The most famous equation in finance, the Black-Scholes/Merton equation, came from physics. It launched an industry worth trillions of dollars and led to the world’s best investments. Go to https://www.eightsleep.com/veritasium and use the code Veritasium for $200 off your Pod Cover.

Special thanks to our Patreon supporters! Join this list to help us keep our videos free, forever:
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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

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A huge thank you to Prof. Andrew Lo (MIT) for speaking with us and helping with the script.

We would also like to thank the following:
Prof. Amanda Turner (University of Leeds)
Owen Maher (Electrify Video Partners)

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References:

The Man Who Solved the Market: How Jim Simons launched the quant revolution, Gregory Zuckerman. Penguin Publishing Group. - https://ve42.co/GZuckerman

The Physics of Finance: Predicting the Unpredictable: Can Science Beat the Market? James Owen Weatherall. Short Books. - https://ve42.co/FinancePhysics

The Statistical Mechanics of Financial Markets, J.Voigt. Springer. - https://ve42.co/Springer

Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of political economy, 81(3), 637-654. - https://ve42.co/BlackScholes

Cornell, B. (2020). Medallion fund: The ultimate counterexample?. The Journal of Portfolio Management, 46(4), 156-159. - https://ve42.co/Medallion

Images & Video:
Ed Thorp on The Tim Ferris Show - https://www.youtube.com/watch?v=CNvz91Jyzbg
Jim Simons on TED - https://www.youtube.com/watch?v=U5kIdtMJGc8
Jim Simons on Numberphile - https://www.youtube.com/watch?v=QNznD9hMEh0

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Directed by Will Wood and Derek Muller
Written by Will Wood, Emily Zhang, Petr Lebedev and Derek Muller
Camera operation by Raquel Nuno
Additional research by Gregor Čavlović
Edited by Jack Saxon and Trenton Oliver
Animated by Fabio Albertelli, Jakub Misiek, Ivy Tello, David Szakaly and Will Wood
Produced by Will Wood, Han Evans and Derek Muller

Thumbnail by Ren Hurley
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🔥Edureka*** Machine Learning Certification Training - https://www.edureka.co/machine....-learning-certificat ***

00:00 Introduction
01:10 Agenda
01:28 Why Mathematics in Machine learning
03:38 Linear Algebra
05:05 Linear ALgebra - Scalars
06:20 Linear Algebra - Vectors
11:27 Linear Algebra - Matrices
20:24 Linear Algebra - Vector as Matrix
26:11 Linear Algebra - Eigen Vectors
27:41 Linear Algebra - Applications
30:18 Multivariate Calculus

Data Science Training: https://www.edureka.co/data-sc....ience-r-programming-

This Edureka video on "Clustering Algorithms" will help you understand the various aspects of clustering using K Means in Python.

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

Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities.

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

Why Learn Data Science?

Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework.

After the completion of the Data Science course, you should be able to:
1. Gain insight into the 'Roles' played by a Data Scientist
2. Analyse Big Data using R, Hadoop and Machine Learning
3. Understand the Data Analysis Life Cycle
4. Work with different data formats like XML, CSV and SAS, SPSS, etc.
5. Learn tools and techniques for data transformation
6. Understand Data Mining techniques and their implementation
7. Analyse data using machine learning algorithms in R
8. Work with Hadoop Mappers and Reducers to analyze data
9. Implement various Machine Learning Algorithms in Apache Mahout
10. Gain insight into data visualization and optimization techniques
11. Explore the parallel processing feature in R

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

Who should go for this course?

The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. 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. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
4. Business Analysts who want to understand Machine Learning (ML) Techniques
5. Information Architects who want to gain expertise in Predictive Analytics
6. 'R' professionals who want to captivate and analyze Big Data
7. Hadoop Professionals who want to learn R and ML techniques
8. Analysts wanting to understand Data Science methodologies.

For online Data Science training write to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).

🔥 Data Science Master Program: https://www.edureka.co/masters....-program/data-scient

This Live session on 'Data Science For Non Programmers' will help you explore the basics of Data Science and Machine Learning and in the process also tell you how to use different Python Libraries that let you implement Machine Learning Deep Learning, Data Visualization for Data Science and other purposes Non Programmatically.

🔷About Speaker: Mr. Krishna Prasad P is
1. Director Consulting at CGI.
2. Mentor for W2RT cohort as part of Nasscom initiative.
3. Recipient of prestigious “CGI Builder Award” at CGI level & “Sirius Award” at India level.
4. Submitted various white papers on Data related topics in DCAL (IIMB & IISC).
5. Architected and implemented comprehensive Data platforms for leading Banking firms.
6. Excellent experience in managing programs globally across delivery locations involving multiple time-zones.
7. Driving Pre-sales as Solution Architect & Solution Lead involving large deals.
8. Overall 22+ Years of experience with a strong focus on leading high performing teams & managing delivery excellence.
9. An Alumnus of the Indian School of Business.

Check our complete Data Science playlist here: https://goo.gl/60NJJS

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About the Master's Program

This program follows a set structure with 6 core courses and 8 electives spread across 26 weeks. It makes you an expert in key technologies related to Data Science. At the end of each core course, you will be working on a real-time project to gain hands on expertise. By the end of the program you will be ready for seasoned Data Science job roles.

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

Topics Covered in the curriculum:

Topics covered but not limited to will be : Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib, Spark SQL, Random Forest, Naïve Bayes, Time Series, Text Mining, Web Scraping, PySpark, Python Scripting, Neural Networks, Keras, TFlearn, SoftMax, Autoencoder, Restricted Boltzmann Machine, LOD Expressions, Tableau Desktop, Tableau Public, Data Visualization, Integration with R, Probability, Bayesian Inference, Regression Modelling etc.

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


Got a question on the topic? Please share it in the comment section below and our experts will answer it for you.

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

MIT Introduction to Deep Learning 6.S191: Lecture 4
Deep Generative Modeling
Lecturer: Ava Amini
*New 2024 Edition*

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

Lecture Outline
0:00​ - Introduction
6:10- Why care about generative models?
8:16​ - Latent variable models
10:50​ - Autoencoders
17:02​ - Variational autoencoders
23:25 - Priors on the latent distribution
32:31​ - Reparameterization trick
34:36​ - Latent perturbation and disentanglement
37:40 - Debiasing with VAEs
39:37​ - Generative adversarial networks
42:09​ - Intuitions behind GANs
44:57 - Training GANs
48:28 - GANs: Recent advances
50:57 - CycleGAN of unpaired translation
55:03 - Diffusion Model sneak peak

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Sing's Best Songs - "Let me hear you sing!" Groove with all your favorite songs featuring Rosita (Reese Witherspoon), Meena (Tori Kelly), Gunter (Nick Kroll), Ash (Scarlett Johansson), Johnny (Taron Egerton), and more! What's your favorite song from the Sing movies?
BUY THE MOVIES: https://www.vudu.com/content/m....ovies/details/Illumi

Watch the best Sing series scenes & clips: https://www.youtube.com/playli....st?list=PL86SiVwkw_o

Subscribe and click the bell to be notified of all your favorite movie scenes: http://bit.ly/2CZa490

CREDITS:
TM & © Universal (2021)
Cast: Reese Witherspoon, Nick Kroll, Taron Egerton, Scarlett Johansson, Tori Kelly

Watch More:
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Rotten Tomatoes MOVIECLIPS is the largest collection of movie clips on the web. Here you will find unforgettable moments, scenes, and quotes from all your favorite films.

This is my 50 Claude Code tips from 6 months of daily use personally and at Meta as a Staff Software Engineer. I've been coding with Claude Code basically 12 hours a day really trying to understand what makes Claude Code tik. Here's everything I wish I knew when I started, from foundations to advanced parallel workflows.

⏱️ TIMESTAMPS
0:00 - Intro
1:04 - ACT 1: Foundations (Tips 1-25)
1:18 - Tip 1: Run from root directory
1:56 - Tip 2: Run /init immediately
2:54 - Tip 3: CLAUDE.md is hierarchical
3:27 - Tip 4: Keep CLAUDE.md concise
3:58 - Tip 5: Structure: What, Domain, Validation
5:36 - Keyboard Shortcuts
5:58 - Tip 6: Shift+Tab toggles modes
6:40 - Tip 7: Escape interrupts
7:43 - Tip 8: Double Escape clears input
7:59 - Tip 9: Double Escape on empty = rewind
8:29 - Tip 10: Screenshot and drag
8:44 - Tip 11: Add context to screenshots
9:09 - Essential Commands
9:41 - Tip 12: /clear resets context
10:13 - Tip 13: /context shows token usage
11:42 - Tip 14: Let auto-compaction work
12:23 - Tip 15: /model switches models
12:49 - Tip 16: /resume recovers sessions
13:21 - Tip 17: /mcp shows MCP status
14:19 - Tip 18: /help shows all commands
14:33 - Tip 19: Git is your safety net
15:24 - CLAUDE.md Deep Dive
15:52 - Tip 20: Add a Critical Rules section
17:08 - Tip 21: Ask Claude to update rules
17:46 - Tip 22: Use workflow triggers
18:27 - Tip 23: Commit CLAUDE.md to git
19:34 - Tip 24: dangerously-skip for throwaway envs
20:39 - Tip 25: Combine skip with allowlists
20:59 - ACT 2: Daily Workflow (Tips 26-32)
21:38 - Tip 26: Start features in Plan Mode
23:46 - Tip 27: Fresh context beats bloated
24:29 - Tip 28: Persist before ending sessions
25:03 - Tip 29: Lazy load context
26:09 - Tip 30: Give verification commands
27:32 - Tip 31: Consider Opus for complex work
28:18 - Tip 32: Read thinking blocks
29:01 - ACT 3: Power User (Tips 33-40)
29:34 - Tip 33: Four composability primitives
29:54 - Tip 34: Skills = recurring workflows
31:33 - Tip 35: Commands = quick shorthand
32:18 - Tip 36: Never create commands manually
33:02 - Tip 37: MCPs = external service docs
33:52 - Tip 38: Ask Claude to install MCPs
34:15 - Tip 39: Subagents = isolated context
37:10 - Tip 40: Avoid instruction overload
37:48 - ACT 4: Advanced (Tips 41-50)
38:02 - Tip 41: Run multiple instances
39:06 - Tip 42: iTerm split panes
40:33 - Tip 43: Enable notifications
41:10 - Tip 44: Git worktrees for isolation
41:40 - Tip 45: /chrome connects browser
43:17 - Tip 46: Powerful for debugging
43:28 - Hooks & Automation
43:41 - Tip 47: Hooks intercept actions
44:10 - Tip 48: Auto-format with PostToolUse
44:24 - Tip 49: Block dangerous commands
44:43 - Tip 50: Explore the plugin ecosystem
45:32 - Context is King (Outro)

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#claudecode #aicoding #programming

Sebastian's books: https://sebastianraschka.com/books/
The lecture slides are available at: https://github.com/rasbt/stat4....53-deep-learning-ss2

Covers some of the basics of recurrent neural networks. In particular, this lecture covers

RNNs and Sequence Modeling Tasks: 00:00
Backpropagation Through Time: 20:23
Long-short term memory (LSTM): 31:42
Many-to-one Word RNNs: 45:16
Generating Text with Character RNNs: 50:45
Attention Mechanisms and Transformers: 1:00:09

High Quality HDR 12K VIDEO ULTRA HD 120FPS, 60FPS, 30FPS For Your HDR 8K resolution devices. Amazing combination of 16k sensor and one of the sharpest lenses in the world Zeiss Otus set in addition of HDR brings image to life! You can use this collection of Hight Resolution clips in your Tv For The Living Room, Office, Lounge, Waiting Room, Spa, Showroom, Restaurant and more. Play It On Your LG Qled TV, Samsung Oled TV, Smart TV, Sony Device, Samsung Technology, Roku, Apple TV, IPad Pro, Apple XDR, Chromecast, Xbox, Playstation and more.

⭐ Note: To view at 8K 60P you will need to use Chrome & opera.

⭐ All Videos was shot, edited & color graded by me.
THESE 8K VIDEOS ARE FOR TV'S FOR DEMO AND TEST THE QUALITY OF ALL 8K TV'S.

⭐ I have done High color correction, Color changing, Raw Videos editing, HDR color Setting, merge files & 8K Export file etc.

Editing Video by
PREETI NAAGAR

This video created for entertainment informative, educational purposes and Film & Animation.


Editing Software
Adobe premiere pro

ALL CREDIT GOES TO YOUTUBE

Copyright
⭐ All The footage Was Edited And Color Corrected By Me.
⭐ Video Footage Copyright Under License.

All other rights reserved.

#12khdr #dolbyvision #60fps

#8k #china #hdr
I inserted a lot of useful information into subtitles to make watching my films more enjoyable.
Please click on CC button to activate subtitles and to choose from different languages available.

This film was created for educational, entertainment and informative purposes.
Some footage have been originally recorded in 8K resolution and some in 4K. I upscaled all 4K footage to 8K resolution, resulting something new.
This film was re-edited in HDR10 standard and color corrected (high color correction , color grading , adjusted the blacks, adjusted the highlights and the saturation).
To watch this video in real HDR, you should use a HDR television set.

If you want to know more about my films, then you can access:
My Website: https://8kvideoshdr.com
Facebook: https://www.facebook.com/8kvideoshdr/

There are a lot of interesting facts that you probably didn’t know.
Shanghai is a financial and cultural hub for the entire world. Shanghai has the longest metro system in the world with 644 km of tunnels and track.
"The Pearl of Asia" and "The Paris of the East" are two nicknames for Shanghai.
Hong Kong is famous for many towering skyscrapers. The tallest skyscraper in Hong Kong is The International Commerce Center. Hong Kong is recognized as the crossroads of East and West.
Hangzhou is a famous tourist destination in this country. One of China's seven historic capitals is Hangzhou. Hangzhou has been known as "Capital of Tea" since ancient times.
Chapters:
0:00-0:10 Intro
0:11-0:31 Shanghai
0:32-0:48 Hong Kong
0:49-1:01 Shanghai
1:02-2:17 Hangzhou, Zhejiang province
2:18-3:47 Hong Kong
3:48-4:20 Hangzhou, Zhejiang province
4:21-4:32 Suzhou, Jiangsu Province
4:33-4:38 Village, South China
4:39-4:48 Li River, Guangxi Province
4:49-5:02 Huangshan Mountain, Anhui Province
5:03-5:18 Great Wall
5:19-5:28 Hong Kong
5:29-5:35 Chinese clothes
5:36-5:45 Yu Garden, Shanghai
5:46-5:52 Hong Kong traffic
5:53-6:25 Shanghai traffic

Music:
Path Of The Fireflies by AERØHEAD
Somewhere Down The Line by AERØHEAD
https://soundcloud.com/aerohead/
Thumbnail image by Jeremy Zhu

Thanks for watching! Please do not forget to like, comment and subscribe.

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐢𝐜𝐫𝐨𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 : https://www.edureka.co/microse....rvices-architecture- (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎)
This Edureka Microservices Full Course video will help you learn Microservices from scratch with examples. This Microservices Tutorial is ideal for both beginners as well as professionals who want to master Microservices Architecture.
00:00:00 Introduction
00:01:03 Agenda
00:02:02 What are Microservices?
00:08:37 What is Microservice Architecture
00:10:38 Microservices Architecture
00:12:57 Features of Microservice Architecture
00:14:08 Advantages of Microservices Architecture
00:21:16 Monolithic Vs Microservices Architecture
00:25:55 Top Microservices Tools
00:44:36 Top 10 Reasons to learn Microservices
00:51:16 Microservice Design Pattern
01:19:04 Installing Spring Boot CLI & Spring Tool Suite
01:36:05 Microservices Spring Boot
01:55:19 Building REST Web Services with Spring Boot
01:58:57 How to Setup REST Services for Spring Boot Application
02:08:30 Microservices Security
02:25:15 Microservices Vs SOA
02:36:49 Use Case
02:42:57 Which is Better SOA Vs Microservices
02:43:06 Microservices Vs API
02:53:23 Microservices Interview Question & Answers

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What is Kubernetes?

Kubernetes is an open-source container orchestration platform that automates many of the manual processes involved in deploying, managing, and scaling containerized applications. You can cluster groups of hosts running Linux® containers, and Kubernetes helps you easily, efficiently manage those clusters.
It has a large, rapidly growing ecosystem. Kubernetes is not a traditional, all-inclusive PaaS (Platform as a Service) system. It can help you deliver and manage containerized, legacy, and cloud-native apps, as well as those being refactored into microservices.

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐞𝐚𝐜𝐭 𝐉𝐒 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐂𝐨𝐮𝐫𝐬𝐞 : https://www.edureka.co/reactjs....-redux-certification (Use code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎")
This Edureka React tutorial on ES5 to ES6 Refactoring will help you understand the current syntax being used in React and what new features you can use in the upgraded version. This video helps you to learn the following topics:
00:00:00 Introduction
00:00:30 Agenda
00:01:45 Introduction to React components
00:02:45 Component Structure using ES5
00:03:46 Rendering a Component
00:05.48 Component Structure in Facebook
00:06:27 Component Structure using ES5
00:08:00 Pros and Cons of ES5 Syntax
00:09:02 Building Our Application
00:09:55 React Components using ES5 Code example
00:17:12 Benefits of ES6
00:19:38 Advantages of ES6
00:24:50 ES5 vs ES6
00:29:19 ES6 restructuring of code example
00:31:26 Building Tic Tac Toe game in React using ES6

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🔵 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh

🌕 Artificial and Machine Learning PGD with E&ICT Academy
NIT Warangal: http://bit.ly/3OuZ3xs

📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 2023 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢
⏩ NEW Top 10 Technologies To Learn In 2023 - https://youtu.be/udD_GQVDt5g

📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
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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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Humanity's LAST Invention - Artificial General Intelligence (AGI)

Artificial General Intelligence has the whole world divided over it. While some are in support of the smart software technology having human cognition abilities, others fear that the outcome it might have on our world may be bad for the world. Will AGI become an essential invention for a better future or the final nail in the coffin of the world? Let’s find out in today’s video.

Don't forget to LIKE, SUBSCRIBE, and hit the NOTIFICATION BELL to stay updated on the latest technology news and breakthroughs in robotics! 💡

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TAGS: #AGI #artificialgeneralintelligence #artificialintelligence
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Want to know how creative web applications are developed? Our video about Streamlit will help you to know about the same.

This video about Streamlit Tutorial by Intellipaat will take a deep dive into What is Streamlit. Furthermore, it will explore more about its uses and Installation, and not only this but will also help you to understand the basic functions of Streamlit, Input widgets, and will end with its Practical Implementation.

Let’s first understand its preliminaries,

🔵 What is Streamlit?
With the help of the free, open-source Streamlit framework, data scientists can quickly create interactive dashboards and Machine Learning web apps without any prior front-end web programming knowledge.

🔵 Why Streamlit is used?
It enables us to quickly develop web applications for data science and machine learning. Major Python libraries like Scikit-learn, Keras, PyTorch, SymPy (latex), NumPy, pandas, and Matplotlib are all compatible with it.

🔵 Following topics are covered in this session:
00:00 - Introduction to Streamlit
1:59 - Uses of Streamlit
2:50 - Installation
5:01 - Streamlit Basic Functions
5:22 - Input Widgets
6:00 - Practical Implementation

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