Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng lectures on principal component analysis (PCA) and independent component analysis (ICA) in relation to unsupervised machine learning.

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

Photoshop has received many updates over the years, but nothing has added a powerful feature. With the new Premiere Pro beta, you can now officially use Adobe Firefly in Photoshop, opening tons of doors. This is truly next-level and a significant update for the future of Photoshop. This guide shows you how to install and use this latest feature in the beta version of Premiere Pro - I will show you how to install that if you don't already have it.

You can use this AI to (among other things):
- Generate people or objects
- Fill areas or backgrounds to replace parts of a scene or replace it entirely. You can even use AI to select a subject or the background automatically!
- Remove objects, replace objects
- Recolour objects or replace them with something else entirely
- Extend images - This is super powerful. You can take an image and expand it past the borders creating new information.

Most of these have been available in Stable Diffusion for a long time... In fact all of these -- But this is the first time Adobe has release an AI tool this powerful for Photoshop in an official update!

Adobe guide on Generative AI in Photoshop: https://helpx.adobe.com/photos....hop/using/generative
Adobe AI license: https://www.adobe.com/go/adobe....-gen-ai-user-guideli

Timestamps:
0:00 - Explanation
0:22 - Download Photoshop Beta update
1:13 - Enabling Generative AI in Photoshop
2:00 - Replace Background AI
2:34 - Selecting variations
3:07 - Generating more variations
3:40 - Generating objects
4:10 - Extending images
5:15 - Replace objects
6:19 - Removing objects/people
6:35 - Limitations
7:46 - Swapping objects, clothes and more

#Photoshop #AI #StableDiffusion
-----------------------------
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Everything in this video is my personal opinion and experience and should not be considered professional advice. Always do your own research and ensure what you're doing is safe.

Join My English Mindset and transform the way you think and feel about your English: https://bit.ly/3WdR0r1

#chatgpt #ai #openai ChatGPT is a FREE computer program that will change the way you practice English forever. In today’s video, I’ll walk you through how to use OpenAI ChatGPT to enhance your vocabulary, grammar, conversation, exam prep and so much more. It will completely transform the way you practice in ways you wouldn’t believe are possible!

Read my ULTIMATE guide for using Chat GPT for English Learning: https://bit.ly/3H5ApjD

Download my list of prompts for practicing with ChatGPT: https://bit.ly/3XCHOOA

Try OpenAI ChatGPT now: https://chat.openai.com/

Can’t WAIT for you to get started! Don’t miss my ULTIMATE guide for using Chat GPT for English Learning: https://bit.ly/3H5ApjD

Mentioned in the video:
Join my FREE speaking community: https://hadarshemesh.com/in
Convert text to speech: https://www.naturalreaders.com/online/
Practice grammar effectively: https://youtu.be/g-IcEqSEA-w

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Listen to my Podcast 🎧: https://bit.ly/3oYNOCf
Let’s connect on Instagram ♥️: https://bit.ly/2M4Tg2R
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FREE stuff to give you the confidence and fluency boost you need:
🚀Join our community on Facebook and practice https://hadarshemesh.com/in
🚀American Accent crash course: https://hadarshemesh.com/cc
🚀50 of the most mispronounced words in English https://hadarshemesh.com/ms

Free American Pronunciation Guides for:
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🚀Hindi and Urdu speakers https://hadarshemesh.com/hi
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⏱️Check out my SPRINTS - Effective Practice to boost your vocabulary, grammar and pronunciation:
Sprint #1 https://hadarshemesh.com/spr1
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Sprint #3 https://hadarshemesh.com/spr3
Morning Pronunciation Routine https://youtu.be/l69yZ5xabbo

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NEW HERE? 🔥Get started with those helpful lessons:
#1 STRATEGY of how to become FLUENT in English https://youtu.be/0V0WeEnsec0
Want to improve your speaking vocabulary? STOP LEARNING NEW WORDS✋ https://youtu.be/bd6iGLmUssQ
My pronunciation playlist: https://bit.ly/39nh0ub
How to improve your listening skills: https://youtu.be/ezZ-EJm9IRY
Sound like a native - the myth: https://youtu.be/zE5kvQ9TF50
How to stop translating in your head: 5-steps to get stuck LESS and speak FASTER in English https://youtu.be/ZP6Ev1HvK4w
How to stay MOTIVATED when learning ENGLISH https://youtu.be/IAx7X_jvHcU
Do you change your voice when you speak English? Here’s why
https://youtu.be/qFbjwopad7c
American INTONATION - What They don't Teach You in School https://youtu.be/FStyKn4V8cE
10 ways to DESTROY your English Fluency https://youtu.be/36KgqKYdWhY

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
This 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐓𝐮𝐭𝐨𝐫𝐢𝐚𝐥 is intended as a Crash Course on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 for Beginners. 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 has been growing in popularity exponentially. But, 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 is still not known to many people. In this video, I aim to show you the different ways in which you can use 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 for yourself.

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

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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

🔵 DevOps Online Training: http://bit.ly/3VkBRUT
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🔵 GCP Online Training: http://bit.ly/3VkCzS3
🌕 Microservices Online Training: http://bit.ly/3gxYqqv
🔵 Data Science Online Training: http://bit.ly/3V3nLrc
🌕 CEHv12 Online Training: http://bit.ly/3Vhq8Hj
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🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
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🔵 Python Developer Masters Program: http://bit.ly/3EV6kDv
🌕 RPA Developer Masters Program: http://bit.ly/3OteYfP
🔵 Web Development Masters Program: http://bit.ly/3U9R5va
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🔵 Cyber Security Masters Program: http://bit.ly/3U25rNR
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🔵 Automation Testing Engineer Masters Program : http://bit.ly/3AGXg2J
🌕 Python Developer Masters Program : https://bit.ly/3EV6kDv
🔵 Azure Cloud Engineer Masters Program: http://bit.ly/3AEBHzH

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬

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

🔵 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh


📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain
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📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

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

Learn the Swift programming language in this full tutorial for beginners.

In this video, we will go through every modern aspect of Swift as a programming language including, variables, constants, functions, structures, classes, protocols. extensions, asynchronous programming, generics and much more. This video will lay the foundation for learning Swift for those who are not familiar with Swift already.

You can follow along with this video on macOS, Linux and Windows. On Linux and Windows you will need to download the Swift toolchain from https://swift.org and run the examples manually by invoking Swift from Terminal using your favorite code editor such as Visual Studio Code.

✏️ Vandad Nahavandipoor created this course.
Vandad on YouTube: https://youtube.com/c/vandadnp
Vandad on Twitter: https://twitter.com/vandadnp
Vandad on LinkedIn: https://linkedin.com/in/vandadnp

⭐️ Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:06:49) Variables
⌨️ (0:29:46) Operators
⌨️ (0:46:55) If and else
⌨️ (1:05:08) Functions
⌨️ (1:23:58) Closures
⌨️ (1:52:08) Structures
⌨️ (2:17:58) Enumerations
⌨️ (2:59:21) Classes
⌨️ (3:24:51) Protocols
⌨️ (3:47:48) Extensions
⌨️ (4:00:06) Generics
⌨️ (4:32:44) Optionals
⌨️ (4:53:39) Error Handling
⌨️ (5:39:35) Collections
⌨️ (6:17:17) Equality and Hashing
⌨️ (6:38:46) Custom Operators
⌨️ (6:50:53) Asynchronous Programming
⌨️ (7:04:38) Outro

🎉 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

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐞𝐚𝐜𝐭 𝐉𝐒 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐂𝐨𝐮𝐫𝐬𝐞 : https://www.edureka.co/reactjs....-redux-certification (Use code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎")
This Edureka React tutorial on ES5 to ES6 Refactoring will help you understand the current syntax being used in React and what new features you can use in the upgraded version. This video helps you to learn the following topics:
00:00:00 Introduction
00:00:30 Agenda
00:01:45 Introduction to React components
00:02:45 Component Structure using ES5
00:03:46 Rendering a Component
00:05.48 Component Structure in Facebook
00:06:27 Component Structure using ES5
00:08:00 Pros and Cons of ES5 Syntax
00:09:02 Building Our Application
00:09:55 React Components using ES5 Code example
00:17:12 Benefits of ES6
00:19:38 Advantages of ES6
00:24:50 ES5 vs ES6
00:29:19 ES6 restructuring of code example
00:31:26 Building Tic Tac Toe game in React using ES6

🔴 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

🔵 DevOps Online Training: http://bit.ly/3VkBRUT
🌕 AWS Online Training: http://bit.ly/3ADYwDY
🔵 React Online Training: http://bit.ly/3Vc4yDw
🌕 Tableau Online Training: http://bit.ly/3guTe6J
🔵 Power BI Online Training: http://bit.ly/3VntjMY
🌕 Selenium Online Training: http://bit.ly/3EVDtis
🔵 PMP Online Training: http://bit.ly/3XugO44
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🔵 Cybersecurity Online Training: http://bit.ly/3tXgw8t
🌕 Java Online Training: http://bit.ly/3tRxghg
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🌕 Microservices Online Training: http://bit.ly/3gxYqqv
🔵 Data Science Online Training: http://bit.ly/3V3nLrc
🌕 CEHv12 Online Training: http://bit.ly/3Vhq8Hj
🔵 Angular Online Training: http://bit.ly/3EYcCTe

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
🌕 Cloud Architect Masters Program: http://bit.ly/3OvueZy
🔵 Data Scientist Masters Program: http://bit.ly/3tUAOiT
🌕 Big Data Architect Masters Program: http://bit.ly/3tTWT0V
🔵 Machine Learning Engineer Masters Program: http://bit.ly/3AEq4c4
🌕 Business Intelligence Masters Program: http://bit.ly/3UZPqJz
🔵 Python Developer Masters Program: http://bit.ly/3EV6kDv
🌕 RPA Developer Masters Program: http://bit.ly/3OteYfP
🔵 Web Development Masters Program: http://bit.ly/3U9R5va
🌕 Computer Science Bootcamp Program : http://bit.ly/3UZxPBy
🔵 Cyber Security Masters Program: http://bit.ly/3U25rNR
🌕 Full Stack Developer Masters Program : http://bit.ly/3tWCE2S
🔵 Automation Testing Engineer Masters Program : http://bit.ly/3AGXg2J
🌕 Python Developer Masters Program : https://bit.ly/3EV6kDv
🔵 Azure Cloud Engineer Masters Program: http://bit.ly/3AEBHzH

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬

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

🔵 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh


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📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

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

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚'𝐬 𝐃𝐞𝐯𝐎𝐩𝐬 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐂𝐨𝐮𝐫𝐬𝐞 (𝐔𝐒𝐄 𝐂𝐎𝐃𝐄 '𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎'): https://www.edureka.co/devops-....certification-traini
Get Ready for Your DevOps Interview with Edureka's DevOps Interview Questions and Answers! Explore essential topics and tips to ace your DevOps Engineer Interview.
This comprehensive DevOps Tutorial will help you master the key concepts, covering DevOps Interview questions from the beginner level to the advanced level.
Don't miss this complete guide to your DevOps career success!

This DevOps Interview Questions video by Edureka will cover:
✅ 00:00 Introduction
✅ 01:17 What is DevOps?
✅ 01:45 Who are DevOps Engineers?
✅ 02:04 How can you become a DevOps Engineer?
✅ 02:27 Beginner-level DevOps Interview Questions
✅ 08:44 Intermediate-level DevOps Interview Questions
✅ 17:43 Advanced-level DevOps Interview Questions

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

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𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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About the Course

Edureka’s DevOps online training is designed to help you master key tools of DevOps lifecycle like Docker, Puppet, Jenkins, Nagios, GIT, Ansible used by a DevOps Engineer for automating multiple steps in SDLC. During this course, our expert DevOps instructors will help you:

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In this comprehensive exploration of the field of deep learning with Professor Simon Prince who has just authored an entire text book on Deep Learning, we investigate the technical underpinnings that contribute to the field's unexpected success and confront the enduring conundrums that still perplex AI researchers.

Understanding Deep Learning - Prof. SIMON PRINCE [STAFF FAVOURITE]

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Key points discussed include the surprising efficiency of deep learning models, where high-dimensional loss functions are optimized in ways which defy traditional statistical expectations. Professor Prince provides an exposition on the choice of activation functions, architecture design considerations, and overparameterization. We scrutinize the generalization capabilities of neural networks, addressing the seeming paradox of well-performing overparameterized models. Professor Prince challenges popular misconceptions, shedding light on the manifold hypothesis and the role of data geometry in informing the training process. Professor Prince speaks about how layers within neural networks collaborate, recursively reconfiguring instance representations that contribute to both the stability of learning and the emergence of hierarchical feature representations. In addition to the primary discussion on technical elements and learning dynamics, the conversation briefly diverts to audit the implications of AI advancements with ethical concerns.

Pod version (with no music or sound effects): https://podcasters.spotify.com..../pod/show/machinelea

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https://www.linkedin.com/in/si....mon-prince-615bb9165

Get the book now!
https://mitpress.mit.edu/97802....62048644/understandi
https://udlbook.github.io/udlbook/

Panel: Dr. Tim Scarfe -
https://www.linkedin.com/in/ecsquizor/
https://twitter.com/ecsquendor

TOC:
[00:00:00] Introduction
[00:11:03] General Book Discussion
[00:15:30] The Neural Metaphor
[00:17:56] Back to Book Discussion
[00:18:33] Emergence and the Mind
[00:29:10] Computation in Transformers
[00:31:12] Studio Interview with Prof. Simon Prince
[00:31:46] Why Deep Neural Networks Work: Spline Theory
[00:40:29] Overparameterization in Deep Learning
[00:43:42] Inductive Priors and the Manifold Hypothesis
[00:49:31] Universal Function Approximation and Deep Networks
[00:59:25] Training vs Inference: Model Bias
[01:03:43] Model Generalization Challenges
[01:11:47] Purple Segment: Unknown Topic
[01:12:45] Visualizations in Deep Learning
[01:18:03] Deep Learning Theories Overview
[01:24:29] Tricks in Neural Networks
[01:30:37] Critiques of ChatGPT
[01:42:45] Ethical Considerations in AI

References:

#61: Prof. YANN LECUN: Interpolation, Extrapolation and Linearisation (w/ Dr. Randall Balestriero)
https://youtube.com/watch?v=86ib0sfdFtw

Scaling down Deep Learning [Sam Greydanus]
https://arxiv.org/abs/2011.14439

"Broken Code" a book about Facebook's internal engineering and algorithmic governance [Jeff Horwitz]
https://www.penguinrandomhouse.....com/books/712678/br

Literature on neural tangent kernels as a lens into the training dynamics of neural networks.
https://en.wikipedia.org/wiki/....Neural_tangent_kerne

Zhang, C. et al. "Understanding deep learning requires rethinking generalization." ICLR, 2017.
https://arxiv.org/abs/1611.03530

Computer Vision: Models, Learning, and Inference, by Simon J.D. Prince
https://www.amazon.co.uk/Compu....ter-Vision-Models-Le

Deep Learning Book, by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
https://www.deeplearningbook.org/

Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network
https://arxiv.org/abs/2210.00881

Computer Vision: Algorithms and Applications, 2nd ed. [Szeliski]
https://szeliski.org/Book/

A Spline Theory of Deep Networks [Randall Balestriero]
https://proceedings.mlr.press/....v80/balestriero18b/b

DEEP NEURAL NETWORKS AS GAUSSIAN PROCESSES [Jaehoon Lee]
https://arxiv.org/abs/1711.00165

Do Transformer Modifications Transfer Across Implementations and Applications [Narang]
https://arxiv.org/abs/2102.11972

ConvNets Match Vision Transformers at Scale [Smith]
https://arxiv.org/abs/2310.16764

Dr Travis LaCroix (Wrote Ethics chapter with Simon)
https://travislacroix.github.io/

CORRECTION: At 10:56 we shouldn't divide by 4 to get the covariance, we should divide by 1+1+1+1/3, which is 10/3. That means the covariances are the following:
Var(x) = 1.056
Var(y) = 0.864
Cov(x,y) = 0.768
(Thank you Shivkumar Pippal!)

Mean, variance, covariance, and the covariance matrix for a dataset and a weighted dataset.

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0:00 Introduction
0:09 The covariance matrix
2:22 Average
3:23 X-variance
5:06 Problem: Same variances
7:59 Formulas
10:30 Center points

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In this video, I break down building an AI Agent so simply even a 10-year-old could do it! I’ll walk you through what an AI agent is and how to build a basic email agent in n8n that can automatically send emails for you.

No coding experience? No problem! I’ll guide you step-by-step, showing just how quick and easy you can get this set up. By the end of this video, you’ll have your very own email-sending AI agent up and running in no time.


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WATCH NEXT:
https://youtu.be/u2Tuu02r7QI

TIMESTAMPS
00:00 Components of an AI Agent
03:50 Step 1: Chat Input
04:18 Step 2: Adding the Brain
05:49 Step 3: Adding Memory
07:45 Step 4: Adding Send Email Tool
10:21 Step 5: Adding Instructions (System Message)
12:04 Testing the Email Agent
13:43 Reviewing the Agent Log
15:00 Step 6: Adding Contact Database Tool
16:57 Final Test
18:05 Final Thoughts

Gear I Used:
Camera: Razer Kiyo Pro
Microphone: HyperX SoloCast
Background Music: https://www.youtube.com/watch?v=Q7HjxOAU5Kc&t=0s

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

October 14, 2025
This lecture covers adversarial robustness and generative models.

To learn more about enrolling in this course, visit: https://online.stanford.edu/co....urses/cs230-deep-lea

To follow along with the course schedule and syllabus, visit: https://cs230.stanford.edu/syllabus/

More lectures will be published regularly.
View the playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

Andrew Ng
Founder of DeepLearning.AI
Adjunct Professor, Stanford University’s Computer Science Department

Kian Katanforoosh
CEO and Founder of Workera
Adjunct Lecturer, Stanford University’s Computer Science Department

I sit down with Remy Gaskell to break down how anyone can build AI agents to run entire departments of their business. Remy walks through the core concepts: agent loops, context files, memory, MCP tool connections, and skills. We put everything together by building a fully functional executive assistant live on screen. This is a beginner-friendly crash course that covers Claude Code, Codex, Cowork, Antigravity, Manus, and OpenClaw, showing that once you understand how to "drive," you can jump into any agent platform. By the end, listeners know exactly how to set up markdown-based context files, connect their everyday tools, and create reusable skills that compound over weeks and months.

Timestamps
00:00 – Intro
01:35 – Agents vs Chat
03:22 – The Agent Loop
05:46 – How Agents work
06:39 – Demoing Agents (Claude Code, Codex, Antigravity)
08:52 – Security and Agent Permissions
10:43 – Comparing Results Across Three Platforms
13:57 – Startup Idea: Cold Email Website Offer
14:50 – Folder Structure and Department-Based Agents
15:52 – Onboarding an Agent Like a Real Employee
17:05 – Voice-to-Text With Monologue and WhisperFlow
18:04 – Chat Memory vs. Agent Memory
19:34 – Building the agents md
22:20 – Context Engineering Over Prompt Engineering
24:29 – How Memory Compounds and Reduces Errors
30:27 – How Big Can memory md Get?
31:43 – Connecting Tools via MCP (Model Context Protocol)
34:49 – Working in Claude Code for High-Value Tasks
37:09 – Why the Real Value Is in Stacking, Not Summarizing
40:04 – What Are Skills? (SOPs for AI)
43:08 – Creating Skills
48:36 – Real-World Example: Ads Analyst Skill: 4-Hour Process in Minutes
50:37 – Chaining Skills together
52:01 – Real-World Example: Automated Car Search
53:34 – OpenClaw and Migrating Agents to More Autonomous Platforms
55:19 – Which Platform Should Beginners Start With?
56:28 – Global vs. Project-Level Skills, Context, and MCPs

Key Points

* Agent platforms (Claude Code, Codex, Cowork, Antigravity, Manus, OpenClaw) are all running the same observe-think-act loop under the hood — learning one means you can use any of them.
* The shift from chat to agents requires moving from prompt engineering to context engineering: load the agent with rich context so simple prompts produce excellent results.
* A memory md file creates a self-improving loop where the agent learns preferences across sessions and makes fewer errors over time.
* MCP (Model Context Protocol), built by Anthropic, acts as a universal translator between your agent and every tool it needs — Gmail, Calendar, Stripe, Notion, and more.
* Skills are reusable SOPs packaged as markdown files; once you explain a process once, you can invoke it repeatedly, and they compound as you add three to five per week.
* Scheduled tasks turn skills into automated workflows — morning briefs, car searches, ad library analyses — that run on a cron without any manual trigger.

Numbered Section Summaries

1. The Agent Loop in Action

Remy kicks off with a live demo, sending the same prompt — "build a minimalist portfolio site for Greg Isenberg" — to Claude Code, Codex, and Antigravity simultaneously. All three platforms run the same observe-think-act loop: research the subject, write the code, spin up a preview, and verify the result with a screenshot. The demo makes it tangible that every agent harness is just a different car with the same engine.

2. Onboarding Your Agent Like a Real Employee

Remy shows that without context, an agent asked to "write me a cold email" has no idea who you are or what you sell. The fix is an agents.md (or Claude.md) file — a persistent context document loaded at the start of every session. You fill it with your role, business details, tools, and working preferences, and the result is that a two-word prompt produces a fully informed output.

3. Memory That Compounds

Chat models store memory invisibly in the cloud; agents require you to build it intentionally. Remy adds a memory.md file and a simple instruction in the context file: "When I correct you or you learn something new, update memory.md." Preferences like tone, email sign-offs, and design choices persist across sessions, and errors decrease over time.


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