Learn how to build your own large language model, from scratch. This course goes into the data handling, math, and transformers behind large language models. You will use Python.

✏️ Course developed by @elliotarledge

💻 Code and course resources: https://github.com/Infatoshi/fcc-intro-to-llms

Join Elliot's Discord server: https://discord.gg/pV7ByF9VNm

⭐️ Contents ⭐️
(0:00:00) Intro
(0:03:25) Install Libraries
(0:06:24) Pylzma build tools
(0:08:58) Jupyter Notebook
(0:12:11) Download wizard of oz
(0:14:51) Experimenting with text file
(0:17:58) Character-level tokenizer
(0:19:44) Types of tokenizers
(0:20:58) Tensors instead of Arrays
(0:22:37) Linear Algebra heads up
(0:23:29) Train and validation splits
(0:25:30) Premise of Bigram Model
(0:26:41) Inputs and Targets
(0:29:29) Inputs and Targets Implementation
(0:30:10) Batch size hyperparameter
(0:32:13) Switching from CPU to CUDA
(0:33:28) PyTorch Overview
(0:42:49) CPU vs GPU performance in PyTorch
(0:47:49) More PyTorch Functions
(1:06:03) Embedding Vectors
(1:11:33) Embedding Implementation
(1:13:06) Dot Product and Matrix Multiplication
(1:25:42) Matmul Implementation
(1:26:56) Int vs Float
(1:29:52) Recap and get_batch
(1:35:07) nnModule subclass
(1:37:05) Gradient Descent
(1:50:53) Logits and Reshaping
(1:59:28) Generate function and giving the model some context
(2:03:58) Logits Dimensionality
(2:05:17) Training loop + Optimizer + Zerograd explanation
(2:13:56) Optimizers Overview
(2:17:04) Applications of Optimizers
(2:18:11) Loss reporting + Train VS Eval mode
(2:32:54) Normalization Overview
(2:35:45) ReLU, Sigmoid, Tanh Activations
(2:45:15) Transformer and Self-Attention
(2:46:55) Transformer Architecture
(3:17:54) Building a GPT, not Transformer model
(3:19:46) Self-Attention Deep Dive
(3:25:05) GPT architecture
(3:27:07) Switching to Macbook
(3:31:42) Implementing Positional Encoding
(3:36:57) GPTLanguageModel initalization
(3:40:52) GPTLanguageModel forward pass
(3:46:56) Standard Deviation for model parameters
(4:00:50) Transformer Blocks
(4:04:54) FeedForward network
(4:07:53) Multi-head Attention
(4:12:49) Dot product attention
(4:19:43) Why we scale by 1/sqrt(dk)
(4:26:45) Sequential VS ModuleList Processing
(4:30:47) Overview Hyperparameters
(4:32:14) Fixing errors, refining
(4:34:01) Begin training
(4:35:46) OpenWebText download and Survey of LLMs paper
(4:37:56) How the dataloader/batch getter will have to change
(4:41:20) Extract corpus with winrar
(4:43:44) Python data extractor
(4:49:23) Adjusting for train and val splits
(4:57:55) Adding dataloader
(4:59:04) Training on OpenWebText
(5:02:22) Training works well, model loading/saving
(5:04:18) Pickling
(5:05:32) Fixing errors + GPU Memory in task manager
(5:14:05) Command line argument parsing
(5:18:11) Porting code to script
(5:22:04) Prompt: Completion feature + more errors
(5:24:23) nnModule inheritance + generation cropping
(5:27:54) Pretraining vs Finetuning
(5:33:07) R&D pointers
(5:44:38) Outro

🎉 Thanks to our Champion and Sponsor supporters:
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👾 Justin Hual
👾 Otis Morgan

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I went from being a college dropout with zero technical skills to landing a software developer job in 4 months. This video is about how I became a self-taught software developer and how I learned how to code without a computer science degree or coding bootcamp.

Connect With Me:
⭐️ Main Site: https://www.timkim.me/
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Learn How To Code Playlist:
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Mentioned Resources:
⭐️ https://www.coursera.org/learn..../learning-how-to-lea
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Behind The Scenes:
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Disclaimer: Some of the links are affiliate links so I can feed mi familia while I make these videos for you guys. 🙏🙏🙏

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐉𝐚𝐯𝐚 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠: https://www.edureka.co/java-j2ee-training-course (Use code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎")
This Edureka video on "Interface on Java" will provide you with detailed knowledge about Java Interface and also cover some real time examples in order to provide you a better understanding of the functionality of Java Interface. This video will cover the following topics:
00:00:00 Introduction
00:00:22 Agenda
00:00:56 What is an Interface?
00:01:30 Why do we need an Interface?
00:03:20 Practical examples on Interface
00:05:32 Interface Nesting
00:07:02 Difference between Class and Interface
00:08:30 Advantages and Disadvantages of Interface
00:09:10 Key Points on Interface.
00:09:55 Practical Examples of Interface on Key Points

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

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📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
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📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
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Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

🔥Edureka Tensorflow Training - https://www.edureka.co/ai-deep....-learning-with-tenso
This Edureka "Neural Network Tutorial" video (Blog: https://goo.gl/4zxMfU) will help you to understand the basics of Neural Networks and how to use it for deep learning. It explains Single layer and Multi layer Perceptron in detail.

Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE

00:00 Introduction
01:00 Why Neural Networks
02:24 Motivation Behind Neural Networks
04:43 What are Neural Networks
06:39 How it works
13:42 Activation Functions
17:12 Multi Layer Perceptron
20:51 Training a Neural Network
24:36 Hands On

------------------------------------Edureka Online Training and Certification---------------------------------

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-----------------------------------------Edureka Masters Programs---------------------------------------------------

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🟣Business Intelligence Masters Program: https://bit.ly/2BPLtn2
🔵Python Developer Masters Program: https://bit.ly/2Vn7tgb
🟣RPA Developer Masters Program: https://bit.ly/3eHwPNf

---------------------------------------Edureka Post Graduate Courses-------------------------------------------

🔵 Artificial and Machine Learning PGD: https://bit.ly/3AylL0q

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

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#edureka #deeplearningEdureka #artificialNeuralnetwork #deeplearningTutorial #learnDeeplearning #withMe

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

How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

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

About the Course

Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow.

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

Who should go for this course?

The following professionals can go for this course:
1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers
3. Business Analysts
4. Information Architects
5. Professionals who want to captivate and analyze Big Data
6. Analysts wanting to understand Data Science methodologies

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

Why Learn Deep Learning With TensorFlow?
TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.

For more information, please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free).

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ChatGPT, an extraordinary creation of artificial intelligence. Born from the brilliance of OpenAI's GPT-3.5 architecture, ChatGPT is designed to engage, educate, and entertain. With a vast expanse of knowledge and the ability to adapt to individual preferences, ChatGPT is here to provide valuable insights, answer questions, and spark captivating conversations. From exploring various subjects to assisting with creative endeavors, ChatGPT is ready to embark on a journey of discovery with you. Whether you are a marketing expert, cybersecurity expert, a developer or a blogger, ChatGPT is all you need!
This full course on chatgpt, will help you to excel in it in digital marketing domain, cybersecurity, ui ux, content creation, seo. With this we will also put a light on how to use ChatGPT to make money!

00:00 Introduction to ChatGPT
06:16 How does ChatGPT work?
11:32 What is GPT 4?
15:11 Automate Excel using ChatGPT
01:27:57 How to use ChatGPT for SEO?
02:17:28 Chat GPT for Content Creation
02:26:21 Master SEO Content Using ChatGPT
02:28:08 ChatGPT for Marketing
02:38:50 How to Build a Website Using ChatGPT
03:20:50 How To Use ChatGPT For Web Development
03:36:57 Chat GPT for Programming
03:45:17 Can ChatGPT Solve LeetCode Problems?
05:11:49 Create a Telegram Bot Using ChatGPT
05:50:30 How To Integrate ChatGPT With Whatsapp
Automate WhatsApp using ChatGPT
06:06:14 Build a Game using Python and ChatGPT
06:38:44 ChatGPT in Cybersecurity
07:00:29 ChatGPT for UI/UX Design
07:47:42 Top 10 Chat GPT Use Cases
08:13:46 6 Reasons Why ChatGPT Can Make Your Business
08:23:19 9 Ways to Make Money Online Using ChatGPT
08:43:48 Bing vs Bard vs ChatGPT : Comparison
09:08:34 Will ChatGPT and Bard Take Over SEO?

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➡️ About Caltech Post Graduate Program In AI And Machine Learning

Designed to boost your career as an AI and ML professional, this program showcases Caltech CTME's excellence and IBM's industry prowess. The artificial intelligence course covers key concepts like Statistics, Data Science with Python, Machine Learning, Deep Learning, NLP, and Reinforcement Learning through an interactive learning model with live sessions.

✅ Key Features

- Simplilearn's JobAssist helps you get noticed by top hiring companies
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This Data Engineer Full Course video explains What Is Big Data, How to become a Data Engineer, skills required for Data engineering jobs, Big Data applications, introduction to Hadoop, Hadoop ecosystem, Spark, and top Hadoop interview questions. So, let's get started with this Data Tutorial For Beginners!

Below are the topics covered in this video
00:00:00 Data Engineer Crash Course
00:03:44 What is Big Data?
00:07:32 Big Data Tools
00:10:17 Data Engineer Roadmap
00:24:24 Data Engineer Certifications
00:29:03 Top skills for Data Engineer
00:35:03 Reasons to become data engineer
00:41:32 Hadoop Ecosystem
00:58:12 Spark

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✅ About Post Graduate Program In Data Engineering
Fast-track your career as a Data Engineering professional with our Data Engineering course. This course covers Big Data and Data Engineering concepts, the Hadoop ecosystem, Apache Python basics, AWS EMR, Quicksight, Sagemaker, the AWS cloud platform, and Azure services.

✅ Skills Covered
- Real Time Data Processing
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- Apache Hadoop
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👉 Listen to what millions of users say about our courses! https://www.simplilearn.com/reviews?utm_campaign=26August2023DataEngineerCrashCourse2023&utm_medium=Description&utm_source=youtube

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 nebuloustdg@gmail.com

🔗 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

--

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

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

Learn how to use GraphQL in this tutorial for beginners. Throughout this course, you'll learn the core principle of this popular database, explore its advantages over traditional REST APIs, and gain the practical skills to design and implement robust data-driven applications.

✏️ Course developed by @NetNinja
Net Ninja website: https://netninja.dev
NetNinja Node.js Crash Course: https://www.youtube.com/watch?v=zb3Qk8SG5Ms&list=PL4cUxeGkcC9jsz4LDYc6kv3ymONOKxwBU&index=1

💻 Code: https://github.com/iamshaunjp/graphql-crash-course

⭐️ Contents ⭐️
⌨️ (0:00:00) What is GraphQL?
⌨️ (0:10:30) Query Basics
⌨️ (0:19:44) Making a GraphQL Server (with Apollo)
⌨️ (0:25:42) Schema & Types
⌨️ (0:36:19) Resolver Functions
⌨️ (0:46:24) Query Variables
⌨️ (0:56:02) Related Data
⌨️ (1:09:41) Mutations (Adding & Deleting Data)
⌨️ (1:21:20) Update Mutation

🎉 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

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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 CAPM® Certification training offered by Simplilearn. This video compounded by 3 lessons of the CAPM Certification Course. And the lessons as follows,
1. Lesson 1 : Introduction to CAPM
2. Lesson 2 : Project Management Framework
3. Lesson 3 : Project Management Process

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✅About Post Graduate Program In Project Management

This project management certificate program will cover strategization and management - project, program, risk, quality, complexity management, customer-centric digital transformation, PMO implementation, and agile and scrum skills; and allow you to earn 146 Professional Development Units (PDUs) for maintaining CCR for PMI certifications.

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- Receive Post Graduate Program Certificate and Alumni Association Membership from UMass Amherst.
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This video on the "Artificial Intelligence full course" video cover all the topics you need to know to become a master in AI and ML. It covers all the basics of Machine Learning, the different types of Machine Learning, and the various applications of Machine Learning used in different industries. This video will also help us understand the basics of artificial intelligence. We will look at the future of AI and listen to some of the industry experts and learn what they have to say about AI. Finally, you will learn the Top 10 Artificial Intelligence Technologies In 2022.
Below are the topics covered in this AI and ML full course:

Artificial Intelligence Full Course 2022
Artificial Intelligence Basics
Top 10 AI Technologies 2022
Top 10 AI Companies for 2022
Machine Learning Algorithms
Linear Regression
Decision Tree
SVM
Clustering
K-means Clustering
Logistic Regression
KNN
Perceptron
RNN
Keras
CNN classification
Sequential Model

✅Subscribe to our Channel to learn more about the top Technologies: https://www.youtube.com/user/Simplilearn

⏩ Check out the Artificial Intelligence tutorial videos: https://www.youtube.com/watch?v=ad79nYk2keg&list=PLEiEAq2VkUULyr_ftxpHB6DumOq1Zz2hq

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What Exactly is Machine Learning?
A good start at a Machine Learning definition is that it is a core sub-area of Artificial Intelligence (AI). ML applications learn from experience (data) like humans without direct programming. When exposed to new data, these applications learn, grow, change, and develop by themselves. In other words, with Machine Learning, computers find insightful information without being told where to look. Instead, they do this by leveraging algorithms that learn from data in an iterative process.

What is Artificial Intelligence?
Artificial Intelligence is a method of making a computer, a computer-controlled robot, or software think intelligently like the human mind. AI is accomplished by studying the patterns of the human brain and by analyzing the cognitive process. The outcome of these studies develops intelligent software and systems.

➡️ 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
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- 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

✅ Skills Covered

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

Learn the basics of Django by building a simple online marketplace where people can buy and sell items. You will learn how to implement:
- Authentication
- Communication between users
- Dashboard for your items
- Form handling and customizations
- and more

✏️ The course is developed by CodeWithStein. Check out his channel:
https://www.youtube.com/c/CodeWithStein
CodeWithStein on twitter: https://twitter.com/codewithstein

💻 Code: https://github.com/SteinOveHelset/puddle

⭐️ Contents ⭐️
⌨️ (0:00:00) Demo
⌨️ (0:02:01) Introduction
⌨️ (0:02:20) Setting up
⌨️ (0:06:00) First app
⌨️ (0:24:51) Items
⌨️ (0:44:30) Item detail
⌨️ (0:55:56) Signing up
⌨️ (1:10:06) Logging in
⌨️ (1:15:44) Adding items
⌨️ (1:28:25) Dashboard
⌨️ (1:32:36) Delete items
⌨️ (1:36:58) Edit items
⌨️ (1:40:01) Searching
⌨️ (1:53:43) Communication
⌨️ (2:23:00) Summary

🎉 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

React: Use Advanced JavaScript in React Render Method


#100DaysOfCode

Learn how to use Figma Variants to design a scalable mobile app. Variants can streamline your frontend design process by allowing you to group and organize similar components into a single container.

✏️ Ahmet Efeoglu developed this course. Check out his channel: https://www.youtube.com/channe....l/UCSziSLMFFNT4PaRQh

🔗 Tutorial file link: https://www.figma.com/file/FrL....R3t9jZ9X8psPdmztdlh/
🔗 Homework file link: https://www.figma.com/file/8js....2feuv6LdhmvVtBXkC2L/

⌨️ (0:00:18) Intro
⌨️ (0:02:13) Accessing Tutorial and Homework Files
⌨️ (0:04:24) Project Overview
⌨️ (0:05:27) Recommending Personal and freeCodeCamp Channel
⌨️ (0:06:25) Basics Overview
⌨️ (0:08:22) Learning The Frame Functionality
⌨️ (0:10:25) Learning The Autolayout Functionality
⌨️ (0:14:39) Learning The Component Functionality
⌨️ (0:18:55) Learning The Variant Functionality
⌨️ (0:21:42) Creating The Type System
⌨️ (0:28:41) Creating The Color Palette/System
⌨️ (0:35:54) Creating The Icon Set
⌨️ (0:41:34) Creating Input Variants
⌨️ (0:52:23) Creating Large Button Variant
⌨️ (1:00:47) Designing Sign Up and Login Screen
⌨️ (1:18:46) Creating Status Bar Variant
⌨️ (1:23:14) Creating The Filter Variant
⌨️ (1:27:40) Creating Bottom Navigation Variant
⌨️ (1:35:02) Creating Image Card Variant
⌨️ (1:49:27) Updating Input Variant
⌨️ (1:57:31) Designing The Discover Screens
⌨️ (2:15:20) Creating Large Avatar Variant
⌨️ (2:24:05) Creating Small Button Variant
⌨️ (2:32:45) Creating The Benefit Card Variant
⌨️ (2:46:45) Designing Details Screen

🎉 Thanks to our Champion and Sponsor supporters:
👾 Raymond Odero
👾 Agustín Kussrow
👾 aldo ferretti
👾 Otis Morgan
👾 DeezMaster

--

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

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

React: Pass a Callback as Props


#100DaysOfCode.

Use a span to Target Inline Elements



#100daysofcode




you can do it

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Timestamps :
00:00:00 - Introduction
00:01:38 - Installing Code Editor (one from Froala/UltraEdit/VSCode)
00:05:40 - How do websites work?
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00:36:38 - Level 2
01:03:27 - Level 3
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