Correction (10:26). The probabilities are wrong. The correct ones are here:
For Die 1: 0.4^4 * 0.2^2 * 0.1^1 * 0.1^1 * 0.2^2
For Die 2: 0.4^4 * 0.1^2 * 0.2^1 * 0.2^1 * 0.1^2
For Die 3: 0.1^4 * 0.2^2 * 0.4^1 * 0.2^1 * 0.1^2

Kullback Leibler (KL) divergence is a way to measure how far apart two distributions are.
In this video, we learn KL-divergence in a simple way, using a probability game with dice.

Shannon entropy and information gain: https://www.youtube.com/watch?v=9r7FIXEAGvs&t=1066s&pp=ygUic2hhbm5vbiBlbnRyb3B5IGluZm9ybWF0aW9uIHRoZW9yeQ%3D%3D

Grokking Machine Learning book: www.manning.com/books/grokking-machine-learning
40% discount code: serranoyt

This video shows how you can detect if a sequence is periodic or not, and also find its period, using the Discrete Fourier Transform.

This is the second 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 (this one)

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

00:00 Introduction
2:37: Periodic sequences
12:54 In the inverse DFT

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)

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

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

An introduction to logistic regression and the perceptron algorithm that requires very little math (no calculus or linear algebra), only a visual mind.

0:00 Introduction
0:08 Series of 3 videos
0:41 E-mail spam classifier
7:19 Classification goal: split data
11:36 How to move a line
12:21 Rotating and translating
18:47 Perceptron Trick
23:20 Correctly and incorrectly classified points
24:20 Positive and negative regions
27:18 Perceptron Error
29:40 Gradient Descent
34:36 A friendly introduction to deep learning and neural networks
37:48 Activation function (sigmoid)
38:31 Log-Loss Error
41:37 Perceptron Algorithm
42:45 Logistic regression algorithm
44:48 Thank you!

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

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

An introduction to support vector machines (SVMs) that requires very little math (no calculus or linear algebra), only a visual mind.
This is the third of a series of three videos.
- Linear Regression: https://www.youtube.com/watch?v=wYPUhge9w5c
- Logistic Regression: https://www.youtube.com/watch?v=jbluHIgBmBo

0:00 Introduction
1:42 Classification goal: split data
3:14 Perceptron algorithm
6:00 Split data - separate lines
7:05 How to separate lines?
12:01 Expanding rate
18:19 Perceptron Error
19:26 SVM Classification Error
20:34 Margin Error
25:13 Challenge - Gradient Descent
27:25 Which line is better?
28:24 The C parameter
30:16 Series of 3 videos
30:30 Thank you!

Hi my name is Chris and I build productivity apps 👋 and this is EVERYTHING I learned building an AI agent using the Anthropic Agent SDK :)

---
Check out Convex (database I'm using): https://convex.link/chrisraroque
(please tell them I sent you 🙏)
---

My apps and socials: https://chrisraroque.com
My agency (work with me): https://aloa.co/

Timestamps:
0:00 – Intro / What we are covering
1:03 - What I built with the Agent SDK
2:28 - How Agents Work & Agent SDK Bascs
4:50 - What makes the Agent SDK special
7:55 - Using Convex as the database for my agent
9:19 - Building tools for the agent
10:28 - Agent Skills
12:32 - Agent memory
14:24 - Why I could not release my agent
17:07 - Practical use cases for agents
18:26 - Deploying agents
19:47 - Final thoughts and thank you :)

#appdevelopment #dayinthelife #softwareengineer #startup #softwaredev #indieappdeveloper #dayinthelifecoding #codewithme #buildinpublic #vlog

Anthropic’s Alex Albert (Claude Relations) sits down with Erik Schluntz (Multi-Agent Research and co-author of our blog post, Building Effective Agents) for a discussion on the evolution of agents over the past six months, including tips for building multi-agent systems, common multi-agent patterns, and best practices for using skills, MCP servers, and tools.

00:00 - Introductions
00:35 - Training Claude to tackle agentic tasks
1:30 - Making Claude more autonomous with code
3:20 - Using the Claude Agent SDK to build agents
5:00 - Tips for using Agent Skills
6:40 - The evolution of workflows and agents (workflows of agents)
8:30 - The value of simple agent architectures
9:30 - Building multi-agent systems: orchestrators, subagents, and tool calling
11:40 - Training Claude to use subagents
12:25 - Multi-agent use design patterns: parallelization, MapReduce, and test-time compute
13:20 - Coordinating problem solving with tools and subagents
14:15 - Common agent failure modes
15:00 - Best practices for getting started with building agents (context engineering, MCPs, and tools)
17:15 - The future of agents: coding, computer use, and beyond

Read the original blog post: https://www.anthropic.com/engi....neering/building-eff
Learn more about Agent Skills: https://www.anthropic.com/engi....neering/equipping-ag

Gemini 3 is our most intelligent model yet that helps you bring any idea to life. In this video, you’ll learn how to build an AI Agent with Gemini 3 Pro and the Agent Development Kit (ADK). You’ll explore how to build a single agent with access to Google Search as its tool, and interact with it using a web UI. We will also learn how Gemini 3 Pro uses Thought Signatures and we will explore its chain of thought when the agent receives a prompt.


Resources:
Getting started with uv → https://goo.gle/4a7M7KG
ADK Google Search Tool docs → https://goo.gle/3LGFKUR
Github Repo for the AI Agent built with Gemini 3 Pro →
https://goo.gle/4pq0pep

Timestamps:
0:00 - Introduction to Gemini 3 Pro
0:32 - Initializing the Project & Installing ADK and GenAI libraries
1:25 - Setting up Google AI Studio’s API Key & Creating Agent Scaffolding with ADK Create
2:00 - Implementing the Google Search Tool
2:33 - Configuring the Gemini 3 Pro Model
3:14 - Deploying the Agent to ADK Web
4:29 - Testing the Agent
5:24 - Thought Signatures and Analyzing Chain of Thought
6:40 - Conclusion

Speaker: Smitha Kolan
Products Mentioned: Gemini, Google AI, Agent Development Kit (ADK)

n8n Tutorial for Beginners 2026: How to Build AI Agents
✅ self-host n8n and save tons of money with Hostinger: http://hostinger.com/youri10

In this video, I show you how to build your own AI agent in n8n from scratch, self-host it on Hostinger for unlimited executions, and automate tasks that normally waste hours every week. You’ll learn how to set up a VPS with one-click n8n installation, connect OpenAI models and memory, add real-world tools like Google Search, and turn the output into clean newsletters automatically sent to your inbox.

for inquiries: youri (at) mediaflow.group

Try Notion for free → https://ntn.so/techwithtim

👉 Check out PyCharm, the only Python IDE you need. Built for web, data, and AI/ML professionals. Download now. Free forever, plus one month of Pro included: https://jb.gg/check_out_pycharm_ide

Today I'm going to show you how to build an AI agent in Python in less than ten minutes.

Want to make real money with coding? I share high-signal insights on careers, monetization, and leverage in my free newsletter. Join here and get my guide How to Make Money With Coding instantly: https://techwithtim.net/newsletter

🎞 Video Resources 🎞
UV Video: https://www.youtube.com/watch?v=6pttmsBSi8M
Code in this video: https://github.com/techwithtim..../PythonAIAgentin10Mi

⏳ Timestamps ⏳
00:00 | Install & Setup
01:23 | OpenAI API Key
03:26 | Imports
04:42 | Tools
06:39 | LLM & Agent
07:43 | Driver Code
09:45 | Testing

Hashtags
#Python #AIAgents #Notion

Check out HubSpot’s AI Agents Unleashed: Playbook for 2025 Success - https://clickhubspot.com/23bc50
🤖 Want to get ahead in your career using AI? Join the waitlist for my AI Agent Bootcamp: https://www.lonelyoctopus.com/ai-agent-bootcamp

I tested every no-code AI agent builder so you don’t have to.
From StackAI and Relevance AI to n8n, Flowise, Lindy, and Dify, this video breaks down the best platforms to create AI agents — without writing a single line of code.

You’ll learn:
⚙️ The core features and ideal use cases of each builder
🧩 How each platform handles automation, API integration, and LLM workflows
📈 When to use visual tools vs workflow orchestrators
💡 The difference between automations and dynamic agents — and why it matters
🚀 The easiest way to go from idea → AI agent → deployed product

We’ll explore:

StackAI for general-purpose agents and API publishing
Relevance AI for scalable workflows
n8n for powerful orchestration & branching logic
Flowise / Langflow for open-source prompt engineering
Dify and Lindy for hybrid and business automation
Botpress, Bubble, Make, MindStudio, and more

By the end, you’ll know exactly which no-code agent builder fits your workflow.

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

🔗 Tools & Resources Mentioned
https://learn.deeplearning.ai/....courses/agentic-ai/l
https://learn.deeplearning.ai/....courses/agentic-ai/l
https://learn.deeplearning.ai/....courses/agentic-ai/l
https://learn.deeplearning.ai/....courses/agentic-ai/l

🔗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
========================
📷 camera: https://amzn.to/3LHbi7N
🎤 mic: https://amzn.to/3LqoFJb
🔭 tripod: https://amzn.to/3DkjGHe
💡 lights: https://amzn.to/3LmOhqk

📲Socials
========================
instagram: https://www.instagram.com/hellotinah/
linkedin: https://www.linkedin.com/in/tinaw-h/
tiktok: https://www.tiktok.com/@hellotinahuang
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: tina@smoothmedia.co

========================
Some links are affiliate links and I may receive a small portion of sales price at no cost to you. I really appreciate your support in helping improve this channel! :)

Host your n8n agents on Hostinger: https://www.hostinger.com/david
Use code David ;)

Learn about the best AI Business models here - https://www.youtube.com/watch?v=Ta5g-OxjPO4

Wanna learn how to code with AI? Go here: https://www.skool.com/new-society

Follow me on Instagram - https://www.instagram.com/davidondrej1/
Follow me on Twitter - https://x.com/DavidOndrej1

Subscribe if you're serious about AI.

This is the ultimate guide about AI Agents.

www.vectal.ai

🧪AI Agents Labs for Free: https://kode.wiki/3Wh4DZ6

Learn everything about AI agents from scratch in this comprehensive tutorial. No prior knowledge required. We'll take you from zero to building production-ready AI systems with hands-on labs.

🎯 What You'll Learn:
• AI Fundamentals - LLMs, tokens, embeddings, and context windows
• LangChain - Simplify AI development with pre-built components
• Prompt Engineering - Zero-shot, few-shot, and chain-of-thought techniques
• Vector Databases - Semantic search with ChromaDB and Pinecone
• RAG (Retrieval Augmented Generation) - Build intelligent document search
• LangGraph - Create multi-step AI workflows and agents
• MCP (Model Context Protocol) - Connect AI to external tools

🔧 Hands-On Labs Include:
✓ Making your first OpenAI API calls
✓ Building semantic search engines
✓ Creating RAG systems for document retrieval
✓ Developing multi-agent workflows
✓ Integrating external tools with MCP

Perfect for developers, data scientists, and anyone wanting to understand modern AI development. Follow along with free labs and build a real-world AI assistant that searches 500GB of documents in under 30 seconds.

🚨Start Your AI Journey with KodeKloud: https://kode.wiki/4qsrspX

⏰ TIMESTAMPS:
00:00 - Introduction to AI Agents
00:40 - How LLMs work in real time?
04:56 - Embeddings & Vector Representations
05:56 - How LangChain works?
10:12 - Practice Labs - Your First AI API Call
14:57 - Practice Labs - LangChain
17:57 - Prompt Engineering Techniques
21:21 - Practice Labs - Master Prompt Engineering
24:46 - Vector Databases Deep Dive
31:27 - Practice Labs - Build Semantic Search Engine
35:15 - RAG (Retrieval Augmented Generation)
38:14 - Practice Labs - RAG Implementation
42:14 - LangGraph for AI Workflows
45:51 - Practice Labs - Build Stateful AI Workflow
48:51 - Model Context Protocol (MCP)
51:56 - Practice Labs - Advanced MCP Concepts
55:21 - Conclusion

🔔 Subscribe to KodeKloud for more AI development tools and tutorials!

#AiAgents #AI #Aifundamentals #LangChain #MCP #LLMs #RAG #Langgraph #vectordb #promptengineering #VectorDatabases #Tutorial #kodekloud

Want to see Maya Murad explain more about AI Agents? Click here to register for a Virtual Agents Webinar → https://ibm.biz/BdaAVa
Want to play with the technology yourself? Explore our interactive demo → https://ibm.biz/BdKsEf

In this video, Maya Murad explores the evolution of AI agents and their pivotal role in revolutionizing AI systems. From monolithic models to compound AI systems, discover how AI agents integrate with databases and external tools to enhance problem-solving capabilities and adaptability.

AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://www.ibm.com/account/re....g/us-en/signup?formi

Thanks to Microsoft for sponsoring this video! Submit your #CodingWithCopilot story for a chance to be featured in an upcoming video!

In this video, you'll learn how to build an AI agent
from scratch in Python. I'll walk you through everything step-by-step. This will be very beginner friendly,
and you'll learn how to make something quite interesting in Python
with some popular frameworks like LangChain. I'll show you how to use various
LLMs like Claude or GPT, how you can give the agent access to various tools, and how you can structure the output of the agent
so you can use it in your code.

🎞 Video Resources 🎞
Code in this video: https://github.com/techwithtim..../PythonAIAgentFromSc
Learn Python Virtual Environments: https://www.youtube.com/watch?v=Y21OR1OPC9A
Get Your Anthropic API Key: https://console.anthropic.com/settings/keys
Get Your OpenAI API Key: https://platform.openai.com/api-keys

⏳ Timestamps ⏳
00:00 | Overview
00:35 | Agent Demo
01:38 | Setup/Requirements
06:53 | Basic Code Setup/Imports
08:37 | Using Claude or GPT
10:00 | Getting Your API Key
11:32 | Basic LLM Functionality
12:43 | Structured Output/Models
15:42 | Prompt Templates
17:33 | Creating & Running the Agent
21:00 | Output Parsing
23:39 | Adding Prebuilt Tools
30:48 | Custom Tool Calling

Hashtags
#CodingWithCopilot #Sponsored

Ready to become a certified watsonx AI Assistant Engineer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/BdndTY

Want to learn more about Agentic AI + Data? Register here → https://ibm.biz/BdeGLe

Learn more about Agentic AI + Data here → https://ibm.biz/BdeGLe

What’s the difference between generative AI and agentic AI? 🤔 Martin Keen explains how generative AI powers content creation and image generation, while agentic AI uses LLMs and chain of thought reasoning for proactive tasks like personal shopping and conference planning. Discover the future of intelligent AI collaboration! 🚀

AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdndTz

#generativeai #agenticai #ai #llm