAG Based AI System
01:06 Tool Augmented AI System
02:08 Agentic AI System
08:02 Agentic AI Apps with Code
09:31 Low Code Agentic AI
11:16 AI Agent vs Agentic AI
11:42 Gen AI vs Agentic AI

Anthropic agent guide: https://www.anthropic.com/engi....neering/building-eff
RAG and tool ammended AI system project 1: https://youtu.be/CO4E_9V6li0?si=4BhXW9c6HnPC2uww
RAG and tool ammended AI system project 2: https://youtu.be/jLM6n4mdRuA?si=oKer2d5eyixiTgF5
Agno reasoning agent: https://docs.agno.com/reasonin....g/reasoning-agents#r

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If you're prompting Claude Code from scratch every time, you're working way too hard. I was too — until I figured this out.

Claude Code skills are the most underleveraged feature in AI right now. This video walks through the folder workflow — a dead-simple pattern for using AI tools on any kind of work, not just software — and then shows how to turn that workflow into a skill that your AI remembers permanently. Two skills are built from scratch on camera: a weekly meal planner that tracks what your family likes, and a personal people directory that works from anywhere. No templates. No downloads. Just a conversation.

If you've been using ChatGPT, Claude, or any AI tool and feel like you keep re-explaining yourself, this is the video that fixes that. Whether you're a developer looking to level up Claude Code or someone who's never written a line of code but wants AI to actually work for your life — meal planning, meeting notes, contacts, anything — this covers the pattern and the permanence. Especially relevant if you've heard about Claude Code skills but haven't built one yet.

Claude Code VS Code Extension: https://marketplace.visualstud....io.com/items?itemNam

#ClaudeCode #AISkills #AI #Productivity #AICoding
00:00 - Intro
01:13 - Meeting Transcripts
03:46 - Image Processor
04:25 - Meal Planner
05:34 - But ... one-shots?
06:08 - Not with Skills!
07:07 - Now, what is a skill?
07:29 - Let's try it!
08:14 - One more time... huh?
10:13 - A PEEPS Skill
11:06 - Local vs. Global?
12:13 - AI didn't fully listen?
14:28 - And, it's that easy