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Explore the capabilities of AI with our latest YouTube video on ChatGPT's revolutionary memory feature. In this How To Use ChatGPT Memory comprehensive video, we detail how ChatGPT remembers information from your past interactions to tailor and enhance your ongoing experiences. We'll guide you through how this memory mechanism captures essential information and seamlessly integrates it into future discussions. Through vivid real-life scenarios, we demonstrate the practical applications of this technology—from improving project management to customizing educational content and remembering personal preferences. This video is perfect for anyone curious about the practical impacts of AI in daily life and those interested in the technical aspects of how AI can adapt and learn over time. Tune in to discover how ChatGPT's memory is making AI interactions more intuitive and impactful.

In this How To Use ChatGPT Memory video, we start with:
00:00:00 Introduction to ChatGPT Memory Feature
00:01:18 Features of ChatGPT's Memory Feature
00:01:48 How to enable and Manage ChatGPT's Memory Feature
00:03:39 Introducing Temporary Chat Feature
00:06:21 Applications of ChatGPT's Memory Feature using prompts
00:10:52 Delete or Remove ChatGPT's Memory
00:15:31 Other Examples of ChatGPT's Memory Feature using prompts

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➡️ About Post Graduate Program In AI And Machine Learning

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

✅ Key Features

- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
- 3 Capstones and 25+ Projects with industry data sets from Twitter, Uber, Mercedes Benz, and many more
- Master Classes delivered by Purdue faculty and IBM experts
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more
- Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools

✅ Skills Covered

- ChatGPT
- Generative AI
- Explainable AI
- Generative Modeling
- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- NLP
- Neural Networks
- Computer Vision
- And Many More…

👉 Enroll Now: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=10May24HowToUseChatGPTMemory&utm_medium=Description&utm_source=youtube
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** RPA Training: https://www.edureka.co/robotic....-process-automation- **
This session on UiPath Studio will give you an overview of UiPath Studio and its components.
Below are the topics covered in the video:
1:00 What is RPA?
3:05 RPA Tools
3:35 Introduction To UiPath Studio
4:09 UiPath Studio Installation
6:35 Projects in UiPath
10:47 UiPath Studio Components
11:32 Ribbon Components
21:03 Activity Components
25:13 Demo

RPA Playlist: https://bit.ly/2B53HLe
RPA Blog Series: https://bit.ly/2Ay1bzG

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How does it work?

1. This is a 4 Week Instructor-led Online Course, 25 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 have to work on a project, based on which we will provide you a Grade and a Verifiable Certificate!

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About the Robotic Process Automation Course

Edureka’s RPA training helps you to understand the concepts around Robotic Process Automation using the leading RPA tool named ‘UiPath’. Robotic Process Automation is the automation of repetitive and rules-based human tasks working with the software applications at the presentation/UI level i.e. no software integrations are needed at middleware, server or database levels. In this course, you will learn about the RPA concepts and will gain in-depth knowledge on UiPath tool using which you will be able to automate real-world processes at the enterprise level such as Insurance Claims Processing, Accounts Payable / Purchase Orders Processing, Invoice Processing, Complaints Management, Customer Feedback Analysis, Employee Onboarding, Compliance Reporting, and many more.

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What are the Objectives of our Robotic Process AutomationTraining?

After completing this course, you will be able to:

1. Know about Robotics Process Automation and their working
2. Assess the key considerations while designing an RPA solution
3. Work proficiently with the leading RPA tool ‘UiPath
4. Have practical knowledge on designing RPA solutions using UiPath
5. Perform Image and Text automation
6. Learn Data Manipulation using variables and arguments
7. Create automation with applications running in Virtual Environments
8. Debug and handle exceptions in workflow automation

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Why learn Robotic Process Automation?

Robotic Process Automation (RPA) is an automation technology for making smart software by applying intelligence to do high volume and repeatable tasks that are time-consuming. RPA is automating the tasks of a wide variety of industries, hence reducing the time and increasing the output.
Some of the facts about RPA include:

1. A 2016 report by McKinsey and Co. predicts that the robotic process automation market could be worth $6.7 trillion by 2025
2. A major global wine business, after implementing RPA, increased the order accuracy from 98% to 99.7% while costs reduced to Rs. 5.2 Crore
3. A global dairy company used RPA to automate the processing and validation of delivery claims, reduced goodwill write-offs by Rs. 464 Million

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What are the pre-requisites for this course?

To master the concept of RPA, you need to have a basic understanding of :

1.Basic programming knowledge of using if/else and switch conditions
2.Logical thinking ability

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).

🔥 Post Graduate Program In Full Stack Web Development: https://www.simplilearn.com/pgp-full-stack-web-development-certification-training-course?utm_campaign=4April2023DataStructureFullCourse2023&utm_medium=DescriptionFF&utm_source=youtube
🔥 Caltech Coding Bootcamp (US Only): https://www.simplilearn.com/coding-bootcamp?utm_campaign=4April2023DataStructureFullCourse2023&utm_medium=DescriptionFF&utm_source=youtube

Simplilearn's "Data Structure Full Course 2023" video will include the "Data Structures Complete Course Using C and C++." We will cover every topic of data structure, from the basics to the advanced level. Common data structures include arrays, linked lists, stacks, queues, trees, and graphs. Each of these data structures has pros and cons, and choosing the best one for your problem can enhance the performance and maintainability of your code dramatically.

✅01:54 What is a data structure?
✅07:56-What is an algorithm?
✅19:33-Pointers in data structure
✅28:23-Structure in data structure
✅35:09-Array in data structure
✅53:28-2D arrays
✅1:10:28-Linked list in data structure
✅1:51:13-Doubly linked list explained
✅2:04:44-Introduction to a circular linked list
✅2:18:03-Arrays vs linked list
✅2:23:48-Stacks in data structure
✅2:38:07-Stack implementation using an array
✅2:40:18-Stack implementation using a linked list
✅2:45:39-A complete guide to queue in data structure
✅5:19:48-Stack vs Queue
✅5:30:09-Tress in data structure
✅5:41:50-Binary tree in data structure
✅5:46:48-Tree traversal in data structure
✅5:58:30-Binary search tree in data structure
✅6:34:26-AVL tree in data structure

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⏩ Check out the Big Data training videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUUJqp1

#DataStructureFullCourse #DataStructureFullCourse2023 #DataStructures #DataStructure #DSA #Course #Simplilearn

What is data structure?
The data structure aims to store the elements in a way that allows it to perform a specified activity. It requires the least amount of memory capacity, allows for faster execution, and aids in data organization to improve accessibility. Data structures are the most convenient way to handle, retrieve, store, and organize data.

What is an Algorithm?
The algorithm is a step-by-step procedure or set of instructions to be followed to perform certain tasks.

What is a pointer?
A pointer is a variable that holds the address of another variable to be executed which can be of data type int, char, array, etc…

What is an Array?
An array is a homogenous collection of elements of the same data type; That means similar types of elements are stored under one name called an array name. And also the array of elements, stored in a consecutive block of memory.

What is a linked list?
A linked List is a linear data structure consisting of nodes. Each node in a linked list is divided into two sections that hold data and the address of the successive node, stored at the random address in the memory.

✅ About Post Graduate Program In Full Stack Web Development

This program will give you the foundation for building full stack web apps using the Java programming language. You'll begin with the basics of JavaScript, and then venture into some of the more advanced concepts like Angular, Spring Boot, Hibernate, JSPs, and MVC. Now is a perfect time to get started on your career as a full stack web developer!

✅ Skills covered

-Agile
-JAVA
-Hibernate and JPA
-Spring Core 50
-DevOps
-HTML5 and CSS3
-AWS
-JavaScript ES6
-ServletsSOAP and REST
-JSP

✅ Tools covered

-Angular
-CSS3
-Docker
-GIT
-html 5
-Jenkins
-Junit 5
-Maven
-mongodb
-MySQL
-RabbitMQ
-Selenium
-TypeScript

✅ Eligibility Criteria

-A bachelor's degree with an average of 50% or higher marks
-Basic programming knowledge
-Having 2+ years of work experience is preferred

👉Learn more at: https://www.simplilearn.com/pgp-full-stack-web-development-certification-training-course?utm_campaign=4April2023DataStructureFullCourse2023&utm_medium=Description&utm_source=youtube

🔥🔥 Interested in Attending Live Classes? Call Us: IN - 1800-212-7688 / US - +1-844-532-7688

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OpenAI has finally released the most anticipated ChatGPT model today, called "gpt-3.5-turbo". Unlike the GPT 3.0 models that work like a search engine, ChatGPT model tracks the conversation to create more useful outputs. In this tutorial, I will go through every single detail on how to get started with the newest OpenAI ChatGPT API in Python.

📑 Python Script Used In The Video: https://wp.me/payCAw-1lw

💻 Build Your Own ChatGPT Desktop App: https://youtu.be/snkys9zXyD0

✉ Signup for an OpenAI account: https://openai.com/

📑 OpenAI GPT Model Pricing: https://openai.com/pricing

📑 openai.ChatCompletion reference: https://platform.openai.com/docs/guides/chat

📑 OpenAI ChatGPT Model (gpt3.5 turbo) Info : https://platform.openai.com/docs/models/gpt-3-5

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00:00 - Intro to OpenAI gpt 3.5 turbo model
00:34 - OpenAI GPT-3.5 Pricing difference vs GPT-3.0
01:51 - OpenAI GPT 3.5 models summary
03:03 - Sign up for an OpenAI account
03:29 - Create an OpenAI API Key
03:47 - Create Python script
04:15 - Install OpenAI Python package
04:27 - open.ChatCompletion library usage
11:00 - Track ChatGPT conversation
15:03 - Make the Python script runs like ChatGPT

#chatgpt #chatgptapi #openai #ai #python #gpt

Welcome to Micromouse, the fastest maze-solving competition on Earth. Join Onshape’s community of over 3 million CAD users by creating a free account here: https://Onshape.pro/Veritasium.

▀▀▀
A huge thank you to Peter Harrison for all of his help introducing us to the world of Micromouse – check out https://ukmars.org & https://micromouseonline.com.
Thank you to David Otten, APEC, and the All-Japan Micromouse Competition for having us.
Thank you to Juing-Hei (https://www.youtube.com/@suhu9379) & Derek Hall (https://www.youtube.com/@MicroMouse) for usage of their micromouse videos.
Thank you to John McBride, Yusaku Kanagawa, and Katie Barnshaw for their help with Japanese translations.

▀▀▀
References:
Claude Shannon Demonstrates Machine Learning, AT&T Tech Channel Archive - https://ve42.co/ClaudeShannon
Mighty mouse, MIT News Magazine - https://ve42.co/MightyMouse
History, Micromouse Online Blog - https://ve42.co/MMHistory
Christiansen, D. (1977). Spectral lines: Announcing the Amazing Micro-Mouse Maze Contest. IEEE Spectrum, vol. 14, no. 5, pp. 27-27 - https://ve42.co/Christiansen1977
Allan, R. (1979). Microprocessors: The amazing micromice: See how they won: Probing the innards of the smartest and fastest entries in the Amazing Micro-Mouse Maze Contest. IEEE Spectrum, vol. 16, no. 9, pp. 62-65, - https://ve42.co/Allan1979
1977-79 – “MOONLIGHT SPECIAL” Battelle Inst. (American), CyberNetic Zoo - https://ve42.co/MoonlightSpecial
Christiansen, D. (2014). The Amazing MicroMouse Roars On. Spectral Lines - https://ve42.co/Christiansen2014
1986 - MicroMouse history, competition & how it got started in the USA, via YouTube - https://ve42.co/MMArchiveYT
The first World Micromouse Contest in Tsubuka, Japan, August 1985 [1/2] by TKsTclip via YouTube - https://ve42.co/MMTsukubaYT
IEEE. (2018). Micromouse Competition Rules - https://ve42.co/IEEERules
Tondra, D. (2004). The Inception of Chedda: A detailed design and analysis of micromouse. University of Nevada - https://ve42.co/Tondra2004
Braunl, T. (1999). Research relevance of mobile robot competitions. IEEE Robotics & Automation Magazine, vol. 6, no. 4, pp. 32-37 - https://ve42.co/Braunl1999
All Japan Micromouse 2017 by Peter Harrison, Micromouse Online - https://ve42.co/RedComet
Winning record of the national competition micromouse (half size) competition. mm3sakusya @ wiki (Google translated from Japanese) - https://ve42.co/JapanFinishTimes
The Fosbury Flop—A Game-Changing Technique, Smithsonian Magazine - https://ve42.co/FosburyFlop
Gold medal winning heights in the Men's and Women's high jump at the Summer Olympics from 1896 to 2020, Statistica - https://ve42.co/HighJump
Zhang, H., Wang, Y., Wang, Y., & Soon, P. L. (2016). Design and realization of two-wheel micro-mouse diagonal dashing. Journal of Intelligent & Fuzzy Systems, 31(4), 2299-2306. - https://ve42.co/Zhang2016
Micromouse Turn List, Keri’s Lab - https://ve42.co/MMTurns
Green Ye via YouTube - https://ve42.co/Greenye
Classic Micromouse, Excel 9a. Demonstrate fan suction, by TzongYong Khiew via YouTube - https://ve42.co/MMFanYT
Vacuum Micromouse by Eliot, HACKADAY - https://ve42.co/MMVacuum

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

▀▀▀
Written by Tom Lum and Emily Zhang
Edited by Trenton Oliver
Animated by Ivy Tello
Coordinated by Emily Zhang
Filmed by Yusaku Kanagawa, Emily Zhang, and Derek Muller
Additional video/photos supplied by Getty Images and Pond5
Music from Epidemic Sound
Thumbnail by Ren Hurley and Ignat Berbeci
References by Katie Barnshaw
Produced by Derek Muller, Petr Lebedev, and Emily Zhang

The world's strongest magnet is a million times stronger than Earth's magnetic field. Learn more about sustainability and Google’s efforts at sustainability.google. Part of this video was sponsored by Google.

Trends insights for the past year are based on Google Trends data from 2/10/2022 - 2/10/2023, U.S.

▀▀▀
Thanks to the entire NHMFL team - especially Tim, Stephen, Caroline, Kristin, Sam, Lance, and everyone who helped with the demos - for the great visit.
The NHMFL is funded by the National Science Foundation and the State of Florida.

Special thanks to Henry from Minutephysics for lending his magnet animations from our magnet collaboration: https://youtu.be/hFAOXdXZ5TM

▀▀▀
References:
Liu, Y., Zhu, D. M., Strayer, D. M., & Israelsson, U. E. (2010). Magnetic levitation of large water droplets and mice. Advances in Space Research, 45(1), 208-213.

Simon, M. D., & Geim, A. K. (2000). Diamagnetic levitation: Flying frogs and floating magnets. Journal of applied physics, 87(9), 6200-6204.

Berry, M. V., & Geim, A. K. (1997). Of flying frogs and levitrons. European Journal of Physics, 18(4), 307.

▀▀▀
Special thanks to our Patreon supporters:
Tj Steyn, Meg Noah, Bernard McGee, James Sanger, Elliot Miller, Jerome Barakos M.D., Amadeo Bee, TTST, Balkrishna Heroor, Chris LaClair, John H. Austin Jr., Eric Sexton, John Kiehl, Anton Ragin, Diffbot, Gnare, Dave Kircher, Burt Humburg, Blake Byers, Evgeny Skvortsov, Meekay, Bill Linder, Paul Peijzel, Josh Hibschman, Mac Malkawi, Juan Benet, Sunil Nagaraj, Richard Sundvall, Lee Redden, Stephen Wilcox, Marinus Kuivenhoven, Michael Krugman, Cy 'kkm' K'Nelson, Sam Lutfi

▀▀▀
Written by Derek Muller
Edited and Motion Graphics by Trenton Oliver
Coordinated by Emily Zhang and Derek Muller
Filmed by Derek Muller, Trenton Oliver, Raquel Nuno and Emily Zhang
Additional video/photos supplied by Pond5 & Getty Images
Music from Epidemic Sound
Thumbnail by Ignat Berbeci
Produced by Derek Muller, Petr Lebedev, and Emily Zhang

Large Language Models like ChatGPT have remarkable abilities to generate content based on training data but do they have actual intelligence? Find out more about how LLM's and Chatbots work as we explore this question.

Featuring:
Mira Murati the CTO of OpenAI
Cristóbal Valenzuela the creator of Runway

Presented by: Code.org, ETS, ISTE, Khan Academy

Start learning today!
https://code.org/ai/how-ai-works

Stay in touch with us on social media:
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Help make our work possible with a donation at http://code.org/donate!

In this video, learn how to build your own Small Language Model (SLM) from scratch using Python, PyTorch, and Hugging Face datasets. We’ll walk through every step — from data collection and preprocessing to tokenization, transformer architecture, and model training.

You’ll discover how a compact 10–15 million parameter model can still generate coherent and meaningful text, using concepts inspired by GPT models. This tutorial simplifies complex AI topics like embedding layers, attention mechanisms, loss computation, and next-token prediction — all explained clearly with working code examples.

🔹 Topics Covered:

What are Small Language Models (SLMs)?

Using the TinyStories dataset from Hugging Face

Tokenization with OpenAI’s tiktoken library

Creating .bin training files for efficient processing

Building a Transformer architecture step-by-step

Implementing GPT-like attention blocks

Training configuration and hyperparameter tuning

Generating text from your trained SLM

🎯 Perfect for AI researchers, ML engineers, and enthusiasts who want to understand how GPT-style models actually work under the hood — without requiring massive GPUs or billion-parameter setups.

#SmallLanguageModel #BuildLLM #GPT2Tutorial #TransformerModel #PyTorch #AIML #DeepLearning #NLP #HuggingFace #TrainYourOwnGPT #SLM #LanguageModel #MachineLearning #ArtificialIntelligence #NanoGPT #AIProjects #PythonCoding #AICoding #OpenSourceAI #generativeai

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai

November 18, 2025
This lecture covers career advice and a guest speaker.

To learn more about enrolling in this course, visit: https://online.stanford.edu/co....urses/cs230-deep-lea

Please follow along with the course schedule and syllabus: https://cs230.stanford.edu/syllabus/

View the playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

Guest Speaker
Laurence Moroney
Best-selling AI author and award-winning researcher

Andrew Ng
Founder of DeepLearning.AI
Adjunct Professor, Stanford University’s Computer Science Department

Kian Katanforoosh
CEO and Founder of Workera
Adjunct Lecturer, Stanford University’s Computer Science Department

🔥PGP in Generative AI and ML in collaboration with Illinois Tech: https://www.edureka.co/executi....ve-programs/pgp-gene
🔥Integrated MS+PGP Program in Data Science & AI:https://www.edureka.co/dual-ce....rtification-programs

This beginner-friendly AI course is designed to help you understand Artificial Intelligence from the ground up. You will learn the basics of AI, Machine Learning, and Deep Learning in simple and practical terms. The course covers key concepts, real-world examples, popular AI tools, and hands-on demonstrations to help you build a strong foundation.

By the end of this course, you will clearly understand how AI works, where it is used, and how to start your journey in the field of Artificial Intelligence with confidence.

📝Feel free to share your comments below.📝

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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

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

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Update: check out my latest video - the most realistic simulated movie to-date of the supermassive black hole in the centre of our own Milky Way galaxy! [https://youtu.be/wU3vRKczamc]

On smartphones this video is best viewed using the youtube app. Try google cardboard on your smartphone with a VR headset for the most immersive experience (smartphone with gyro sensor required). For desktop computers try viewing in Google Chrome browser or Firefox.

If you're in a hurry, jump forward to 2:00 where it gets really interesting.

Science note: this is a real physics calculation (not simulation or rendering) I did of what we would actually see if we were unfortunate enough to fall into a black hole, from far away all the way up to the event horizon! Each frame is rendered at a resolution of 8K and the video plays at 60fps. Calculations are performed using my own general relativistic ray tracing and radiative transfer computer code, 'BHOSS' (Younsi et al. 2017), i.e., solving the equations of motion of light/photons (null geodesics) for a given spacetime, in this case a spinning black hole (Kerr).

For now there are no Doppler or gravitational redshifting effects for the sake of clarity. I've omitted an accretion disk and proper radiative transport of light as it distracts from the gravitational lensing of the starlight and the black hole's shadow. Including an accretion disk or even a torus calculated from a proper general relativistic magnetohydrodynamical computer simulation of gas falling onto a black hole is also possible and I may do this in the future.

In this movie the black hole is spinning rapidly (almost at the maximum possible rate). The starfield is taken from real observational data. The movie starts one thousand gravitational radii away from the black hole and ends at the event horizon, where eventually all light focuses into a single point and vanishes. Try looking around as you approach, or you'll miss it!

I made this VR movie to promote the "Einstein Inside" exhibition touring Germany, where it was first shown in November and December at the Goethe University of Frankfurt. Copyright: Ziri Younsi.

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Movie produced from calculations utilising my general-relativistic radiation transfer code BHOSS, e.g., Ziri Younsi et al. 2012, 2016, 2020:
https://ui.adsabs.harvard.edu/....abs/2012A%26A...545A
https://ui.adsabs.harvard.edu/....abs/2016PhRvD..94h40
https://ui.adsabs.harvard.edu/....abs/2020IAUS..342...

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This Generative AI Full Course 2025 by Simplilearn provides a structured learning path, starting with the fundamentals of Generative AI and a detailed roadmap to mastering it. Learners explore top AI technologies, including DeepSeek R1, Deep Learning, and Search GPT, followed by essential tools like LangChain. The course dives into Generative Adversarial Networks (GANs), Transformers, and Long Short-Term Memory (LSTM) networks, forming the foundation of modern AI models. It then introduces Large Language Models (LLMs), Machine Learning concepts, and Reinforcement Learning, leading into practical applications like ChatGPT analysis and OpenAI Sora. Advanced topics include LLM benchmarking, Hugging Face tutorials, and OpenAI's ChatGPT O1 model. Practical insights into Generative AI tools for job interviews, Agentic AI, and AI monetization strategies help learners stay ahead in the field. The course concludes with a look at Google Quantum AI and Machine Learning interview preparation, ensuring a strong grasp of both theoretical and applied AI concepts.

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00:00:00 Introduction to Gen AI Full Course 2025
00:04:37 What is Gen AI ?
00:05:22 Gen AI Tutorial for beginners
00:16:01 Roadmap to become a Gen AI Engineer
00:25:51 Introduction to LLM
01:27:04 What is Machine Learning?
02:23:36 Machine Learning Tutorial
04:28:59 Reinforcement Learning
04:45:04 Deepseek r1
04:52:03 Deep Learning
05:00:20 Search GPT
05:02:35 Langchain
05:59:10 Generative Adversarial Tutorial
06:08:32 What are Gans
06:09:33 Transformers in AI
06:22:02 LSTM
06:41:53 CHatgpt analyse
06:52:49 Openai sora
07:01:42 LLM Benchmarkeing
07:52:25 Hugging Face and its tutorial
08:07:49 Open ai chatgpt o1 model
08:44:51 Agentic AI
08:53:14 Google Quantam AI
08:58:23 Gen ai tools for job interview
10:58:44 Deep learning Interview questions

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➡️ About Professional Certificate Program in Generative AI and Machine Learning

Dive into the future of AI with our Generative AI & Machine Learning course, in collaboration with E&ICT Academy, IIT Guwahati. Learn tools like ChatGPT, OpenAI, Hugging Face, Python, and more. Join masterclasses led by IITG faculty, engage in hands-on projects, and earn Executive Alumni Status.

Key Features:
✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
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✅ Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
✅ Opportunity to earn an 'Executive Alumni Status' from E&ICT Academy, IIT Guwahati
✅ Eligibility for a campus immersion program organized at IIT Guwahati
✅ Exclusive hackathons and “ask-me-anything” sessions by IBM
✅ Certificates for IBM courses and industry masterclasses by IBM experts
✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
✅ Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
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Skills Covered:
✅ Generative AI
✅ Prompt Engineering
✅ Chatbot Development
✅ Supervised and Unsupervised Learning
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Machine Learning Algorithms
✅ Speech Recognition
✅ Statistics

Learning Path:
✅ Program Induction
✅ Programming Fundamentals
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning with TensorFlow (IBM)
✅ Deep Learning Specialization
✅ Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ Advanced Generative AI
✅ Capstone
Electives:
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✅ NLP and Speech Recognition
✅ Reinforcement Learning
✅ Academic Masterclass
✅ Industry Masterclass

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This Excel Data Analytics Full Course video will help you understand the various crucial functions available in Excel, such as lookup, H lookup, sumif/s, counif/s, if error, and others. Finally, you will see how to use the Data Analysis Toolpak to perform various data analysis operations. So, let's begin.

00:00:00 Basic of excel data analysis
00:04:20 Lookup & functions in excel data analysis
01:37:58 Conditional formating in excel data analysis
01:54:30 Data validation in excel data analysis
02:36:30 Sorting and filtering in excel data analysis
03:23:55 Data analysis using toolpak in excel data analysis

Dataset Link: https://drive.google.com/drive..../folders/1U8CF0Xx3Ni

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What is Microsoft Excel?
Excel is one of the best applications available for creating spreadsheets to crunch numbers and dashboard reports and storing and administering data. This software first appeared on the scene back in 1987, and since then it has grown to become one of the most popular pieces of software for home or business. Excel can be used for data entry to store data in the form of a table, such as recording your daily expenses or business expenditure. It can also be used for inventory management.

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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.

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- Professional Program certificate and Alumni Association membership
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- Data Analytics
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- Data Analysis Python and R
- Data Visualization Tableau and Power BI
- Linear and logistic regression modules
- Clustering using kmeans
- Supervised Learning

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

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

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


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

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

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About Simplilearn Machine Learning course:

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

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What skills will you learn from this Machine Learning course?

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

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

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Who should take this Machine Learning Training Course?

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

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

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This Simplilearn video will acquaint you with the top 5 cybersecurity skills that will help you get into the field of cybersecurity. Today, a cybersecurity career is highly promising. Let's begin this cybersecurity shorts video!

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What Is Cyber Security?
Cyber Security involves techniques that help in securing various digital components, networks, data, and computer systems, from unauthorized digital access. There are several ways to implement cybersecurity, depending on the kind of network you are connected to and the type of cyberattacks you are prone to. A few ways to implement cybersecurity are defining clear boundaries, using network security control devices like Firewalls and IDS.


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This Post Graduate Program in Cyber Security is designed to equip you with the skills required to become an expert in the rapidly growing field of Cyber Security. This cyber security course aims to help you stay abreast all the latest trends in cyber security as well. This Post Graduate Program in Cyber Security will help you learn comprehensive approaches to protecting your infrastructure and securing your data, including risk analysis and mitigation, cloud-based security, and compliance. You will receive foundational to advanced security skills through industry-leading certification courses that are part of the program.


Key Features:
✅ Simplilearn Post Graduate Certificate
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✅ Featuring Modules from MIT SCC and EC-Council
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✅ Industry case studies in cyber security
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✅ Capstone project in 3 domains
✅ 25+ hands-on projects


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This Edureka video on Random Forest in Machine Learning explains the concept of the Random Forest algorithm in Python and how is it used.

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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!

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About the Course :

Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience.
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Why Learn Machine Learning with Python?

Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.
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