🔥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

🔴Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV

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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!

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

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.


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

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.

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

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).

Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka

⚙️ 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

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:
https://www.youtube.com/channe....l/UCkzW5JSFwvKRjXABI

✅ One-Time Donations:
Paypal: https://bit.ly/3buoRYH
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▶️ You Can Connect with me on:
Twitter - https://twitter.com/aladdinpersson
LinkedIn - https://www.linkedin.com/in/al....addin-persson-a95384
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:
https://www.youtube.com/channe....l/UCkzW5JSFwvKRjXABI

✅ One-Time Donations:
Paypal: https://bit.ly/3buoRYH
Ethereum: 0xc84008f43d2E0bC01d925CC35915CdE92c2e99dc

▶️ You Can Connect with me on:
Twitter - https://twitter.com/aladdinpersson
LinkedIn - https://www.linkedin.com/in/al....addin-persson-a95384
GitHub - https://github.com/aladdinpersson

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
----------------------------------------------------------------------------
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!
----------------------------------------------------------------------------
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
----------------------------------------------------------------------------
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
----------------------------------------------------------------------------
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.
----------------------------------------------------------------------------
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.

IQ is supposed to measure intelligence, but does it? Head to https://brilliant.org/veritasium to start your free 30-day trial, and the first 200 people get 20% off an annual premium subscription.

If you’re looking for a molecular modeling kit, try Snatoms – a kit I invented where the atoms snap together magnetically – https://ve42.co/SnatomsV

▀▀▀
A huge thank you to Emeritus Professor Cecil R. Reynolds and Dr. Stuart J. Ritchie for their expertise and time.

Also a massive thank you to Prof. Steven Piantadosi and Prof. Alan S. Kaufman for helping us understand this complicated topic. As well as to Jay Zagrosky from Boston University's Questrom School of Business for providing data from his study.

▀▀▀
References:
Kaufman, A. S. (2009). IQ testing 101. Springer Publishing Company.

Reynolds, C. R., & Livingston, R. A. (2021). Mastering modern psychological testing. Springer International Publishing.

Ritchie, S. (2015). Intelligence: All that matters. John Murray.

Spearman, C. (1961). " General Intelligence" Objectively Determined and Measured. - https://ve42.co/Spearman1904

Binet, A., & Simon, T. (1907). Le développement de l'intelligence chez les enfants. L'Année psychologique, 14(1), 1-94.. - https://ve42.co/Binet1907

Intelligence Quotient, Wikipedia - https://ve42.co/IQWiki

Radiolab Presents: G. - https://ve42.co/RadioLabG

McDaniel, M. A. (2005). Big-brained people are smarter: A meta-analysis of the relationship between in vivo brain volume and intelligence. Intelligence, 33(4), 337-346. - https://ve42.co/McDaniel2005

Deary, I. J., Strand, S., Smith, P., & Fernandes, C. (2007). Intelligence and educational achievement. Intelligence, 35(1), 13-21. - https://ve42.co/Deary2007

Lozano-Blasco, R., Quílez-Robres, A., Usán, P., Salavera, C., & Casanovas-López, R. (2022). Types of Intelligence and Academic Performance: A Systematic Review and Meta-Analysis. Journal of Intelligence, 10(4), 123. - https://ve42.co/Blasco2022

Kuncel, N. R., & Hezlett, S. A. (2010). Fact and fiction in cognitive ability testing for admissions and hiring decisions. Current Directions in Psychological Science, 19(6), 339-345. - https://ve42.co/Kuncel2010

Laurence, J. H., & Ramsberger, P. F. (1991). Low-aptitude men in the military: Who profits, who pays?. Praeger Publishers. - https://ve42.co/Laurence1991

Gregory, H. (2015). McNamara's Folly: The Use of Low-IQ Troops in the Vietnam War; Plus the Induction of Unfit Men, Criminals, and Misfits. Infinity Publishing.

Gottfredson, L. S., & Deary, I. J. (2004). Intelligence predicts health and longevity, but why?. Current Directions in Psychological Science, 13(1), 1-4. - https://ve42.co/Gottfredson2004

Sanchez-Izquierdo, M., Fernandez-Ballesteros, R., Valeriano-Lorenzo, E. L., & Botella, J. (2023). Intelligence and life expectancy in late adulthood: A meta-analysis. Intelligence, 98, 101738. - https://ve42.co/Izquierdo2023

Zagorsky, J. L. (2007). Do you have to be smart to be rich? The impact of IQ on wealth, income and financial distress. Intelligence, 35(5), 489-501. - https://ve42.co/Zagorsky2007

Strenze, T. (2007). Intelligence and socioeconomic success: A meta-analytic review of longitudinal research. Intelligence, 35(5), 401-426. - https://ve42.co/Strenze2007

Deary, I. J., Pattie, A., & Starr, J. M. (2013). The stability of intelligence from age 11 to age 90 years: the Lothian birth cohort of 1921. Psychological science, 24(12), 2361-2368. - https://ve42.co/Deary2013

Flynn, J. R. (1987). Massive IQ gains in 14 nations: What IQ tests really measure. Psychological bulletin, 101(2), 171. - https://ve42.co/Flynn1987

Why our IQ levels are higher than our grandparents' | James Flynn, TED via YouTube - https://www.youtube.com/watch?v=9vpqilhW9uI

Duckworth, A. L., Quinn, P. D., Lynam, D. R., Loeber, R., & Stouthamer-Loeber, M. (2011). Role of test motivation in intelligence testing. Proceedings of the National Academy of Sciences, 108(19), 7716-7720. - https://ve42.co/Duckworth2011

Kulik, J. A., Bangert-Drowns, R. L., & Kulik, C. L. C. (1984). Effectiveness of coaching for aptitude tests. Psychological Bulletin, 95(2), 179. - https://ve42.co/Kulik1984

▀▀▀
Special thanks to our Patreon supporters:
Adam Foreman, Amadeo Bee, Anton Ragin, Balkrishna Heroor, Benedikt Heinen, Bernard McGee, Bill Linder, Burt Humburg, Dave Kircher, Diffbot, Evgeny Skvortsov, Gnare, John H. Austin, Jr., john kiehl, Josh Hibschman, Juan Benet, KeyWestr, Lee Redden, Marinus Kuivenhoven, MaxPal, Meekay, meg noah, Michael Krugman, Orlando Bassotto, Paul Peijzel, Richard Sundvall, Sam Lutfi, Stephen Wilcox, Tj Steyn, TTST, Ubiquity Ventures

▀▀▀
Written by Derek Muller, Casper Mebius, & Petr Lebedev
Edited by Trenton Oliver
Filmed by Derek Muller, Han Evans, & Raquel Nuno
Animation by Fabio Albertelli & Ivy Tello
Additional video/photos supplied by Getty Images & Pond5
Music from Epidemic Sound
Produced by Derek Muller, Casper Mebius, & Han Evans

🔥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

🔴Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV

Edureka Community: https://bit.ly/EdurekaCommunity
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Telegram: https://t.me/edurekaupdates
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Meetup: https://www.meetup.com/edureka/

#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!

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

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.


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

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.

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

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).

Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka

🔥Data Analyst Masters Program (Discount Code - YTBE15) - https://www.simplilearn.com/data-analyst-masters-certification-training-course?utm_campaign=oHm6uf9YOt0&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥IITK - Professional Certificate Course in Data Analytics and Generative AI (India Only) - https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=oHm6uf9YOt0&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Purdue - Post Graduate Program in Data Analytics - https://www.simplilearn.com/pgp-data-analytics-certification-training-course?utm_campaign=oHm6uf9YOt0&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Caltech - Data Analytics Bootcamp (US Only) - https://www.simplilearn.com/data-analytics-bootcamp?utm_campaign=oHm6uf9YOt0&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥IITG - Professional Certificate Program in Data Analytics and Generative AI (India Only) - https://www.simplilearn.com/iitg-generative-ai-data-analytics-program?utm_campaign=oHm6uf9YOt0&utm_medium=DescriptionFirstFold&utm_source=Youtube

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

In this video, we will build a Vision Language Model (VLM) from scratch, showing how a multimodal model combines computer vision and natural language processing for vision QA. GitHub below ↓

Want to support the channel? Hit that like button and subscribe!

GitHub Link of the Code
https://github.com/uygarkurt/VLM-PyTorch

Dataset
https://huggingface.co/dataset....s/uygarkurt/simple-i

Implement and Train ViT From Scratch for Image Recognition - PyTorch
https://youtu.be/Vonyoz6Yt9c

Implement Llama 3 From Scratch - PyTorch
https://youtu.be/lrWY4O5kUTY

Fine-Tune Visual Language Models (VLMs) - HuggingFace, PyTorch, LoRA, Quantization, TRL
https://youtu.be/3ypHZayanBI

ViT (Vision Transformer) - An Image Is Worth 16x16 Words (Paper Explained)
https://youtu.be/8phM16htKbU

What should I implement next? Let me know in the comments!

00:00 VLM Explanation
04:42 Downloading Dataset
06:39 Imports
10:09 Hyperparameters
12:37 Data Processing
16:03 ViT Definition
19:05 VLM Implementation
41:40 Sample Inference
45:20 Data Loaders
52:46 Training Loop
57:50 Inference

References
https://github.com/AviSoori1x/seemore

Buy me a coffee! ☕️
https://ko-fi.com/uygarkurt

In this video, Dr. Raj Dandekar (MIT PhD) teaches you how to build a production level SLM entirely from scratch.

You will learn the following:

(1) Creating the dataset
(2) Tokenizing the dataset
(3) Creating input-target pairs
(4) Creating the entire SLM architecture
(5) Setup the SLM for pre-training
(6) Pre-training the SLM
(7) Inference

Google Colab Notebook: https://colab.research.google.....com/drive/1k4G3G5MxY

I sit down with my dear friend Vin (Internet Vin) for a deep, hands-on walkthrough of how he uses Obsidian and Claude Code together as a thinking partner, idea generator, and personal operating system. Vin demonstrates live how Claude Code can read, reference, and surface patterns across an entire Obsidian vault of interlinked markdown files — turning years of personal notes into actionable insights, project ideas, and even custom commands. This episode covers everything from the basic setup to advanced workflows like tracing how ideas evolve over time, generating contextual startup ideas, and delegating tasks to autonomous agents. If you are serious about getting the most out of LLMs, this is the episode that shows you how your own writing becomes the fuel.

Timestamps
00:00 – Intro
02:10 – What Is Claude Code?
06:45 – What Is Obsidian?
10:28 – Obsidian CLI: Giving Claude Code Access to Your Vault
14:53 – Thinking Tools: Ghost, Challenge, Emerge, Drift, Ideas, Trace
22:51 – The Role of Reflection in Building a Powerful Vault
25:15 – How This Relates to OpenClaw (Autonomous Agents)
29:13 – Live Demo: /Connect — Bridging Two Domains
31:25 – Meeting Notes & External Info
33:23 – Why Vin Keeps a Strict Separation: Human-Written vs. Agent-Written
35:42 – How Claude Code uses Obsidian
41:46 – Live Demo: /Ideas — Generating Actionable Ideas from Your Vault
47:10 – The /Graduate Command
50:29 – Why Obsidian Is the Missing Link for AI Companies
54:53 – The Alpha: Why 99.99% of People Won't Do This
57:38 – Closing Thoughts & Where to Follow Vin

Key Points

* Claude Code is a command-line agent that can control your computer through natural language — and its power multiplies when you feed it rich, persistent context files instead of re-explaining projects every session.
* Obsidian is uniquely valuable because it sits on top of interlinked markdown files; the new Obsidian CLI lets Claude Code see both the files and the relationships between them.
* Vin built custom slash commands (/trace, /connect, /ideas, /ghost, /drift, /challenge) that let him use Claude Code as a thinking partner — surfacing latent patterns, contradictions, and ideas he would never see on his own.
* Writing and daily reflection are the engine of the entire system: the more you write, the more context the agent has, and the more it can do for you.
* Markdown files are the real oxygen of LLMs; if you are serious about building a personal OS with AI, a centralized note-taking tool built on markdown is foundational

Numbered Section Summaries

1. Obsidian as an Interlinked Knowledge Base

Vin introduces Obsidian as an interface that sits on top of a folder of markdown files, with the critical addition of backlinks — connections between files that mirror how the brain forms associations. He walks through his own vault, showing how daily notes, project files, and notes on people all link together in a visual graph.

2. Obsidian CLI: The Bridge Between Your Vault and Claude Code

The real breakthrough comes from Obsidian CLI, which gives Claude Code access to both the files and their interrelationships. This means the agent can see that a note about filmmaking is connected to a note about world building, and can surface cross-domain patterns you have been circling for months without realizing it.

3. Custom Slash Commands as Thinking Tools

Vin demonstrates a suite of custom commands he built: /context loads his full life and work state; /today pulls calendar, tasks, and daily notes into a prioritized plan; /trace tracks how an idea has evolved over time; /connect bridges two domains using the vault's link graph; /ghost answers a question the way Vin would; /challenge pressure-tests his current beliefs. These turn Claude Code from a generic assistant into a deeply personalized thinking partner.

4. Markdown Files as the Foundation of the AI Era

I make the case that if you are serious about using LLMs to their full potential, a centralized markdown-based note-taking system is table stakes. Writing and reflection are the raw material; files are perfect memory where human recall is flawed; and the 99.99% of people who skip this step are leaving massive value on the table.

The #1 tool to find startup ideas/trends - https://www.ideabrowser.com/
LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/
The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/

FIND ME ON SOCIAL
X/Twitter: https://twitter.com/gregisenberg
Instagram: https://instagram.com/gregisenberg/
LinkedIn: https://www.linkedin.com/in/gisenberg/

FIND VIN ON SOCIAL
X: https://x.com/internetvin
Youtube: https://www.youtube.com/@otherstuffpod
Personal Website: https://internetvin.com/Index

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
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** Tableau Certification Training: https://www.edureka.co/tableau....-certification-train **
"Level of Detail" is a new syntax which, both, simplifies and extends Tableau’s calculation language by making it possible to address level of detail questions directly. In this Edureka tutorial, you’ll gain insights into how LOD Expressions work, along with a more in-depth look at the different types of LOD Expressions and their respective use cases.

01:18 Introduction to LOD
06:12 Include Calculation
06:46 Exclude Calculation
07:12 Fixed Calculation
08:21 Aggregation & LOD
11:14 Nesting in LOD
12:16 Data Sources Supported by LOD
12:26 How to Create LOD Expressions
17:00 Level of Detail vs Table Calculations
18:04 Limitations of LOD

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Why learn Tableau?

Tableau is a leader in Gartner's magic quadrant in BI & Data analytic field. Being used in various leading domains like Business Intelligence, Marketing, Big Data Hadoop, etc., Tableau is one skill set most professional wish to carry ahead in their career. As per Indeed.com, the mean salary of Tableau professional is $ 100,000.

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For Tableau Training and Certification, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

AI robots, with Elon Musk, Boston Dynamics. To learn AI, visit: https://brilliant.org/digitalengine where you'll also find loads of fun courses on maths, science and computer science.

Sources:

Future of Life Institute AI discussion with Elon Musk:
https://www.youtube.com/watch?v=h0962biiZa4&t=1452s

AI Alignment study, OpenAI, Oxford and UC Berkeley:
https://twitter.com/RichardMCN....go/status/1603862969

Atlas gets a grip - Boston Dynamics:
https://youtu.be/-e1_QhJ1EhQ

OpenAI's ChatGPT:
https://openai.com/blog/chatgpt/

David Chalmers on Machine Learning Street Talk (great channel):
https://www.youtube.com/watch?v=T7aIxncLuWk

Volcanic lightning is making the world safer:
https://www.youtube.com/watch?v=Yc-2lfNNmWk

Ball lightning:
https://www.youtube.com/watch?v=_gOlQCI9Tgg

A message to artists about AI art, ChrissaBug:
https://www.youtube.com/watch?v=zx3ROK9nOYE

Study on the health cost of sitting down too much:
https://www.acpjournals.org/doi/10.7326/M17-0212

AI improves stroke recovery:
https://www.euronews.com/next/....2022/12/27/ai-techno

AI encodes clinical knowledge:
https://arxiv.org/abs/2212.13138?utm_source=substack&utm_medium=email

Elon Musks tweet on ChatGPT, with Altman’s response.
https://twitter.com/elonmusk/s....tatus/15991285770686

In this video you will learn about three very common methods for data dimensionality reduction: PCA, t-SNE and UMAP. These are especially useful when you want to visualise the latent space of an autoencoder.

If you want to learn more about these techniques, here are some key papers:
- UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction https://arxiv.org/abs/1802.03426
- Stochastic Neighbor Embedding https://papers.nips.cc/paper_f....iles/paper/2002/hash
- Visualizing Data using t-SNE https://www.jmlr.org/papers/vo....lume9/vandermaaten08

And if you want to learn about even more recent techniques such as TriMAP and PACMAP, here are the papers:
- TriMap: Large-scale Dimensionality Reduction Using Triplets https://arxiv.org/abs/1910.00204
- PaCMAP https://arxiv.org/abs/2012.04456

Chapters:
00:36 PCA
05:15 t-SNE
13:30 UMAP
18:02 Conclusion

This video features animations created with Manim, inspired by Grant Sanderson's work at @3blue1brown. Here is the code that I used to make this video: https://github.com/ytdeepia/La....tent-Space-Visualisa

If you enjoyed the content, please like, comment, and subscribe to support the channel!


#DeepLearning #PCA #ArtificialIntelligence #tsne #DataScience #LatentSpace #Manim #Tutorial #machinelearning #education #somepi

The Best Songs from Sing 2
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STAR WARS: THE OLD REPUBLIC Full Movie 8K 60FPS Upscaled (Remastered with Machine Learning AI) UHD

Star Wars The Old Republic All Cinematic Trailers

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Links to Source Trailers if you want to see what they originally looked liked on their own:

Return Cinematic Trailer - https://www.youtube.com/watch?v=mm4JEZudf0c
Hope Cinematic Trailer - https://www.youtube.com/watch?v=1ToztqqDcaY
Deceived Cinematic Trailer - https://www.youtube.com/watch?v=YdgmH9Vv2-I
Sacrifice Cinematic Trailer - https://www.youtube.com/watch?v=Nzq9epS2b1A
Betrayed Cinematic Trailer - https://www.youtube.com/watch?v=LbpDxrew4A0

You can check out more of our upscales here: https://www.youtube.com/playli....st?list=PL1cvljv8vQm

I used Gigapixel AI to upscale and enhance the original videos, and we feel the results are quite good. I also used DAIN to make the original 30 frame videos into 60 frames per second (one of them was original 24fps and we interpolated it to 48fps). If you're watching on a phone then you're likely won't see too much of a difference, but if you're on a desktop or tv and are watching in 2K, 4k or 8K you should see a stark difference, especially if you click on the original videos after to see how grainy and blurry they look now on modern monitors. Even if you don't have an 4K or 8K monitor, you can still click on those options to get a better bitrate and quality. The only issue is you might get frame lag. If that's the case you might want to check your settings on Chrome to see if you have hardware acceleration on, in many cases that will help with the lag. Let us know what other upscales you'd like to see. Hope you enjoy!

00:00 Return
06:01 Hope
11:01 Deceived
14:14 Sacrifice
18:10 Betrayed
24:05 Return Comparison With Original
29:52 Hope Comparison With Original
34:51 Deceived Comparison With Original
38:03 Sacrifice Comparison With Original
42:00 Betrayed Comparison With Original
47:54 Outro


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