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📊 Excel vs Power BI: Unleashing the Power of Data

In this insightful video, we dive deep into the world of data analysis and visualization, comparing two powerhouse tools: Microsoft Excel and Power BI. Whether you're a data enthusiast, a business professional, or a student eager to enhance your skills, this comparison will help you understand the strengths and nuances of each tool.

🔍 What's Covered:

Introduction to Excel:

Explore Excel's familiar interface and its robust capabilities for data manipulation.
Learn how to create pivot tables, use formulas, and perform basic data analysis within Excel.
Introduction to Power BI:

Discover the dynamic features of Power BI designed for advanced data modeling and visualization.
Understand the seamless integration of Power BI with various data sources for real-time insights.
Head-to-Head Comparison:

Breakdown of key differences and similarities between Excel and Power BI.
Practical examples showcasing scenarios where one tool may excel over the other.
When to Use Each Tool:

Guidance on choosing the right tool based on your specific needs and the complexity of your data.
Integration Possibilities:

Explore how Excel and Power BI can work together harmoniously to maximize your analytical capabilities.

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

⏩ Check out the Data Analytics Training Videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUUKnB4

#ExcelTraining #ExcelBasicsTrainingCourse #ExcelTraining #Exceltutorial #AdvancedExcelFullcourse #ExcelCourse #CompleteExcelCourse #AdvancedExcelTutorial #ExcelTraining #MSExcel #ExcelForBeginners #ExcelFullCourse #LearnExcel #2023 #Simplilearn

➡️ 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
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- 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

✅ Enroll Course Now: https://www.simplilearn.com/pgp-data-analytics-certification-training-course?utm_campaign=23Nov23ExcelVsPowerBi&utm_medium=Description&utm_source=youtube
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🔥Intellipaat Microsoft excel training: https://intellipaat.com/excel-training/
In this microsoft excel tutorial you will master how to use excel, complete ms excel formulas, excel tips and tricks, excel accounting, how to use excel vlookup, pivot table in excel, excel formulas and functions in detail.
#ExcelTutorial #MicrosoftExcelTutorial #Excel

👉Following topics are covered in this video:
0:00 - Excel Tutorial
1:08 - Microsoft Excel Overview
4:52- Getting started with Microsoft Excel
5:33- Hands on with Microsoft excel
8:02 - Saving an Excel file
10:31- Excel Customization
13:21- Important areas of working
15:51- What is formula bar
19:18- ribbons
24:06- Formatting excel and shortcuts
33:04- Basic Formulas
50:00- Find and Replace
1:05:49- Text Functions-Formatting Data
1:39:25- count functions
1:40:45- Relative Reference
1:57:17- Absolute Reference
2:14:12- Mixed Reference
2:32:52- Data Validation
2:42:00- Different types of data validation
3:03:02- Conditional formatting
3:43:56- sorting data
4:06:15- filtering data
4:34:11- column chart
5:09:54- line chart
5:23:01- pie chart
5:36:51- protection
6:14:29- pivot tables
6:59:44- Vlookup
7:50:55- index function
7:51:51- Match function
8:30:39- lookup function
9:11:55- what is VBA
9:13:23- what is macro
9:14:37- Exploring Visual Basic Editor (VBE)
9:17:14- Using Macro Recorder
9:39:12- Recap
9:51:18- Variable, data types and constants
10:04:14- scope of a variable
10:15:09- Data Types
10:21:11- Constants

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If you’ve enjoyed this microsoft excel training video, Like us and Subscribe to our channel for more similar informative videos.
Got any questions about ms excel tutorial? Ask us in the comment section below.
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Why microsoft excel is important?

Microsoft Excel is the most-used spreadsheet program in the world. Excel can perform formula-based calculations and many other mathematical functions. The program also serves as a programming platform for Visual Basic for Applications. Because of its utility, Excel has become a staple in many enterprises.

Why should you opt for a microsoft excel career?

Microsoft Excel has proven to be advantageous for day to day business activities. The knowledge of Microsoft Excel has become essential for small business establishments to carry out their day to day business and reap the best results from their business. There is a huge demand for ms excel certified professional. The salaries for ms excel professional are also very good.
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Please write us to [email protected] or call us at: +91-7847955955

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🔥Edureka Python Certification Training: https://www.edureka.co/machine....-learning-certificat
This Edureka video on 'Support Vector Machine Tutorial' covers A brief introduction to Support Vector Machine in Python with a use case to implement SVM using Python.

🔷🔸About the Speaker🔸🔷
Name: Dr. Rajesh Kumar
Details:
◾Data Science Head at SCG Chemicals
◾Ex - Ernst & Young, Ex-Intel, Ex - Mercedes Benz
◾16 years of experience spanning across IT Services, Petrochemicals, Hi-Tech, Business Consulting, Supply Chain, and Automotive Industries.
◾A Ph.D. holder from the Indian Institute of Science
----------------------------------------------------------------------------------
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s

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

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LinkedIn: https://www.linkedin.com/company/edureka
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SlideShare: https://www.slideshare.net/EdurekaIN
Castbox: https://castbox.fm/networks/505?country=in
Meetup: https://www.meetup.com/edureka

#Edureka #PyhtonEdureka #Supportvectormachineinpython #pythonprojects #pythonprogramming #pythontutorial #PythonTraining #PythonEdureka learn #withme


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


How it Works?
1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work
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 be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!

- - - - - - - - - - - - - - - - -
About the Course

Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you:

1. Master the Basic and Advanced Concepts of Python
2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs
3. Master the Concepts of Sequences and File operations
4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python
5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application
6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn
7. Master the concepts of MapReduce in Hadoop
8. Learn to write Complex MapReduce programs
9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python
10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics
11. Master the concepts of Web scraping in Python
12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience
- - - - - - - - - - - - - - - - - - -

Why learn Python?

Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.
Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain.

Who should go for python?

Edureka’s Data Science certification course in Python is a good fit for the below professionals:


· Programmers, Developers, Technical Leads, Architects
· Developers aspiring to be a ‘Machine Learning Engineer'
· Analytics Managers who are leading a team of analysts
· Business Analysts who want to understand Machine Learning (ML) Techniques
· Information Architects who want to gain expertise in Predictive Analytics
· 'Python' professionals who want to design automatic predictive models


For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free)

In this comprehensive exploration of the field of deep learning with Professor Simon Prince who has just authored an entire text book on Deep Learning, we investigate the technical underpinnings that contribute to the field's unexpected success and confront the enduring conundrums that still perplex AI researchers.

Understanding Deep Learning - Prof. SIMON PRINCE [STAFF FAVOURITE]

Watch behind the scenes, get early access and join private Discord by supporting us on Patreon:
https://patreon.com/mlst
https://discord.gg/aNPkGUQtc5
https://twitter.com/MLStreetTalk

Key points discussed include the surprising efficiency of deep learning models, where high-dimensional loss functions are optimized in ways which defy traditional statistical expectations. Professor Prince provides an exposition on the choice of activation functions, architecture design considerations, and overparameterization. We scrutinize the generalization capabilities of neural networks, addressing the seeming paradox of well-performing overparameterized models. Professor Prince challenges popular misconceptions, shedding light on the manifold hypothesis and the role of data geometry in informing the training process. Professor Prince speaks about how layers within neural networks collaborate, recursively reconfiguring instance representations that contribute to both the stability of learning and the emergence of hierarchical feature representations. In addition to the primary discussion on technical elements and learning dynamics, the conversation briefly diverts to audit the implications of AI advancements with ethical concerns.

Pod version (with no music or sound effects): https://podcasters.spotify.com..../pod/show/machinelea

Follow Prof. Prince:
https://twitter.com/SimonPrinceAI
https://www.linkedin.com/in/si....mon-prince-615bb9165

Get the book now!
https://mitpress.mit.edu/97802....62048644/understandi
https://udlbook.github.io/udlbook/

Panel: Dr. Tim Scarfe -
https://www.linkedin.com/in/ecsquizor/
https://twitter.com/ecsquendor

TOC:
[00:00:00] Introduction
[00:11:03] General Book Discussion
[00:15:30] The Neural Metaphor
[00:17:56] Back to Book Discussion
[00:18:33] Emergence and the Mind
[00:29:10] Computation in Transformers
[00:31:12] Studio Interview with Prof. Simon Prince
[00:31:46] Why Deep Neural Networks Work: Spline Theory
[00:40:29] Overparameterization in Deep Learning
[00:43:42] Inductive Priors and the Manifold Hypothesis
[00:49:31] Universal Function Approximation and Deep Networks
[00:59:25] Training vs Inference: Model Bias
[01:03:43] Model Generalization Challenges
[01:11:47] Purple Segment: Unknown Topic
[01:12:45] Visualizations in Deep Learning
[01:18:03] Deep Learning Theories Overview
[01:24:29] Tricks in Neural Networks
[01:30:37] Critiques of ChatGPT
[01:42:45] Ethical Considerations in AI

References:

#61: Prof. YANN LECUN: Interpolation, Extrapolation and Linearisation (w/ Dr. Randall Balestriero)
https://youtube.com/watch?v=86ib0sfdFtw

Scaling down Deep Learning [Sam Greydanus]
https://arxiv.org/abs/2011.14439

"Broken Code" a book about Facebook's internal engineering and algorithmic governance [Jeff Horwitz]
https://www.penguinrandomhouse.....com/books/712678/br

Literature on neural tangent kernels as a lens into the training dynamics of neural networks.
https://en.wikipedia.org/wiki/....Neural_tangent_kerne

Zhang, C. et al. "Understanding deep learning requires rethinking generalization." ICLR, 2017.
https://arxiv.org/abs/1611.03530

Computer Vision: Models, Learning, and Inference, by Simon J.D. Prince
https://www.amazon.co.uk/Compu....ter-Vision-Models-Le

Deep Learning Book, by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
https://www.deeplearningbook.org/

Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network
https://arxiv.org/abs/2210.00881

Computer Vision: Algorithms and Applications, 2nd ed. [Szeliski]
https://szeliski.org/Book/

A Spline Theory of Deep Networks [Randall Balestriero]
https://proceedings.mlr.press/....v80/balestriero18b/b

DEEP NEURAL NETWORKS AS GAUSSIAN PROCESSES [Jaehoon Lee]
https://arxiv.org/abs/1711.00165

Do Transformer Modifications Transfer Across Implementations and Applications [Narang]
https://arxiv.org/abs/2102.11972

ConvNets Match Vision Transformers at Scale [Smith]
https://arxiv.org/abs/2310.16764

Dr Travis LaCroix (Wrote Ethics chapter with Simon)
https://travislacroix.github.io/

Reinforcement Learning with Human Feedback (RLHF) is a method used for training Large Language Models (LLMs). In the heart of RLHF lies a very powerful reinforcement learning method called Proximal Policy Optimization. Learn about it in this simple video!

This is the first one in a series of 3 videos dedicated to the reinforcement learning methods used for training LLMs.

Full Playlist: https://www.youtube.com/playli....st?list=PLs8w1Cdi-zv

Video 0 (Optional): Introduction to deep reinforcement learning https://www.youtube.com/watch?v=SgC6AZss478
Video 1: Proximal Policy Optimization https://www.youtube.com/watch?v=TjHH_--7l8g
Video 2 (This one): Reinforcement Learning with Human Feedback
Video 3 (Coming soon!): Deterministic Policy Optimization

00:00 Introduction
00:48 Intro to Reinforcement Learning (RL)
02:47 Intro to Proximal Policy Optimization (PPO)
4:17 Intro to Large Language Models (LLMs)
6:50 Reinforcement Learning with Human Feedback (RLHF)
13:08 Interpretation of the Neural Networks
14:36 Conclusion

Get the Grokking Machine Learning book!
https://manning.com/books/grok....king-machine-learnin
Discount code (40%): serranoyt
(Use the discount code on checkout)

🚀 Small Language Models (SLMs): The Future of AI? 🤖

Most people think AI—like ChatGPT—needs huge servers and an internet connection. While that’s true for Large Language Models (LLMs), AI doesn’t have to be massive!

Introducing Small Language Models (SLMs)—AI that’s lightweight, efficient, and runs entirely offline. 📱💡

🔍 What You’ll Learn in This Video:
✅ SLMs vs. LLMs – What’s the difference?
✅ How SLMs work – Train them on your data for specific tasks.
✅ Real-world examples – AI for customer support, healthcare, and education.
✅ Why SLMs are the future – Privacy-friendly, low-energy, and cost-effective!

🌎 Why This Matters:
Unlike LLMs that require cloud computing, SLMs can run directly on your phone, laptop, or even a Raspberry Pi! No internet needed, no privacy concerns, and perfect for businesses, remote areas, and industries with strict data security requirements.

💡 SLMs Are Changing AI Forever!
• Instant AI-powered customer support 🏢
• Medical assistance in remote areas 🏥
• Personalized education tools for students 📚
• Energy-efficient AI for sustainability 🌱

Basic mathematics from a language model? Rob Miles on GPT3, where it seems like size does matter!

More from Rob Miles: http://bit.ly/Rob_Miles_YouTube

https://www.facebook.com/computerphile
https://twitter.com/computer_phile

This video was filmed and edited by Sean Riley.

Computer Science at the University of Nottingham: https://bit.ly/nottscomputer

Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com

In this quick tutorial we will download and install the Open AI GPT-2 Model and then generate a text based on some input. Basically we will use the Open AI model to build a basic AI Text generator. You can fine tune this for certain tasks like AI Generated Code, Music, Text and so on but in this example we will be generating text based on some input. Also keep in mind this is not some text from the training set or from a website, the AI generates it's own unique response.


In order to get Open AI GPT-2 up and running you need to download the model from the Github repository, install the requirements, download the models and run the sample. You can also fine tune the GPT-2 NLP for other categories in order to make it much more accurate.


If you want me to create an app around this or create a video where I am fine-tuning the model leave a comment down below. If enough people are interested I will create video about that!



🚨Subscribe to my Tech and Software Newsletter🚨 Everything around Tech and Software Development from tutorials to latest news, tips and tricks. Learn everything from creating Ads to configuring your own cloud infrastructure! Use: 🚨 https://noveltechmedia.com 🚨

For any thoughts, ideas, feedback or questions contact me at
🚨 [email protected] 🚨.

Disclaimer:
All videos are for educational purposes and use them wisely. Any video might have inaccurate or outdated information. I give my best to research every topic thoroughly but please be aware that videos can contain mistakes.

🔥Professional Certificate Program In Blockchain: https://www.simplilearn.com/blockchain-certification-training-course?utm_campaign=Blockchainscribe&utm_medium=DescriptionFirstFold&utm_source=youtube
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This video on "Blockchain in 7 Minutes" by Simplilearn will help you understand what is Blockchain and how blockchain works. In this video, you will understand what led to the creation of Blockchain, what Blockchain is, how a Bitcoin transaction works, how Blockchain plays an integral role in it with features like hash encryption, proof of work, and mining, and how Blockchain technology is used in real-life scenarios. Now, let’s dive into this video and understand the basics of Blockchain and How Blockchain works.
Below are the topics we have covered in this Blockchain in 7 minutes video.
00:00 Blockchain In 7 Minutes
01:03 What are Cryptocurrencies?
01:30 What Is A Ledger?
03:13 What Is Blockchain?
05:50 How Walmart uses Blockchain?

🔥 Enroll for FREE Blockchain Course & Get your Completion Certificate: https://www.simplilearn.com/learn-blockchain-basics-skillup?utm_campaign=Blockchainscribe&utm_medium=Description&utm_source=youtube

To learn more about Blockchain, subscribe to our YouTube channel: https://www.youtube.com/user/S....implilearn?sub_confi

Watch more videos on Blockchain: https://www.youtube.com/playli....st?list=PLEiEAq2VkUU

#Blockchain #Whatisblockchain #BlockChainExplained #Blockchaintutorial #Bitcoin #Blockchainonlinetraining #Blockchainforbeginners #BlockchainTechnology #Simplilearn

Simplilearn’s Blockchain Certification Training has been designed for developers who want to decipher the global craze surrounding Blockchain, Bitcoin and cryptocurrencies. You’ll learn the core structure and technical mechanisms of Bitcoin, Ethereum, Hyperledger and Multichain Blockchain platforms, use the latest tools to build Blockchain applications, set up your own private Blockchain, deploy smart contracts on Ethereum and gain practical experience with real-world projects.

Why learn Blockchain?
Blockchain technology is the brainchild of Satoshi Nakamoto, which enables digital information to be distributed. A network of computing nodes makes up the Blockchain. Durability, robustness, success rate, transparency, incorruptibility are some of the enticing characteristics of Blockchain. By design, Blockchain is a decentralized technology which is used by a global network of the computer to manage Bitcoin transactions easily. Many new business applications will result in the usage of Blockchain such as Crowdfunding, smart contracts, supply chain auditing, etc.

➡️ Professional Certificate Program In Blockchain
The blockchain certification program helps the learners start from the fundamentals and then cover all the technical and functional aspects needed to build any blockchain solution using the best tools and techniques in the industry.In this program, they will build smart contracts, bitcoin wallets, create transactions, fabricode and more.

✅ Key Features
Program completion certificate from IIT Kanpur and Simplilearn
Masterclasses from IIT Kanpur faculty
Seamless access to integrated labs on Simplilearn’s LMS
Get hands-on experience with a capstone on industry-relevant use cases
Build skills to become job-ready and advance your career
Simplilearn's JobAssist helps you get noticed by top hiring companies
8X higher interaction in live online classes conducted by industry experts
Acquire insight into the most in-demand Blockchain skills

✅ Skills Covered
- Cryptography and Cryptocurrency
- Bitcoin
- Distributed ledger
- Hyperledger
- Ethereum Blockchain
- Consensus
- Transactions
- Workflows
- Networks

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

This is a beta sneak peek and part of a four video release, make sure to watch all four segments!

Video 1: https://youtu.be/tG7dsM0hllA
Video 2: https://youtu.be/-dVCfczFgEw
Video 3: https://youtu.be/YjDOxcURUpk
Video 4: https://youtu.be/W-pkMkTSu0A

Photoshop will soon harness the power of Artificial Intelligence into their program by way of Generative Fill. Easily remove objects, use inpainting to generate new elements right in your image, use outcropping to effortlessly extend your image canvas, or replace the background all together with Photoshop's new AI powered Generative Fill features.
Kristina will also cover speeding up any task you have, by using the contextual task bar.

Kristina's top 20 Photoshop Retouching Tips E-book: https://www.sharkpixel.com/20-ps-retouching-tips

In this video, I go over how to create a custom dataset to finetune GPT Neo and GPT-J-6B. To do this, I create an AI quote generator.

Github: https://github.com/mallorbc/GPT_Neo_quotes_dataset

Timestamps

00:00 - Intro
00:29 - Quotes Dataset
01:59 - Code Overview
07:07 - Running The Code
07:54 - Looking At Generated Dataset
08:35 - Running The Fine-tuned Model
09:56 - Outro

ChatGPT has taken the world by storm and GPT4 is out soon. While that’s great, wouldn't you like to run your own chatbot, locally and for free (unlike GPT4)? No more queues, nothing to pay, a choice of models and the ability to create your own characters? What’s that? It doesn’t even need a GPU? Sounds too good to be true? Welcome to the text-generation-webui! A gradio web UI for running Large Language Models like GPT-J 6B, OPT, GALACTICA, LLaMA, Pygmalion and many, many more! Whisper and TTS included, allowing you to speak to your characters and have them speak back too.

As with anything AI, you’ll have the very best experience of a simple, error free install every time on Linux.
For Microsoft Windows the exact same steps should also work, but as any Windows user knows anything could go wrong at any time!
As for Mac - not sure!

Thanks to huggingface there is a massive library of models, many with Open Source licenses just ready for you to use! Create any custom character you like and take it for a spin - even with just 8GB VRAM. Some models work with much less too 😀

If you don’t like standard installations, you can also use the obfuscated method. It’s just 3 steps:
1. Install using the 1-click installer
2. Download your model(s)
3. Start the webui!

See the pinned tweet for more links ;)

I’m pretty sure everyone will want to try this, so expect to see lots more of this interface as others catch on! Just remember where you saw it first - right here on the Nerdy Rodent channel!

== Links! ==
* Installing Anaconda for MS Windows Beginners - https://youtu.be/OjOn0Q_U8cY
* How do I create an animated SD avatar? - https://youtu.be/Z7TLukqckR0
* Stable Diffusion Playlist! - https://youtube.com/playlist?l....ist=PLjC8P1vEncQDVOC

== Stable Diffusion Playlists ==
* Interested in adding things to your AI Art? Try these!
Dreambooth Playlist - https://youtube.com/playlist?l....ist=PLjC8P1vEncQD-QY
* Textual Inversion Playlist - https://youtube.com/playlist?l....ist=PLjC8P1vEncQDSDL

Note that GitHub repositories update often! Be sure to check the GitHub README for the current info ;)m

In this talk, we will cover the basics of Reinforcement Learning from Human Feedback (RLHF) and how this technology is being used to enable state-of-the-art ML tools like ChatGPT. Most of the talk will be an overview of the interconnected ML models and cover the basics of Natural Language Processing and RL that one needs to understand how RLHF is used on large language models. It will conclude with open question in RLHF.

RLHF Blogpost: https://huggingface.co/blog/rlhf
The Deep RL Course: https://hf.co/deep-rl-course
Slides from this talk: https://docs.google.com/presen....tation/d/1eI9PqRJTCF
Nathan Twitter: https://twitter.com/natolambert
Thomas Twitter: https://twitter.com/thomassimonini

Nathan Lambert is a Research Scientist at HuggingFace. He received his PhD from the University of California, Berkeley working at the intersection of machine learning and robotics. He was advised by Professor Kristofer Pister in the Berkeley Autonomous Microsystems Lab and Roberto Calandra at Meta AI Research. He was lucky to intern at Facebook AI and DeepMind during his Ph.D. Nathan was was awarded the UC Berkeley EECS Demetri Angelakos Memorial Achievement Award for Altruism for his efforts to better community norms.

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In this video on the Power BI full course, we'll learn the basics of power bi and understand the different components of Power B, how to use Dax functions to derive value out of your data, and how to publish dashboards on to the power bi service.

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

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➡️About Caltech Data Analytics Bootcamp
The Caltech Data Analytics Bootcamp is ideal for working professionals from all backgrounds. Develop core skills such as mastering Excel, creating data-driven presentations, data manipulation with SQL, analyzing data with Python, and data visualization with Tableau. Learn data analysis with tools such as AWS.

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✅Skills Covered
- Data Analytics
- Statistical Analysis using Excel
- Data Analytics using Python
- Data Visualization with Tableau
- Linear and Logistic Regression
- Data Manipulation
- & more

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NEWSLETTER ✉️ http://DylanCurious.com
PATREON 💰 https://patreon.com/DylanCurious (Monthly Video Call)

In today's episode, we're charting the course of Artificial General Intelligence (AGI) as of June 2023, guided by the timeline presented by AI expert Dr. Alan D. Thompson.

A critical turning point came in 2017, with the birth of the attention mechanism by Google researchers, paving the way for the creation of Transformers. These are the foundation of powerful AI models like GPT, and according to Dr. Thompson, we're about halfway to achieving AGI from here.

The period between 2017 and 2023 has been rich with major AI advancements, each one a stepping stone on our path to AGI. These include our deeper understanding of GPT-3's capabilities, innovative applications of AI in microchip design, and the emergence of multitasking models like DeepMind's Gato.

By 2020, we had made roughly 30% progress towards AGI, nudging up to 31% by 2021. Significant leaps, like the unveiling of GPT-3's remarkable abilities and the use of AI in hardware design, were clear indicators of this progress. In May 2022, the introduction of DeepMind's Gato model propelled us to 39% completion, thanks to its impressive capabilities and the demonstration of human-like general intelligence.

As 2022 came to a close, progress continued with developments in autonomous AI systems and AI-assisted human tasks. Into 2023, we saw AGI estimates rise to 41%, largely due to Microsoft's innovative use of ChatGPT in operating robotic components. The introduction of Google's PaLM-E 562B, capable of planning its own future based on visual and language data, took AGI estimates up to 42%.

The launch of the even more powerful GPT-4 model and the integration of AI into robotics have substantially fast-tracked our journey towards AGI. Stay tuned to "Curious Future" for more updates on the fascinating world of AI, and don't forget to subscribe for the latest in AI, technology, and innovation.

CURIOUS FUTURE: @dylan_curious
↪ https://www.youtube.com/channe....l/UCpdyFxSktWo3W6kMY

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↪ https://www.youtube.com/channe....l/UChChPrDzfifYB9Si1

CURIOUS FRIENDS: @vegasfriends
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00:00 - Artificial General Intelligence, 50% Complete: Fact or Fiction?
00:42 - Did Google’s Invention of the Transformers Take Us 20% of the Way to AGI?
01:23 - 30% to AGI in 2020? Unraveling the AI Progress Debate
02:24 - AI Designing AI: The 31% Milestone Towards AGI in 2021
03:14 - DeepMind’s Gato Model: The Super Multitasker Pushing AGI to 39%?
03:48 - We Are 39% Of The Way To AGI: Unraveling Antropic’s Human Reinforcement Method
04:55 - Microsoft’s ChatGPT Pushed Us 41% Closer To AGI
05:49 - AGI at 42%: After Google’s PaLM-E 562B’s Shows Adaptive Abilities
07:19 - AGI at 48%: What Does this Mean for AI’s Future?
08:43 - Humans at 94%, AI at 90.9% | AGI Progress Is Moving Fast
09:37 - 2 Milestone To Look For Before AGI Arrives On Earth

SOURCES:
https://lifearchitect.ai/agi/
https://ai.googleblog.com/2017..../08/transformer-nove
https://www.youtube.com/watch?v=HrV19SjKUss&t=175s&ab_channel=MachineLearningStreetTalk
@MachineLearningStreetTalk
https://www.theverge.com/2021/....6/10/22527476/google
https://www.nature.com/articles/s41586-021-03544-w
https://lifearchitect.ai/the-sky-is-on-fire/
https://www.youtube.com/watch?v=6fWEHrXN9zo&list=PLqJbCeNOfEK-o63ACEKEbwE6-XpEXXS_I&ab_channel=DrAlanD.Thompson
https://en.wikipedia.org/wiki/Gato_(DeepMind)
https://www.deepmind.com/publi....cations/a-generalist
@DrAlanDThompson
https://developer.nvidia.com/b....log/designing-arithm
https://www.microsoft.com/en-u....s/research/group/aut
https://www.youtube.com/watch?v=wLOChUtdqoA&ab_channel=MicrosoftAutonomousSystems%26RoboticsResearch
@msftautonomoussys
https://palm-e.github.io/
https://arxiv.org/abs/2303.12712
https://www.youtube.com/watch?v=XyCKe3rrYik&ab_channel=STrucBot
https://www.fastcompany.com/90....889271/boston-dynami
https://tidybot.cs.princeton.edu/
https://www.youtube.com/watch?v=Vq_DcZ_xc_E&ab_channel=AgilityRobotics
@Structon
@AgilityRobotics

WATCH THE FULL VIDEO ⤵
https://www.youtube.com/watch?v=xyzY3cj7tTA

#ai #artificialintelligence #tech #agi #gpt3 #gpt4 #deepmind #chatgpt #robotics #google #microsoft #machinelearning #autonomousai #palm-e562b #gato #transformers #futuretech #innovation #aitechnology #aitimeline #curiousfuture #alanthompson #artificialgeneralintelligence #aidesign #aipredictions #aiadvancements #aiupdates

The truth, with photons.
I hope I've articulated everything clearly in this video. If not, I'll clarify in comments. Thanks to everyone who appears in this video and thanks to everyone who watches this video!

Veritasium is of course a combination of the latin 'veritas' meaning truth, and the common element ending 'ium'. I guess this is my version of the 'draw my life' craze that rolled through YouTube many years ago. Except I wanted to tell my story with the actual moments, the photons, the stored magnetic states. There's something about that which is so important to me (because I think the alternative involves fooling yourself) which is why I'm so fascinated by film and video.

One of my inspirations for the name Veritasium came from the end of the poem Ode on a Grecian Urn by John Keats, in which he writes:
"Beauty is truth, truth beauty,—that is all
Ye know on earth, and all ye need to know."

Special thanks to Patreon supporters:
Tony Fadell, Donal Botkin, Michael Krugman, Jeff Straathof, Zach Mueller, Ron Neal, Nathan Hansen, Yildiz Kabaran,
Terrance Snow, Stan Presolski

Music from http://epidemicsound.com
Magnified X1 - Gunnar Johnsen
Fluorescent Lights - Martin Gauffin
Dissolving Patterns - Ebb & Flod
Luna - Ebb & Flod

Additional music by Kevin MacLeod: http://incompetech.com
Sneaky Snitch

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This Data Science Full Course Video by Simplilearn helps you learn a brief introduction to data science. followed by that, we will continue by discussing the scope of AI in future, then we will learn the roadmap to become a data scientist, followed by that, we will learn the AI BIAS topic, proceeding ahead we will learn the differences between AI, ML, and DL (Artificial intelligence vs machine learning vs deep learning), next we will have a brief introduction to deep learning and applied data science with python. Then we will learn how to Run Lama Privately. Afterwards, we will procced with an Introduction to LLm and LLM benchmarking, we will proceed with LangChain. Lastly we will discuss Confusion matrix, Machine learning projects for beginners and at the end we will discuss important interview questions. The video covers the following topics.

00:00:00 Introduction to Data Science Full Course
00:04:21 Data Science in 5 minutes
00:13:27 Future of AI
00:14:59 How to become Data Scientist
00:29:52 AI Bias
00:36:03 Difference between AI ML and DL
00:45:39 Roadmap to Data Science
00:54:56 Fastest way to Learn Data Science
06:48:37 Deep Learning
10:05:37 Applied Data Science with Python
10:06:44 Run Lama Privately
10:15:28 Introduction to LLM
10:28:57 LLM Benchmarking
10:30:16 Lang Chain Explained
10:57:44 Confusion Matrix ML
11:15:29 ML Projects for Beginners
12:22:26 Interview Questions

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What is Data Science?
Data science is the field of study that works with massive amounts of data utilizing relevant tools and techniques to derive valuable data. Companies across various industries generate vast amounts of data, so its applications range all the way from education, healthcare, and entertainment to Finance and Marketing.

✅ About Post Graduate Program In Data Science:
This in-depth Data Science program is designed for working professionals, and covers job-critical topics like R, Python programming, Machine Learning techniques, NLP notions, and Data Visualization with Tableau, using an active learning model that includes live sessions from global professionals, practical labs, IBM Hackathons, and corporate ready projects

Key Features
✅ Program completion certificate from Purdue University Online and Simplilearn
✅ Access to Purdue’s alumni association membership on program completion
✅ Core curriculum delivered in live online classes by industry experts
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✅ Engage in live online masterclasses led by Purdue faculty, staff, and IBM experts
✅ Exclusive hackathons and Ask Me Anything (AMA) sessions by IBM
✅ Gain exposure to ChatGPT, Gemini, Keras, TensorFlow and other prominent tools
✅ Interactive sessions on the latest AI trends, such as GenAI, prompt engineering, LLMs, and more
✅ 3 capstones and 25+ hands-on projects from various industry domains
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered
✅ Exploratory Data Analysis
✅ Descriptive Statistics
✅ Inferential Statistics
✅ Model Building and Finetuning
✅ Supervised and Unsupervised Learning
✅ Ensemble Learning
✅ Deep Learning
✅ Data Visualization
✅ Generative AI
✅ Prompt Engineering
✅ ChatGPT
✅ Explainable AI
✅ Machine Learning Algorithms
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Speech Recognition

Learning Path
✅ Program Induction
✅ Programming Refresher
✅ Data Management using SQL
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning Specialization

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CIFAR DLRL 2020 Summer School