This video is about the Fast Fourier Transform.

This is the third in a series of videos about Fourier transforms.

- First video: The Discrete Fourier Transform https://www.youtube.com/watch?v=T8XZxR5H04E
- Second video: Detecting Periodicity with the DFT https://youtu.be/bk9VGJNzQM0
- Third video: The Fast Fourier Transform (this one)

Grokking Machine Learning Book:
https://www.manning.com/books/....grokking-machine-lea
40% discount promo code: serranoyt

00:00 Introduction
00:27 The Discrete Fourier Transform
03:01 The Fast Fourier Transform
07:28 The Butterfly

Covariance matrix video: https://youtu.be/WBlnwvjfMtQ
Clustering video: https://youtu.be/QXOkPvFM6NU

A friendly description of Gaussian mixture models, a very useful soft clustering method.

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

0:00 Introduction
0:13 Clustering applications
1:56 Hard clustering - soft clustering
3:36 Step 1: Colouring points
6:10 Step 2: Fitting a Gaussian
10:33 Gaussian Mixture Models (GMM)

Sam Altman, President of Y Combinator, and Dustin Moskovitz, Cofounder of Facebook and Asana, kick off the How to Start a Startup Course. Dustin discusses Why to Start a Startup and Sam introduces the 4 key components of Starting a Startup: Idea, Product, Team and Execution.
http://www.slideshare.net/Stev....enPham7/lecture-1-ho

Explore Stanford Online courses: https://online.stanford.edu/explore

(March 29, 2010) Stanford professor Robert Sapolsky gave the opening lecture of the course entitled Human Behavioral Biology and explains the basic premise of the course and how he aims to avoid categorical thinking.

Stanford University
http://www.stanford.edu

Stanford Department of Biology
http://biology.stanford.edu/

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

AI Agents are everywhere from automated emails to running deep research, striving to leverage the full power of LLMs. And for many of us, it boils down to one question: To code or not to code? Is the future of AI in the hands of seasoned developers building agents with LangGraph, ADK, Agno? Or with everyone else, using drag & drop in a no-code platform like n8n, Zapier, Make?

In this video, I will discuss which approach wins.

Build your first no code AI agent: https://youtu.be/Jekzc6BM5_w
LangGraph tutorial: https://youtu.be/CnXdddeZ4tQ
CrewAI tutorial: https://youtu.be/G42J2MSKyc8


Do you want to learn technology from me? Check https://resources.codebasics.io/6kp3C8 for my affordable video courses.

Need help building software or data analytics/AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website.

🎥 Codebasics Hindi channel: https://www.youtube.com/channe....l/UCTmFBhuhMibVoSfYo

#️⃣ Social Media #️⃣

🧑‍🤝‍🧑 Discord for Community Support: https://discord.gg/r42Kbuk
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📽️ Hem's Instagram for daily tips: https://www.instagram.com/hemvadivel/
📸 Dhaval's Personal Instagram: https://www.instagram.com/dhavalsays/

🔗 Patreon: https://www.patreon.com/codeba....sics?fan_landing=tru

Next: Your first AI Employee: https://youtu.be/jYbzKYwdy24

In this video, I break down what Agentic AI really is, beyond the hype and buzzwords. While most people think of AI as just chatbots like ChatGPT, the next evolution - Agentic AI - is quietly transforming how we interact with technology.

I explain in simple terms how Agentic AI systems can actually take initiative, complete complex tasks autonomously, and solve problems without constant human guidance. You'll understand the key differences between reactive AI tools and truly agentic systems that can plan, adapt, and achieve goals.

Whether you're a developer, business leader, or just curious about AI's future, this concise explanation gives you the foundation to understand why Agentic AI represents such a significant leap forward in artificial intelligence.

#AgenticAI #ArtificialIntelligence #AIExplained #FutureOfAI #AgentBasedAI #AITechnology #TechTrends #MachineLearning #BusinessAI #AIAgents

In this comprehensive hands-on workshop, Jon Krohn and Ed Donner introduce AI agents, including multi-agent systems. All the essential theory of agentic AI is provided alongside hands-on code demos in Python that feature the critical agent frameworks: MCP, CrewAI and the OpenAI Agents SDK. From design considerations through to practical implementation tips, by completing all four modules in this video, you will have all the knowledge and skills needed to develop and deploy your own multi-agent teams.

The four modules are:
1. Defining Agents (with OpenAI Agents SDK)
2. Designing Agents (with CrewAI)
3. Deploying Agents (with MCP)
4. The Future of Agents

The accompanying slides and code are available in GitHub: github.com/ed-donner/action

Jon Krohn is co-founder and CEO of Y Carrot, a software firm that specializes in designing and implementing agentic AI systems for enterprises. He also serves as ML Practice Fellow at Lightning AI and is the host of SuperDataScience, the data science industry’s most listened-to podcast. He wrote the book Deep Learning Illustrated, an instant #1 bestseller that was translated into seven languages. He lectures at leading universities (Columbia, NYU), keynotes at top global conferences (Web Summit, Collision) and presents content on Bloomberg TV that’s viewed by millions. Jon holds a PhD from Oxford and has been publishing on machine learning in prominent academic journals since 2010.

Ed Donner is renowned for his teaching on LLMs and agentic AI via O'Reilly and Udemy. He’s the co-founder and CTO of Nebula.io, the platform that uses generative AI and other forms of machine learning to source, understand, engage and manage talent. Previously, Ed was the founder and CEO of AI startup untapt, an Accenture Fintech Innovation Lab company that was acquired in 2020. Before that, Ed was a Managing Director at JPMorgan Chase, leading a team of 300 software engineers in Risk Technology across three continents, the culmination of a 15-year technology career on Wall Street. Ed holds a patent for a deep learning matching engine issued in 2023 and a master's in physics from Oxford.

This high-quality footage was shot live during a packed house at the Open Data Science Conference (ODSC) East in Boston on May 14th, 2025. The director of photography was Lucie McCormick and media editor was Mario Pombo.

Two bonus goodies below:

Follow this link to get Ed's 17-hour "Complete Agentic AI Engineering Course" on Udemy at a discounted rate (as well as coupon links to all of his Udemy courses): https://edwarddonner.com/2025/....05/28/connecting-my-

Use this link to skip the waitlist for Lightning AI Studios and get 15 free GPU-compute credits every month: https://lightning.ai/?inviteCo....de=Agentic-AI-worksh

This course, from Rola Dali, PhD, provides a comprehensive overview of agentic AI, defining agents as software entities that use LLMs to perceive environments, make decisions, and execute actions to achieve specific goals. It explores the critical distinction between static workflows and dynamic agentic systems, emphasizing how LLMs serve as a reasoning "brain" to decompose tasks at runtime. Through practical Python demonstrations, the course covers essential components like system prompts, tools, and memory, while also comparing architectural patterns such as Supervisor and Swarm. Finally, the session addresses the future of technology by discussing emerging interoperability protocols like MCP and the shifting paradigms of software development in an AI-driven world.

Slides and Labs: https://github.com/rdali/ML105_Agents

Profile: https://www.linkedin.com/in/roladali/

❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp

⭐️ Contents ⭐️
- 0:00:00 Introduction and Speaker Background
- 0:01:15 A Brief History of Artificial Intelligence (1940s–Present)
- 0:05:43 Traditional Machine Learning vs. Generative AI
- 0:06:35 The Three Pillars of AI: Algorithms, Data, and Compute
- 0:11:08 Specific Tasks vs. General Task Execution
- 0:14:41 Defining Agency and the Spectrum of Autonomy
- 0:18:00 Agentic Milestone Timeline (2017–2026)
- 0:20:31 What is a Generative AI Agent?
- 0:23:04 Agents vs. Workflows: Dynamic Flow vs. Static Paths
- 0:26:18 Pros and Cons of Agentic Systems
- 0:29:59 Patterns and Anti-patterns: When to Use Agents
- 0:32:36 The Core Components of an Agent
- 0:34:55 Choosing the Right LLM for Your Agent
- 0:37:38 Crafting Identity with System Prompts
- 0:39:00 Understanding Memory: Intrinsic, Short-term, and Long-term
- 0:41:26 Enhancing Capabilities with Tools and Actions
- 0:43:09 Hands-on Implementation: From Single LLM Call to Python Agent
- 0:52:18 Adding Memory and History to Your Custom Agent
- 0:54:53 Building Agents with Frameworks (LangChain)
- 0:57:17 The Evolving Landscape of Models and Frameworks
- 1:00:15 Agentic Architectural Patterns: Supervisor vs. Swarm
- 1:01:41 Case Study: Single Agent vs. Supervisor Architecture
- 1:04:48 Deep Dive: Swarm Architecture Performance
- 1:06:08 When to Choose Multi-agent Systems
- 1:09:05 Interface Protocols: MCP, A2A, and AGUI
- 1:12:06 How to Evaluate Agentic Systems (LLM vs. System vs. App)
- 1:13:53 Evaluation Methods: Code-based, LLM-as-a-Judge, and Human
- 1:15:25 Current Challenges: Hallucinations, Cost, and Debugging
- 1:18:15 Real-world Incidents and the AI Incident Database
- 1:21:28 Career Impact: Which Jobs are Most at Risk?
- 1:23:41 Software 3.0: The Evolution of Development Paradigms
- 1:29:00 Weathering the Storm: Strategies for the Future
- 1:33:40 Beyond LLMs: World Models and the Future of AMI
- 1:37:15 Recommended Resources and Closing Thoughts

🎉 Thanks to our Champion and Sponsor supporters:
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In this step-by-step tutorial, I'll show you how to create a powerful AI agent using Microsoft Copilot Studio in Microsoft Copilot 365, with absolutely no code required! This is Part 1 of our AI agent series with Microsoft Copilot Studio.

We'll build "PoochPal," a friendly AI assistant for our demo dog grooming business, "Pooch Haven Spa." You'll learn how to train your bot with your own website data and documents, customize its personality, and set rules for how it responds to customers.

➡️ Watch Part 2: https://youtu.be/sBapFKSwJ6Q
➡️ Learn more about M365 Copilot: https://youtu.be/j5xQn8Pi_Gw

In this video, you'll learn:
🔹 The difference between Copilot Studio in M365 and the full Copilot Studio.
🔹 How to create your first AI agent with a simple prompt.
🔹 How to add knowledge sources like websites and documents (PDF, Word).
🔹 How to customize your agent's icon, tone, and instructions.
🔹 How to test your AI bot to ensure it's accurate and helpful

0:00 Intro: Build Your Own AI Bot
0:45 Accessing Microsoft 365 Copilot
1:31 Difference between Copilot Studio in M365 vs. Copilot Studio
2:03 Create Your First AI Agent with a Simple Prompt
3:20 Add a custom icon to your agent
4:10 Customize Your Agent's Personality & Rules
5:02 Add Knowledge Sources (Websites & Documents)
6:17 Adjust agent capabilities and suggested prompts
6:48 Test Your AI Bot for Accuracy
7:56 Publish and share your agent

🔵 Intellipaat Data Engineering course: https://intellipaat.com/pgp-da....ta-engineering-mit-j
In this Data Engineering Course, you will learn what is Data Engineering, How to Become a Data Engineer, Why Data Engineering is important, What is Big Data Engineering, the Importance of Big Data, the Difference between Data Engineer and Data Scientist, Big Data Engineering, What is Hadoop, Apache Spark Tutorial, AWS Elastic Map Reduce Tutorial, Azure Data Factory Tutorial, Data Engineering Career Roadmap and lot more. This Data Engineer Full Course will help you to understand Data Engineering from scratch.

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🔵 Following topics are covered in this session:
00:00 - Introduction to Data Engineer
1:50:08 - What is Spark?
2:18:02 - Spark's Mllib
3:19:45 - Spark-Hive Integration
3:37:57 - Configuration Options
3:49:35 - What is AWS?
4:46:57 - Azure Data Factory
5:01:30 - Integration Runtime in Azure Data Factory
7:09:55 - Data Engineer Career Path
7:19:22 - Top 50 Data Engineer Interview Questions


🔵 Why Data Engineering is important?
Data engineering helps make data more useful and accessible for consumers of data. To do so, Data engineering must source, transform and analyze data from each system. For example, data stored in a relational database is managed as tables, like a Microsoft Excel spreadsheet. Each table contains many rows, and all rows have the same columns. A given piece of information, such as a customer order, may be stored across dozens of tables.

🔵 Why should you opt for a Data Engineering career?
Data engineers must have specialized skills in creating software solutions around data. At the same time, it’s perhaps unrealistically expected that Data Engineers will be familiar with a breadth of tools and technologies – anywhere from 10 to 30 of them. And these tools are constantly changing.

🔵 Do subscribe to Intellipaat channel & get regular updates on videos: http://bit.ly/Intellipaat

🔵 For more information: Call Our Course Advisors IND: +91-7022374614 US: 1-800-216-8930 (Toll-Free)

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Don't Re-Upload My Videos You Will Get a Copyright Strike Right Away!
Don't Re-Upload My Videos You Will Get a Copyright Strike Right Away!

Please do Like, Comment, and Subscribe to my Channel if you like it.

Artist Name - Viniick
Video - MV Edits
Thumbnail - SM Creation

Social Media:
INSTAGRAM - https://www.instagram.com/viniickmusic/
FACEBOOK - https://www.facebook.com/viniickmusic/

#viniickmusic #arijitsingh #mashups #trending


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©️ DISCLAIMER: This Audio/Video is Strictly meant for Promotional Purposes & Intended to Showcase the Creativity Of the Artist.

As per the 3rd Section of Fair Use guidelines Borrowing small bits of material from an original work is more likely to be considered fair use. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for fair use

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Enjoy and Connected With us....


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3 Cathy's Clown - The Everly Brothers
4 Running Bear - Johnny Preston
5 Teen Angel - Mark Dinning
6 I'm Sorry - Brenda Lee
7 It's Now or Never - Elvis Presley
8 Handy Man - Jimmy Jones
9 Stuck on You - Elvis Presley
10 The Twist - Chubby Checker
11 Everybody's Somebody's Fool - Connie Francis
12 Wild One - Bobby Rydell
13 Greenfields - The Brothers Four
14 What in the World's Come Over You - Jack Scott
15 El Paso - Marty Robbins
16 Alley Oop - The Hollywood Argyles
17 My Heart Has a Mind of Its Own - Connie Francis
18 Sweet Nothin's - Brenda Lee
19 Itsy Bitsy Teenie Weenie Yellow Polka Dot Bikini - Brian Hyland
20 Only the Lonely - Roy Orbison
21 Where or When - Dion and the Belmonts
22 Sixteen Reasons - Connie Stevens
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24 Why - Frankie Avalon
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26 Save the Last Dance for Me - The Drifters
27 Baby (You've Got What It Takes) - Dinah Washington & Brook Benton
28 Sink the Bismarck - Johnny Horton
29 Chain Gang - Sam Cooke
30 Let It Be Me - The Everly Brothers

Learn how to use Dynamic Programming with Java in this course for beginners. It can help you solve complex programming problems, such as those often seen in programming interview questions about data structures and algorithms.

This course was developed by Alvin Zablan from Structy. Structy is a website for learning data structures and algorithms for technical interviews. Learn data structures and algorithms: https://structy.net/

Check out Alvin's channel: https://www.youtube.com/c/AlvinTheProgrammer

⭐️ Contents ⭐️
(0:00:00) course introduction
(0:01:38) fib
🔗 https://structy.net/problems/fib
(0:34:02) tribonacci
🔗 https://structy.net/problems/tribonacci
(0:47:05) sum possible
🔗 https://structy.net/problems/sum-possible
(1:04:18) min change
🔗 https://structy.net/problems/min-change
(1:22:22) count paths
🔗 https://structy.net/problems/count-paths
(1:39:02) max path sum
🔗 https://structy.net/problems/max-path-sum
(1:52:56) non adjacent sum
🔗 https://structy.net/problems/non-adjacent-sum
(2:08:22) summing squares
🔗 https://structy.net/problems/summing-squares
(2:21:50) counting change
🔗 https://structy.net/problems/counting-change

🎉 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

The Knapsack Problem is a classic optimization problem in computer science. It's often used to help teach dynamic programming and greedy algorithms. This is an important problem to understand, especially if you plan on interviewing soon for a programming job. In this course, Gavin Lon will explain the problem and show how to craft an efficient solution using C#.

💻 Code: https://github.com/GavinLonDig....ital/ZeroOneKnapsack

✏️ Course created by @GavinLon

⭐️ Contents ⭐️
(00:00) Introduction
(02:35) Overview of the 0 / 1 Knapsack problem
(09:08) Code the algorithm to solve the problem using C#
(17:49) Explain the algorithm that uses Dynamic Programming and the Memoization strategy
(38:17) Write code using C# to output the items to include in the Knapsack



🎉 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

Lean how to use FL Studio to produce music in this complete course for beginners. FL Studio is a complete software music production environment. It features a graphical user interface with a pattern-based music sequencer.

Tristan Willcox developed this course. You can email him at [email protected]

🔗 FL Studio: https://www.image-line.com/

Sample Packs:
🔗 https://cymatics.fm/
🔗 https://samples.landr.com/
🔗 https://sound-effects.bbcrewind.co.uk/
🔗 https://samplefocus.com/sample....s/arabian-vocal-melo
🔗 https://splice.com/

⭐️ Contents ⭐️
(0:00:00) Chapter 1: Virtual Instruments
(0:04:35) Chapter 2: Melodies and Chords
(0:30:52) Chapter 3: Using Patterns
(0:36:40) Chapter 4: Using Samples
(0:47:02) Chapter 5: Layering and Arranging
(1:00:12) Chapter 6: Leveling
(1:05:54) Chapter 7: Adding to the song
(1:42:55) Chapter 8: Mixing + FX
(1:58:21) Chapter 9: Automation
(2:07:07) Chapter 10: Mastering + Exporting

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

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

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

*Note: 1+ Years of Work Experience Recommended to Sign up for Below Programs⬇️
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Welcome to our Basics Of Artificial Intelligence video. In this informative and engaging video, we delve into the fundamental concepts of Artificial Intelligence (AI). Whether you're new to the field or simply looking to refresh your knowledge, this video has got you covered. We'll explore the definition of AI and its various branches, including machine learning. Discover how AI systems learn, reason, and make decisions, and gain insights into the different types of AI applications in today's world. Join us as we demystify AI and provide you with a solid foundation to better understand this exciting field. Don't forget to like, subscribe, and hit the notification bell to stay updated with our future videos on AI!

Here in this Basics Of Artificial Intelligence video, we start with:

00:00:00 Introduction to Basics Of Artificial Intelligence
00:05:42 What is Artificial Intelligence?
00:09:30 AI Roadmap for 2023
00:16:49 Types Of Artificial Intelligence
00:24:42 Top 10 AI Applications
00;35:28 Future of Artificial Intelligence
00:41:02 What is Machine Learning?
00:46:09 Types Of Machine Learning
01:07:38 Linear Regression Analysis
03:12:00 Classification In Machine Learning
04:46:56 Top 10 AI Tools For 2023
04:53:15 Top 10 AI Robots In 2023
04:59:44 Top 10 Artificial Intelligence Project Ideas 2023
05:13:15 Career Opportunities In Artificial Intelligence 2023

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

⏩ Check out the Machine Learning Videos By Simplilearn: https://youtube.com/playlist?l....ist=PLEiEAq2VkUUI731

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➡️ About Post Graduate Program In AI And Machine Learning

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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