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

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

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

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

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

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

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

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

--

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

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

🔥 Professional Certificate Program In Generative AI And Machine Learning (India Only) - https://www.simplilearn.com/iitr-generative-ai-machine-learning-program?utm_campaign=4Sep2024-RAG-(Retrieval-Augmented-Generation)&utm_medium=DescriptionFirstFold&utm_source=youtube
🔥 Purdue Post Graduate Program In AI And Machine Learning: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=4Sep2024-RAG-(Retrieval-Augmented-Generation)&utm_medium=DescriptionFirstFold&utm_source=youtube
🔥AI Engineer Masters Program (Discount Code - YTBE15): https://l.linklyhq.com/l/1yhn3

In this tutorial, we'll explore how RAG works, why it’s essential for modern AI, and how it solves the limitations of traditional language models. Whether you're a developer, tech enthusiast, or just curious about AI advancements, this guide will show you how RAG is shaping the future of AI by making models smarter and more relevant.RAG allows AI models to search for real-time information from external sources, combine it with their existing knowledge, and generate accurate, up-to-date responses. It’s like giving AI the ability to "Google" for answers while keeping their knowledge sharp.

00:00 Introduction

-- Frequently Asked Questions

✅ Question 1 What is Retrieval Augmented Generation (RAG)?

Answer:RAG is a hybrid AI technique that combines two key processes: retrieving external data from a knowledge base or web and then generating a response based on both the retrieved information and the model’s pre-trained knowledge. This allows the model to provide more accurate and up-to-date answers compared to traditional language models that only rely on their training data.


✅ Question 2 How does RAG improve the accuracy of AI models?

Answer:RAG enhances accuracy by pulling in relevant, real-time information from external sources. Traditional language models can only answer questions based on data they were trained on, which can become outdated. With RAG, AI models can retrieve the latest information, combine it with what they already know, and generate a response that’s both current and highly informed.


✅ Question 3 What are the main applications of RAG?

Answer:RAG is used in various fields such as customer support, healthcare, finance, and legal research. It powers AI models to deliver real-time, accurate responses by retrieving the most relevant and recent data. For instance, it’s used in chatbots for better customer service, in healthcare for retrieving the latest research, and in search engines to provide more relevant search results.

✅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_

✅ Know More about Simplilearn here: https://www.simplilearn.com/?utm_campaign=4Sep2024-RAG-(Retrieval-Augmented-Generation)&utm_medium=Description&utm_source=youtube

#rag(retrievalaugmentedgeneration) #ragretrievalaugmentedgenerationlangchain #retrievalaugmentedgeneration(rag)architecture #localretrievalaugmentedgeneration(rag)fromscratch(stepbysteptutorial) #ragretrievalaugmentedgeneration #llm #simplilearn #2024

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

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- ChatGPT
- Generative AI
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- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- NLP
- Neural Networks
- Computer Vision
- And Many More…

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✅ Inspiring Success Stories of Simplilearn's Learners: https://www.simplilearn.com/reviews?utm_campaign=4Sep2024-RAG-(Retrieval-Augmented-Generation)&utm_medium=Description&utm_source=youtube

Unpacking the multilayer perceptrons in a transformer, and how they may store facts
Instead of sponsored ad reads, these lessons are funded directly by viewers: https://3b1b.co/support
An equally valuable form of support is to share the videos.

AI Alignment forum post from the Deepmind researchers referenced at the video's start:
https://www.alignmentforum.org..../posts/iGuwZTHWb6DFY

Anthropic posts about superposition referenced near the end:
https://transformer-circuits.p....ub/2022/toy_model/in
https://transformer-circuits.p....ub/2023/monosemantic

Some added resources for those interested in learning more about mechanistic interpretability, offered by Neel Nanda

Mechanistic interpretability paper reading list
https://www.alignmentforum.org..../posts/NfFST5Mio7BCA

Getting started in mechanistic interpretability
https://www.neelnanda.io/mecha....nistic-interpretabil

An interactive demo of sparse autoencoders (made by Neuronpedia)
https://www.neuronpedia.org/gemma-scope#main

Coding tutorials for mechanistic interpretability (made by ARENA)
https://arena3-chapter1-transf....ormer-interp.streaml

Sections:
0:00 - Where facts in LLMs live
2:15 - Quick refresher on transformers
4:39 - Assumptions for our toy example
6:07 - Inside a multilayer perceptron
15:38 - Counting parameters
17:04 - Superposition
21:37 - Up next

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

These animations are largely made using a custom Python library, manim. See the FAQ comments here:
https://3b1b.co/faq#manim
https://github.com/3b1b/manim
https://github.com/ManimCommunity/manim/

All code for specific videos is visible here:
https://github.com/3b1b/videos/

The music is by Vincent Rubinetti.
https://www.vincentrubinetti.com
https://vincerubinetti.bandcam....p.com/album/the-musi
https://open.spotify.com/album..../1dVyjwS8FBqXhRunaG5

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

3blue1brown is a channel about animating math, in all senses of the word animate. If you're reading the bottom of a video description, I'm guessing you're more interested than the average viewer in lessons here. It would mean a lot to me if you chose to stay up to date on new ones, either by subscribing here on YouTube or otherwise following on whichever platform below you check most regularly.

Mailing list: https://3blue1brown.substack.com
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Website: https://www.3blue1brown.com

For more information about Stanford's online Artificial Intelligence programs visit: https://stanford.io/ai

To learn more about enrolling in this course visit: https://online.stanford.edu/co....urses/cs336-language

To follow along with the course schedule and syllabus visit: https://stanford-cs336.github.io/spring2025/

Percy Liang
Associate Professor of Computer Science
Director of Center for Research on Foundation Models (CRFM)

Tatsunori Hashimoto
Assistant Professor of Computer Science

View the entire course playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

🔥Advanced Certification In UI UX Design: https://www.simplilearn.com/ui-ux-certification-training-course?utm_campaign=DesignThinking-4nTh3AP6knM&utm_medium=DescriptionFirstFold&utm_source=youtube

In this design thinking tutorial, we will be looking at what is design thinking, why design thing is important, steps of design thinking, empathy mapping, five phases and four pillars of design thinking and agile methodology with design thinking. It is extremely helpful in solving problems that are ill-defined or unknown. Design Thinking is an iterative method that helps resolve user issues or redefines problems in alternative strategies and solutions.

🔥Explore our FREE Courses: https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=DesignThinking&utm_medium=DescriptionFirstFold&utm_source=youtube

Below are the topics we will be discussing in the video:
00:00:00 What is design thinking
00:07:42 Dt process
00:16:58 DT steps
00:27:40 Empathy mapping
00:33:00 DT and agile

Start learning today's most in-demand skills for FREE. Visit us at https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=DesignThinking&utm_medium=Description&utm_source=youtube
Choose over 300 in-demand skills and get access to 1000+ hours of video content for FREE in various technologies like Data Science, Cybersecurity, Project Management & Leadership, Digital Marketing, and much more.

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

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

#DesignThinkingCourse #DesignThinkingExamples #LearnDesignThinking #DesignThinkingProcess #DesignThinkingTraining #DesignThinking #Simplilearn

Design Thinking Certification Training Course:
This Design Thinking Course lets you master the concepts of design thinking—a powerful problem-solving process that involves a deep understanding of customer needs. You can boost your grasp of business strategy and innovation to drive a design thinking culture in your organization with the help of this Design Thinking Training.

Design Thinking Course Overview:
This Design Thinking Certification introduces you to the ImaginXP 5D design framework through case studies. You’ll learn how to identify problems, define requirements, and frame, ideate, prototype, test, and implement a business idea. You’ll also learn how to implement techniques for defining market fit and growth of your product and business.

Skills Covered:
✅ 5D design thinking framework
✅ Discover Define Dream Design Dry Run phases
✅ Ideate workshops
✅ Create innovative solutions
✅ Increase conversion rates
✅ Perform iterative tests
✅ Create interactive prototypes
✅ Perform behavioral user testing

👉Learn more at: https://www.simplilearn.com/design-thinking-certification-training-course?utm_campaign=DesignThinking&utm_medium=Description&utm_source=youtube

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🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

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

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

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

📝Feel free to share your comments below.📝

𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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

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

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

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

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

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This Excel Data Analytics Full Course, from Beginners to Advanced video by simplilearn, will guide you through creating data visualisations and charts like a Funnel Chart in Excel, leveraging advanced functions such as SUMIFS, SUMPRODUCT, and AVERAGEIFS formulas, and mastering Data Visualization techniques, including building Excel Charts like a pro and creating multiple dependent DROP DOWN LISTS. Additionally, you'll learn Data Analytics using AI, how to use Microsoft Power Query for Data Transformation, and importing Excel data into tools like MySQL Workbench and Power BI, alongside learning about the distinctions between a Database and a Data Warehouse. With bonus content covering Automated Payslip Generators, AI in Excel, and tools like ChatGPT and Google Gemini for data analytics, you'll be well-equipped for 2024 with the top Excel formulas and insights for analysts.

The Full course will cover the following topics

00:00:00 Introduction to Excel Full Course
05:34:44 Excel Full Course Beginners to Advanced
05:38:08 How To Create A Funnel Chart In Excel
05:42:10 Big Data in 5 minutes
05:50:28 Data Analyst Roadmap
05:52:32 Data Science Vs Data Analyst
06:02:55 Data Science Vs Data Analyst
06:25:18 Data Analytics using AI
06:31:31 How To Use The Scan Function in Excel ?
06:41:49 How To Use IF Formula In Excel - ADVANCED TIPS
06:44:12 SUMIFS Formula in Excel
07:21:22 Data VisuALIZATION In EXCEL
07:27:08 Compare Two Lists And Find A Match In Excel
07:31:20 Build Excel Charts Like A Pro
07:44:34 Create Multiple Dependent DROP DOWN LIST In EXCEL
07:48:27 SUMPRODUCT Excel
07:50:18 AVERAGEIFS Formula in Excel
08:08:45 How to use microsoft power query
08:14:10 How To Import Excel Data File To MySQL Workbench
08:20:49 How To Import Excel Data In Power BI
08:22:33 How to Import Data from Web to Excel
08:52:31 Master DATA CLEANING In EXCEL
08:53:25 Database Vs Data Warehouse
09:03:46 Database Vs Data Warehouse
09:22:06 Excel Dashboard For Beginners
09:26:41 How To Use AI In Excel ?
09:42:07 How To Build Automated Payslip Generator In Excel
09:51:28 Copilot In EXCEL
10:04:10 Learn EXCEL Using Google Gemini
10:19:47 ChatGPT And Excel For Data Analytics
10:36:08 Data Transformation
11:07:07 ChatGPT for Excel Dashboard
11:30:53 Top 10 Important Excel Formulas For Analysts In 2024

⏩ Check out the Excel tutorial videos: https://www.youtube.com/watch?v=nPkmWE4JCfE&list=PLEiEAq2VkUUKf8aLrspLg3zuyJ5S-5K5S

#exceldataanalytics #exceltraining #excelformulasandfunctions #exceldatavisualization #excelcourse #simplilearn #simplilearn #2024

➡️ About Post Graduate 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
✅ Post Graduate 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=oHm6uf9YOt0&utm_medium=Description&utm_source=youtube

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

In this video Jake Xia provides an overview of key financial concepts, including market structure, types of financial products like stocks, bonds, derivatives, and the roles of various market participants. He also introduces investment strategies, emphasizing the importance of understanding personal financial goals, risk management, and the use of mathematical models in pricing and trading, culminating in a practical trading game to apply these concepts.

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.

MIT 14.01 Principles of Microeconomics, Fall 2023
Instructor: Prof. Jonathan Gruber
View the complete course: https://ocw.mit.edu/14-01F23
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

In this lecture, Prof. Gruber talks about where consumer decisions come from, beginning with consumer preferences. He then builds on these concepts to explain the utility function, which is a mathematical expression of consumer preference. Keywords: micoreconomics, consumer demand, preferences, utility function

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.

There is so much being said about artificial intelligence these days. In order to understand this latest wave of AI, it is important to know how it works and why this moment is different from developments in the past.

WSJ science reporter Eric Niiler joins host Zoe Thomas for the first installment of Tech News Briefing’s special series Artificially Minded. New episodes drop every Monday in April.

0:00 AI basics
2:18 What is machine learning?
4:20 How generative AI like ChatGPT works
6:07 AI in our daily lives
7:45 How people on the street feel about AI
8:38 Why AI is a hot topic right now
9:50 Risks and rules surrounding AI

Tech News Briefing
WSJ’s tech podcast featuring breaking news, scoops and tips on tech innovations and policy debates, plus exclusive interviews with movers and shakers in the industry.

For more episodes of WSJ’s Tech News Briefing: https://link.chtbl.com/WSJTechNewsBriefing

#AI #ArtificialIntelligence #WSJ

MIT Introduction to Deep Learning 6.S191: Lecture 1
*New 2024 Edition*
Foundations of Deep Learning
Lecturer: Alexander Amini

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

Lecture Outline
0:00​ - Introduction
7:25​ - Course information
13:37​ - Why deep learning?
17:20​ - The perceptron
24:30​ - Perceptron example
31;16​ - From perceptrons to neural networks
37:51​ - Applying neural networks
41:12​ - Loss functions
44:22​ - Training and gradient descent
49:52​ - Backpropagation
54:57​ - Setting the learning rate
58:54​ - Batched gradient descent
1:02:28​ - Regularization: dropout and early stopping
1:08:47 - Summary

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

A light intro to LLMs, chatbots, pretraining, and transformers.
Dig deeper here: https://www.youtube.com/playli....st?list=PLZHQObOWTQD
Technical details as a talk: https://youtu.be/KJtZARuO3JY
This was made for an exhibit at the Computer History Museum: https://computerhistory.org/
Instead of sponsored ad reads, these lessons are funded directly by viewers: https://3b1b.co/support

No secret end-screen vlog for this one, the end-screen real estate was all full!

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All code for specific videos is visible here:
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The music is by Vincent Rubinetti.
https://www.vincentrubinetti.com
https://vincerubinetti.bandcam....p.com/album/the-musi
https://open.spotify.com/album..../1dVyjwS8FBqXhRunaG5

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AI Agents Explained: A Comprehensive Guide for Beginners by Alfie Marsh Co-Founder & CEO of https://www.getstation.ai/

(0:00) Introduction to AI Agents
(0:23) What is an AI Agent?
(0:49) How AI Agents Differ from Traditional Software
(1:36) AI Agents vs Large Language Models (LLMs)
(2:50) How AI Agents Work
(3:16) Component 1: Planning
(3:47) Component 2: Interacting with Tools
(4:10) Component 3: Memory and External Knowledge
(5:07) Component 4: Executing Actions
(5:39) Risks and Future of AI Agents
(6:30) Conclusion

In this video, Alfie Marsh, Co-Founder & CEO of Station AI, unpacks the world of AI agents and explains how they are evolving to become an integral part of our lives. Discover what AI agents are, how they differ from traditional automations and other large language models (LLMs) like GPT, Claude, and Gemini, and explore real-world examples of AI agents in action.

Learn about the key components that make up AI agents, including their ability to plan, interact with tools, store memory, access external knowledge, and execute actions autonomously. Alfie also discusses the potential risks and the future of AI agents as they become more sophisticated with advancements in language models like GPT-4 and beyond.

Whether you're interested in building AI agents, understanding how they work, or exploring no-code solutions and tutorials, this video provides a comprehensive overview of AI agents and their growing importance in our lives and careers.

Claude Code in 2026 is not what it was when it launched. After a year of building frameworks, custom setups, and elaborate systems to make AI coding work, we've come to a point now where... most of that is overkill.

In this video, I'll show you what building with pure vanilla Claude Code actually looks like in 2026. No frameworks. No custom rules. Just Claude Code with Opus 4.5 handling real professional development work.

I'll build a real feature in a real app, walking you through plan mode, the clarifying questions flow, and the native features that now do what frameworks used to do.

If you're just getting into AI-assisted development, or if you've been layering tools onto your workflow — this video will show you the simpler path forward.

👇 **Your Builder Briefing (free)**
https://buildermethods.com - Your free, 5-minute read to keep up with the latest tools & workflows for building with AI.

👇 **Build with Claude Code (course)**
https://buildermethods.com/pro/claude-code-course -- Launching in Feb 2026 For members of Builder Methods Pro. Early access workshop happening in January 2026.

▶️ Related videos:
AI skills that matter in 2026 https://youtu.be/7JBuA1GHAjQ
Design OS for AI-first design process https://youtu.be/2vu-6-lIhAs

💬 Drop a comment with your questions and requests for upcoming videos!

Chapters:

0:00 - The Claude Code scene in 2026
5:09 - Claude Code Ask User Questions tool
8:23 - What Changed for 2026
9:27 - Reviewing Claude Code's Build
11:13 - Core Features in Claude Code
11:52 - The Skill That Still Matters
12:49 - When Frameworks Still Help

Prepare for the course

Baltimore 8K Video Ultra HD 120 FPS - City in Maryland || 8K TV Test Video
8K Video Ultra HD, 60fps, 120fps, 240fps for Your 8K Resolution Device: Apple TV, 8K TV Samsung, LG TV, OLED TV, QLED TV, Sony Device or iPhone, Huawei, Xiaomi, Asus Phone and your others 8k device.

》This 8K Demo video is make for Educational and Entertainment purposes. You can use it to learn About Country, City, Nature, Place, River and etc with 8K Ultra HD Resolution.

》I did high color correction, color change, bit rate, raw video editing, merge files, optimize 8K demo video and more.

》About Baltimore : Baltimore is a major city in Maryland with a long history as an important seaport. Fort McHenry, birthplace of the U.S. national anthem, “The Star-Spangled Banner,” sits at the mouth of Baltimore’s Inner Harbor. Today, this harbor area offers shops, upscale crab shacks and attractions like the Civil War–era warship the USS Constellation and the National Aquarium, showcasing thousands of marine creatures. ― Google
Area: 239 km²
Weather: 22°C, Wind E at 5 km/h, 78% Humidity weather.com
Local time: Saturday 8:33 AM
Area code: Area code 410
Mayor: Brandon Scott
Population: 602,274 (2020)
》Top Rated Attractions & Things to Do in Baltimore :
1. Fort McHenry National Monument and Historic Shrine
2. National Aquarium
3. American Visionary Art Museum
4. Baltimore Museum of Art
5. Inner Harbor and Historic Ships
6. See a Game: Oriole Park at Camden Yards
7. Fell's Point
8. Baltimore and Ohio Railroad Museum
9. Maryland Science Center
10. Baltimore Museum of Industry
11. National Cryptologic Museum
12. Maryland Zoo in Baltimore
13. Basilica of the National Shrine of the Assumption of the Blessed Virgin Mary
14. Washington Monument and Mount Vernon
15. Little Italy & etc.

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》Thumbnail Credits: Canva
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I Use Paid Music in this Video
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》All Credits Goes to Youtube
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© Disclaimer:
》All The Footage Used In this Video Licensed by 8K Earth.
》I Use Paid Stock Footage & All Pictures In My Channel.
》Video Footage Copyright Under Standard License.
》I tried to Present a new way by Changing the color of the Video.

#8k #8kvideo #baltimore #maryland #120fps #ultrahd

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Download the complete blueprint to making a movie for free: https://bit.ly/moviemakingblueprint

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I rented a Red Monstro 8K cinema camera for a recent short film. I used Arri Master Anamorphics for a 2.40:1 finish, so my settings were 8K 6:5, 4:1 compression at about T8 mostly.

I also tested the Sony Venice for this project, since both of them are good cameras for low light. Overall, till ISO 3200, they are pretty much similar. At ISO 6400 the Sony Venice is definitely better, and it has great IRND filters that retain color information all the way up. Still, I picked the Monstro for reasons explained in the video.

BTS by Shrey Gambhir and Shyam Kamble
Camera rented from Kshitij Entertainment
Associate Cameramen: Shomit Naik and Murugan Vellaidurai
Focus Puller: Raju Kamat
Key Grip: Ganesh
Gaffer: Mehmood Ali

I'll publish the short film once I'm done with post.

Links related to this video:

Arri Alexa LF review: https://www.youtube.com/watch?v=36SgNE2qMLM
Arri vs Red: When to pick which: https://www.youtube.com/watch?v=ofKveshwVbo
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Rice Mill: https://www.youtube.com/watch?v=dvccueIPlfo
Anamorphic Workflow Guide: https://www.youtube.com/watch?v=o6y9zrFJNFI
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Written review: http://bit.ly/2JOsSuq

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Artificial neural networks provide us incredibly powerful tools in machine learning that are useful for a variety of tasks ranging from image classification to voice translation. So what is all the deep learning rage about? The media seems to be all over the newest neural network research of the DeepMind company that was recently acquired by Google. They used neural networks to create algorithms that are able to play Atari games, learn them like a human would, eventually achieving superhuman performance.

Deep learning means that we use artificial neural network with multiple layers, making it even more powerful for more difficult tasks. These machine learning techniques proved to be useful for many tasks beyond image recognition: they also excel at weather predictions, breast cancer cell mitosis detection, brain image segmentation and toxicity prediction among many others.

In this episode, an intuitive explanation is given to show the inner workings of deep learning algorithms.

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Original blog post by Christopher Olah (source of many images):
http://colah.github.io/posts/2....014-03-NN-Manifolds-

You can train your own deep neural networks on Andrej Karpathy's website:
http://cs.stanford.edu/people/....karpathy/convnetjs/d

Images used in this video:
Bunny by Tomi Tapio K (CC BY 2.0) - https://flic.kr/p/8EbcEk
Train by B4bees (CC BY 2.0) - https://flic.kr/p/6RzHe4
Train with bunny by Alyssa L. Miller (CC BY 2.0) - https://flic.kr/p/5WPeRN
The knot theory blackboard image was created by Clayton Shonkwiler (CC BY 2.0) https://flic.kr/p/64FYv
The tangled knot image was created by Mikael Hvidtfeldt Christensen (CC BY 2.0) https://flic.kr/p/beYG9D

The thumbnail image is a work of Duncan Hull (CC BY 2.0) - https://flic.kr/p/98qtJB

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