This video explains the Transformer architecture in a very detailed way, including most math formulas in the paper, and the neural network operations behind it. The Transformer is the foundation of many powerful language models like BERT, GPT3, RoBERTa, XLNET, ELECTRA, T5. Understanding how it works in detail might help you modify, optimize, or improve it in the way you want.


Connect
Linkedin https://www.linkedin.com/in/xue-yong-fu-955723a6/
Twitter https://twitter.com/home
Email [email protected]

0:00 - Intro
1:10 - Architecture overview
1:56 - Encoder
3:58 - Residual connection & layer normalization
6:59 - Decoder
11:14 - Attention mechanism
14:30 - Scaled dot-product attention
20:22 - Learned projection layers
26:32 - Multi-head attention
28-39 - Encoder-decoder attention
31:18 - Encoder self-attention
31:34 - Decoder self-attention
33:58 - Position-wise feedforward network
36:41 - Word embedding
39:34 - Positional encoding
47:37 - Why self-attention

What Is GPT-3 Series
https://www.youtube.com/playli....st?list=PLoS8jSwcU-c

Paper: Attention Is All You Need
https://arxiv.org/abs/1706.03762

Abstract
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks that include an encoder and a decoder. The best
performing models also connect the encoder and decoder through an attention mechanism. We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. Experiments on two machine translation tasks show these models to be superior in quality while being more parallelizable and requiring significantly less time to train. Our model achieves 28.4 BLEU on the WMT 2014 English- to-German translation task, improving over the existing best results, including ensembles, by over 2 BLEU. On the WMT 2014 English-to-French translation task, our model establishes a new single-model state-of-the-art BLEU score of 41.0 after training for 3.5 days on eight GPUs, a small fraction of the training costs of the best models from the literature. We show that the Transformer generalizes well to other tasks by applying it successfully to English constituency parsing both with large and limited training data.

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This video will introduce you to SQL Server. The tutorial will give you insights into the usage of SQL Server. You will get to know about SQL Server editions. Further, you will learn about the advantages of SQL Server Instances. The demonstration examples will educate you more on the topic.

The following topics are covered in the tutorial:

What is SQL Server?
Usage of SQL Server
SQL Server Editions
Advantages of SQL Server Instances
Hands-on Demonstration

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SQL Certification Training Course:
Master SQL and improve your career prospects with Simplilearn’s SQL Database Training Course. Functional knowledge of SQL (Structured Query Language), the leading programming language for relational database management systems, is in high demand and can set you apart in the job market. This SQL certification course gives you all of the information you need to successfully start working with SQL databases and make use of the database in your applications. Learn how to correctly structure your database, author efficient SQL statements, and clauses, and manage your SQL database for scalable growth.

Key Features:
✅ In-depth coverage of SQL fundamentals
✅ Covers all of the important query tools and SQL commands
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Benefits:
SQL, though an old language, is highly significant today as companies across the world are gathering massive amounts of data for their growth. SQL consistently ranks high in the most-requested tech skills and learning it will add great value to your array of skills.

Eligibility:
This online SQL certification course is ideal for freshers, programmers, software developers, and testing professionals who want to learn SQL. It’s also ideal for marketing professionals and salespeople who want to better understand their company’s data.

Pre-requisites:
There are no prerequisites for this database training course. This course can be taken up by anyone who wants to learn SQL.

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As with his previous incarnations, Godzilla can release pulses of radioactive energy. He first demonstrated this in Godzilla: King of the Monsters where, after absorbing the radiation of a nuclear blast and Mothra’s life force, Godzilla starts to heat up with a fiery red glow, burning and melting objects in his vicinity while becoming completely immune to Ghidorah's gravity beams. This energy overload grants him control over tremendously powerful thermonuclear pulses that incinerates most of Ghidorah's body and a large portion of Boston with him. The shape of these particular pulses also resembles Mothra's wings while the sound of the explosions resembles Mothra's screech, for this ability is a result of Godzilla and Mothra's symbiotic bond, and can only be used in the most specific of circumstances.

I edited the scene a little, removing some irrelevant humans parts, keeping it as seamless and objective as possible, focusing only on the Kaijus.

Source: 3840x2160
Upscale: 7680x4320

© 2019 Warner Bros. Entertainment Inc.

#Godzilla​ #KingGhidorah #8K​ #Kaiju

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This video tutorial on probability and statistics gives a basic overview of the chi-square distribution. It explains how to use the chi-square distribution to conduct goodness of fit test to determine whether the null hypothesis should be accepted or rejected.

In this video, we will discuss -
00:00 Research and Null Hypothesis
01:19 Expected and Observed Frequency
01:47 Chi-Square Test
03:56 Example

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About Simplilearn Data Scientist Program:
This Data Science course, in collaboration with IBM, features exclusive IBM hackathons, masterclass, and Ask-me-anything sessions for the best training experience. This Data Scientist certification training provides hands-on exposure to key technologies including R, Python, Machine Learning, Tableau, Hadoop, and Spark via live interaction with practitioners, practical labs, and industry projects.

Learning Objectives of Simplilearn Data Scientist Program:
Data Scientist is one of the hottest professions. IBM predicts the demand for Data Scientists will rise by 28% by 2020. Simplilearn's Data Science certification course co-developed with IBM encourages you to master skills including statistics, hypothesis testing, data mining, clustering, decision trees, linear and logistic regression, data wrangling, data visualization, regression models, Hadoop, Spark, PROC SQL, SAS Macros, recommendation engine, supervised, and unsupervised learning and more.

Key Features of Simplilearn Data Scientist Program:
✅ Exclusive Hackathons and Live interaction with IBM leadership (Includes live Master Classes and Ask me anything sessions)
✅ 220+ hours of live interactive learning (Live Data Science online classes by industry experts)
✅ Capstone and 15+ real-life Data Science projects (Built on datasets of Amazon, UBER, Comcast)
✅ Simplilearn JobAssist™ (Get noticed by the top hiring companies)

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Extended motivational speech to study deep learning mathematically.

I gave this talk at an NSF Town Hall where the goal was to discuss successes of deep learning especially in light of more traditional fields (other talks can be found here: https://www.nsf.gov/events/event_summ.jsp?cntn_id=304013&org=CISE).

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This Random Forest Algorithm tutorial will explain how the Random Forest algorithm works. By the end of this video, you will be able to understand what is Machine Learning, what is a Classification problem, applications of Random Forest, why we need Random Forest, how it works with simple examples, and how to implement a Random Forest algorithm in Machine Learning. This video is a part of the Machine Learning with Python Series.

Below are the topics covered in this Random Forest Algorithm tutorial:
00:00 - 02:08 Applications of Random Forest Algorithm
02:08 - 02:59 Agenda
02:59 - 04:07 Classification Algorithms
04:07 - 05:36 Why Random Forest?
05:36 - 06:40 What is Random Forest Algorithm?
06:40 - 11:01 What is a Decision Tree?
11:01 - 14:18 How does the Decision Tree algorithm work?
14:18 - 17:27 How does the Random Forest algorithm work?
17:27 - 45:34 Use Case - IRIS Flower Analysis using Python

Dataset Link - https://drive.google.com/drive..../folders/1MQ5Nnhj3gs


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What is Random Forest Algorithm?
The random forest algorithm is a supervised machine learning algorithm that takes randomly selected data and creates different decision trees. It then makes the collection of votes from trees to decide the class of the test object.

You can also go through the Slides here: https://goo.gl/K8T4tW

Machine Learning Articles: https://www.simplilearn.com/what-is-artificial-intelligence-and-why-ai-certification-article?utm_campaign=Random-Forest-Tutorial-eM4uJ6XGnSM&utm_medium=Tutorials&utm_source=youtube

To gain in-depth knowledge of Machine Learning, check our Machine Learning certification training course: https://www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course?utm_campaign=Random-Forest-Tutorial-eM4uJ6XGnSM&utm_medium=Tutorials&utm_source=youtube

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About Simplilearn Machine Learning course:

A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars. This Machine Learning course prepares engineers, data scientists and other professionals with the knowledge and hands-on skills required for certification and job competency in Machine Learning.

- - - - - - -

What skills will you learn from this Machine Learning course?

By the end of this Machine Learning course, you will be able to:

1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling.
2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project.
3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning.
4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.

- - - - - - -

Who should take this Machine Learning Training Course?

We recommend this Machine Learning training course for the following professionals in particular:

1. Developers aspiring to be a data scientist or Machine Learning engineer
2. Information architects who want to gain expertise in Machine Learning algorithms
3. Analytics professionals who want to work in Machine Learning or artificial intelligence
4. Graduates looking to build a career in data science and Machine Learning

- - - - - -

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This Complete Machine Learning Course video will help you understand and learn Machine Learning in detail. This Machine Learning Tutorial is ideal for both beginners as well as professionals who want to master Machine Learning concepts & practice.

All presentation files for the Machine Learning course as PDF for as low as ₹200 (INR): https://forms.gle/VeD1hi5e2n6Ced236

Github repository link for Colab Notebooks: https://github.com/siddhardhan....23/Complete-Machine-

All Datasets Link: https://drive.google.com/drive..../folders/1NEs0rpFelf

Timestamp for the topics covered in this Machine Learning Course video:

00:00 Introduction
4:22 AI vs ML vs DL
9:40 Types of Machine Learning
16:05 Supervised Learning & its Types
21:34 Unsupervised Learning & its Types
27:55 Deep Learning
36:11 Google Colaboratory - basics
45:53 Python Basics
1:08:36 Basic Data types in Python
1:28:40 List, Tuple, Set, Dictionary
1:55:36 Operators in Python
2:14:50 If Else Statement in Python
2:28:42 Loops in Python
2:44:20 Functions in Python
2:59:16 Numpy Tutorial
3:44:03 Pandas Tutorial
4:33:06 Matplotlib Tutorial
5:01:25 Seaborn Tutorial
5:37:34 Data Collection for ML
5:50:46 Importing datasets through Kaggle API
6:05:15 Handling Missing Values
6:29:58 Data Standardization
6:49:30 Label Encoding
7:06:56 Train Test Split
7:19:16 Handling Imbalanced Dataset
7:38:24 Feature Extraction of Text data
7:52:03 Numerical dataset processing
8:11:42 Textual data Processing
8:47:12 ML Use case 1: Rock vs Mine Prediction
9:35:35 ML Use case 2: Diabetes Prediction
10:38:53 ML Use case 3: Spam Mail Prediction


Machine Learning Projects Playlist: https://youtube.com/playlist?l....ist=PLfFghEzKVmjvuSA

Hello everyone! I am setting up a donation campaign for my YouTube Channel. If you like my videos and wish to support me financially, you can donate through the following means:

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ChatGPT Full Course 2024 by simplilearn is a latest variant of ChatGPT Full Course. the couse will guide the aspiring AI Engineers to learn the critical AI and machine learning and ChatGPT AI models from the very Basic To Advanced This ChatGPT Tutorial by simplileatn will cover how to use ChatGPT 4 Omni, Data Analysis with chatGPT, programming with chatgpt, automation with chatgpt and much more. The ChatGPT full course with 4 Omni demonstration will cover the following topics:

00:00:00 ChatGPT Full Course For Beginners 2023
00:02:22 Top AI Tools
00:00:07:50 What is GPT 4?
00:13:52 Automate Excel using ChatGPT
01:24:12 How to Build a Website Using ChatGPT
02:06:35 How To Use ChatGPT For Web Development
02:32:22 Can ChatGPT Solve LeetCode Problems?
04:02:21 Create a Telegram Bot Using ChatGPT
04:19:21 Automate WhatsApp using ChatGPT
04:29:45 Build a Game using Python and ChatGPT
04:54:25 ChatGPT in Cybersecurity
05:24:09 ChatGPT for UI/UX Design
06:10:28 How to use ChatGPT for SEO?
07:02:19 Chat GPT for Content Creation
07:06:14 Master SEO Content Using ChatGPT
7:11:53 Explore 10 Mind-Blowing GPTs Inside ChatGPT - WebPilot Will Amaze You
7:23:43 OpenAI ChatGPT-4o
7:40:21 How To Use ChatGPT Memory ?
7:45:51 ChatGPT For Voice Activated AI Assiatant
7:58:04 How To Use ChatGPT Plugins - Step-By-Step Guide
8:07:15 ChatGPT 4.0 vs Gemini 1.5
8:17:11 WEB SCRAPPING Using CHATGPT
8:21:38 How To Use AI In Excel ?
8:52:36 ChatGPT Made This Excel Dashboard 😱😱
9:03:03 How To Write Resume Using ChatGPT
9:08:40 What Is Multimodal AI?

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#ChatGPT #CHatGPTFullCourse #Chatgpt4o #AI #2024 #Simplilearn

➡️ About Artificial Intelligence Engineer

This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions.

IBM is a leader in AI and Machine Learning technology verticals for 2021. This AI masters course will prepare students for Artificial Intelligence and Data Analytics careers.

✅ Key Features

- Add the IBM Advantage to your Learning
- 25 Industry-relevant Projects and Integrated labs
- Immersive Learning Experience
- Simplilearn's JobAssist helps you get noticed by top hiring companies

✅ Skills Covered

- ChatGPT
- Flask
- Matplotlib
- django
- Python
- Numpy
- Pandas
- SciPy
- Keras
- OpenCV
- And Many More…

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🔥Edureka Tensorflow Training: https://www.edureka.co/ai-deep....-learning-with-tenso
This Edureka LSTM Explained video will help you in understanding why we need Recurrent Neural Networks (RNN) and what exactly it is. It also explains few issues with training a Recurrent Neural Network and how to overcome those challenges using LSTMs.
00:00 Introduction
00:36 Agenda
00:47 Introduction to NLP
01:46 Ways to Process Text Data
02:57 Recurrent Neural Networks
22:02 Long Short-term Memory
51:46 LSTM Use Cases
53:45 Real Time Applications of LSTM

🔹Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE
🔹Check our complete Deep Learning With TensorFlow Blog Series: http://bit.ly/2sqmP4s

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#Edureka #DeepLearningEdureka #LSTMExplained #NeuralNetworks #DeepLearningTraining #DeepearningTutorial #EdurekaTraining

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!

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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. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.


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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 who are leading a team of analysts

3. Business Analysts who want to understand Deep Learning (ML) Techniques

4. Information Architects who want to gain expertise in Predictive Analytics

5. Professionals who want to captivate and analyze Big Data

6. Analysts wanting to understand Data Science methodologies

However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio.

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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 [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).

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In this video I show you examples of how to perform transfer learning in various ways, either having trained a model yourself, using keras.applications or the TensorFlow hub. I also show how you can then pick out specific chunks of the pretrained models and remove specific layers, and then how you could freeze those layers, add layers on top and perform fine tuning.

Download TensorFlow Hub (w. pip it's pip install tensorflow-hub):
https://anaconda.org/conda-forge/tensorflow-hub

I learned a lot and was inspired to make these TensorFlow videos by the TensorFlow Specialization on Coursera. Below you'll find both affiliate and non-affiliate links, the pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
affiliate: https://bit.ly/3t3tgI5
non-affiliate: https://bit.ly/3kZgN5B

GitHub Repository:
https://github.com/aladdinpers....son/Machine-Learning

✅ Equipment I use and recommend:
https://www.amazon.com/shop/aladdinpersson

❤️ Become a Channel Member:
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✅ One-Time Donations:
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GitHub - https://github.com/aladdinpersson

TensorFlow Playlist:
https://www.youtube.com/playli....st?list=PLhhyoLH6Ijf

In this video I walk through a general text generator based on a character level RNN coded with an LSTM in Pytorch in the application of generating new baby names.

People often ask what courses are great for getting into ML/DL and the two I started with is ML and DL specialization both by Andrew Ng. Below you'll find both affiliate and non-affiliate links if you want to check it out. The pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
ML Course (affiliate): https://bit.ly/3qq20Sx
DL Specialization (affiliate): https://bit.ly/30npNrw
ML Course (no affiliate): https://bit.ly/3t8JqA9
DL Specialization (no affiliate): https://bit.ly/3t8JqA9

GitHub Repository:
https://github.com/aladdinpers....son/Machine-Learning

✅ Equipment I use and recommend:
https://www.amazon.com/shop/aladdinpersson

❤️ Become a Channel Member:
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✅ One-Time Donations:
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PyTorch Playlist:
https://www.youtube.com/playli....st?list=PLhhyoLH6Ijf

🔥Edureka AWS Architect Certification Training: https://www.edureka.co/aws-certification-training
This video is about the features and benefits of AWS Kinesis. It shows how AWS Kinesis can be effectively used for processing the streaming data. The topics that we will cover in this session are as follows:
· What is AWS Kinesis?
· Advantages
· Capabilities
· Use Cases
· Kinesis vs SQS
· How it works?
· Demo

Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV
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#edureka #EdurekaAWS #AWSKinesis #awstraining #cloudcomputing
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How does it work?
1. This is a 5 Week Instructor-led Online Course.
2. The course consists of 30 hours of online classes, 30 hours of assignment, 20 hours of project
3. 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.
4. You will get Lifetime Access to the recordings in the LMS.
5. At the end of the training, you will have to complete the project based on which we will provide you a Verifiable Certificate!
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About the Course

AWS Architect Certification Training from Edureka is designed to provide in-depth knowledge about Amazon AWS architectural principles and its components. The sessions will be conducted by Industry practitioners who will train you to leverage AWS services to make the AWS cloud infrastructure scalable, reliable, and highly available. This course is completely aligned to AWS Architect Certification - Associate Level exam conducted by Amazon Web Services.

During this AWS Architect Online training, you'll learn:
1. AWS Architecture and different models of Cloud Computing
2. Compute Services: Amazon EC2, Auto Scaling, and Load Balancing, AWS Lambda, Elastic Beanstalk
3. Amazon Storage Services: EBS, S3 AWS, Glacier, CloudFront, Snowball, Storage Gateway
4. Database Services: RDS, DynamoDB, ElastiCache, RedShift
5. Security and Identity Services: IAM, KMS
6. Networking Services: Amazon VPC, Route 53, Direct Connect
7. Management Tools: CloudTrail, CloudWatch, CloudFormation, OpsWorks, Trusty Advisor
8. Application Services: SES, SNS, SQS
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Course Objectives

On completion of the AWS Architect Certification Training, the learner will be able to:
1. Design and deploy scalable, highly available, and fault-tolerant systems on AWS
2. Understand the lift and shift of an existing on-premises application to AWS
3. Ingress and egress of data to and from AWS
4. Identifying appropriate use of AWS architectural best practices
5. Estimating AWS costs and identifying cost control mechanisms
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Pre-requisites

There are no specific prerequisites for this course. Any professional who has an understanding of IT Service Management can join this training. There is no programming knowledge needed and no prior AWS experience required.
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If you are looking for live online training, write back to us at [email protected] or call us at the US: + 18338555775 (Toll-Free) or India: +91 9606058406 for more information.

⚙️ WEBINAR: Build an AI Operating System for Your Business in 7 Days: https://bit.ly/aios-blueprint-webinar
📈 Get daily AIOS Workshops from me in my Accelerator: https://bit.ly/4rG6nJt

📚 Join the #1 community for AI entrepreneurs and connect with 280k+ members: https://bit.ly/46myCUX
🤝 Ready to transform your business with AI? Let's talk: https://bit.ly/3OUpjFI
📋 Get our FREE 14-day playbook for finding high-impact AI opportunities in any business: https://bit.ly/14-day-playbook

My Vlog/BTS Channel: https://bit.ly/LiamOttleyVlogs

I’m breaking down my AI Operating System built on Claude Code—how I’m automating 60–70% of my workload and running multiple businesses from a phone using a proper tool harness (not brittle bots). You’ll see how to set up Context OS (folder structure, documentation, priming), then wire a Data OS that merges P&L, Google Analytics, YouTube, marketing, and sales into local mission-control dashboards you can query via Telegram.

⏱️ Timestamps:
00:00 What We're Covering
01:00 The AIOS that automates 60–70% of your workload
02:00 Claude Code runs your company from Telegram
03:37 Build the stack: Context setup and layered automation
06:51 Data OS and “Mission Control” dashboards
10:24 Meeting Intelligence + Daily Brief
14:26 Live webinar, templates, and next steps

A quick look at CBOW and how it looks like it in code. I explained how this model works in the previous example so check that out before you look at this one to get a better understanding.

Timestamps:
0:00 - Introduction
0:48 - Imports
0:53 - CBOW model
5:10 - Example of how to train it
8:52 - Ending