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Claude Code isn’t just another coding tool. t’s a game-changer for automation, DevOps, and productivity. Imagine combining the simplicity of Unix commands with the intelligence of an AI-powered assistant. That’s what Claude Code delivers.
From coding support to system maintenance, from workflow automation to custom commands, Claude Code is becoming an essential tool across industries.
🔥 Watch now and see how it can transform the way teams work.
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MIT 18.642 Topics in Mathematics with Applications in Finance, Fall 2024
Instructor: Peter Kempthorne
View the complete course: https://ocw.mit.edu/courses/18....-642-topics-in-mathe
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6
The lecture introduces linear algebra with a focus on its applications in quantitative finance, covering vector and matrix fundamentals, portfolio valuation, and concepts like short selling, arbitrage, and contingent claims. It further explores stochastic matrices and Markov chains, eigenvalues and eigenvectors, and their roles in modeling financial markets, culminating in discussions on no-arbitrage conditions, market completeness, and pricing measures essential for option pricing theory.
License: Creative Commons BY-NC-SA
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🔥NIT Warangal Post Graduate Diploma in AI & Machine Learning with Edureka: https://www.edureka.co/nitw-ai-ml-pgp
This Edureka video of "Chatbots using TensorFlow" gives you an idea about what are chatbots and how did they come into existence. It provides a brief introduction about all the layers involved in creating a chatbot using TensorFlow and Machine Learning.
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---------------------------------------Edureka Post Graduate Courses-------------------------------------------
🔵 Artificial and Machine Learning PGD: https://bit.ly/3AylL0q
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How it Works?
1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!
- - - - - - - - - - - - - -
About the Course
Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.
Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.
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Who should go for this course?
The following professionals can go for this course:
1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. Business Analysts who want to understand Deep Learning (ML) Techniques
4. Information Architects who want to gain expertise in Predictive Analytics
5. Professionals who want to captivate and analyze Big Data
6. Analysts wanting to understand Data Science methodologies
However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio.
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Why Learn Deep Learning With TensorFlow?
TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.
Machine learning is one of the fastest-growing and most exciting fields out there, and Deep Learning represents its true bleeding edge. Deep learning is primarily a study of multi-layered neural networks, spanning over a vast range of model architectures. Traditional neural networks relied on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kinds of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which constitutes the vast majority of data in the world.
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#Autoencoder #Tensorflow #DeepLearning #NeuralNetworks #python #MachineLearning #DimensionalityReduction
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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐀𝐖𝐒 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐂𝐨𝐮𝐫𝐬𝐞: https://www.edureka.co/aws-certification-training (Use code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎")
This Edureka "AWS CloudFront” video will introduce you to the fundamentals of AWS CloudFront and also explain various Content Delivery concepts.
00:00:00 Introduction
00:00:27 Agenda
00:00:49 What is AWS
00:02:40 Need for AWS CloudFront
00:04:47 What is AWS CloudFront
00:05:23 How AWS CloudFront Delivers Content
00:08:01 Applications
00:10:04 Demo
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⏩ NEW Top 10 Technologies To Learn In 2023 - https://youtu.be/udD_GQVDt5g
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Get a brief introduction to " Lean Six Sigma " in just 8 Minutes and clear your doubts on lean six sigma. Watch complete video to learn more!
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In this video, we'll tell you everything you need to learn about Lean Six Sigma in 8 minutes! We'll be covering a number of major concepts like Lean and Six Sigma, to help you answer the question: What is Six Sigma? These concepts are also explained with detailed examples.
So, without further ado, let's get started with Lean Six Sigma!
Don't forget to take the quiz at 07:08!
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#LeanSixSigma #WhatIsLearnSixSigma #LeanSixSigmaExplained #LeanSixSigmaExplainedSimply #LeanSixSigmaIn8minutes #Simplilearn
Learn to develop your organizational projects with the Lean Six Sigma Green Belt certification online program. Aligned to the IASSC exam, this online six sigma certification integrates lean and the DMAIC methodology with case studies to provide you the skills required for an organization's growth.
About Simplilearn SIx Sigma green belt course:
This Lean Six Sigma Green Belt course provides an overview of Six Sigma and the DMAIC methodology and is aligned to the leading Green Belt certifications at ASQ and IASSC. In this Lean Six Sigma Green Belt course, you will learn how to measure current performance to identify process issues and how to formulate solutions.
Six Sigma Green Belt Training Key Features:
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I Used Chat GPT To Predict Lottery Numbers (Update)
In this update, we dive back into our journey with ChatGPT 4, exploring its potential for lottery number predictions. We'll discuss methods like Python, machine learning, and even Excel for predicting lotto outcomes. Can we really predict the lottery? We'll look at the ChatGPT lottery, how to make money with it, and how to use the various ChatGPT plugins. We'll even show a brief ChatGPT tutorial by AI enthusiast Rico Copeland. Stay tuned as we delve deeper into the realm of AI and machine learning lottery predictions.
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And make sure you subscribe to my channel!
DISCLAIMER: Links included in this description might be affiliate links. If you purchase a product or service with the links that I provide I may receive a small commission. There is no additional charge to you! Thank you for supporting my channel so I can continue to provide you with free content each week!
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![Ethical Hacker Full Course - 10 Hours [2024] | Ethical Hacking Course For Beginners | Edureka](https://i.ytimg.com/vi/pqrp2OXxSWE/maxresdefault.jpg)
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Explore our Ethical Hacker Full Course and discover the techniques, tools, and strategies employed by ethical hackers to safeguard systems and networks from malicious attacks. From foundational concepts to advanced techniques, In this Ethical Hacking Course, you'll learn how to defend against cyber threats effectively. Whether you're a beginner or an experienced professional looking to enhance your cybersecurity skills, join us on this Ethical Hacking Full Course journey to become a certified ethical hacker and protect against cyber threats.
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🔵 Azure Cloud Engineer Masters Program: http://bit.ly/3AEBHzH
🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬
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🔵 Advanced Certificate Program in Cloud Computing with E&ICT Academy, IIT Guwahati: https://bit.ly/43vmME8
🌕Advanced Certificate Program in Cybersecurity with E&ICT Academy, IIT Guwahati: https://bit.ly/3Pd2utG
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Please write back to us at [email protected] or call us at IND: 9606058406 / US: +18338555775 (toll-free) for more information.
🔥Purdue - Ai And Machine Learning Post Graduate Certificate Program - https://www.simplilearn.com/applied-ai-course?utm_campaign=4qGrteTY1EM&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Professional Certificate Program in Generative AI and Machine Learning - IITG (India Only) - https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=4qGrteTY1EM&utm_medium=DescriptionFirstFold&utm_source=Youtube
This video by Simplilearn on How ChatGPT Works?covers the mechanism behind ChatGPT. From this video, we will understand the evolution of chatGPT.Alongside we will learn about the algorithms and models behind chatGPT, how chatGPT can resolve problems in coding, advantages, and disadvantages of chatGPT.
Don't forget to take the quiz at 5:15!
✅ 00:00 - How ChatGPT Works?
✅ 00:57 - What is ChatGPT?
✅ 01:20 - Evolution of ChatGPT
✅ 01:55 - How does ChatGPT work?
✅ 04:19 - Applications of ChatGPT
✅ 04:42 - Limitations of ChatGPT
#HowChatGPTWorks #WorkingOfChatGPT #ChatGPTForBeginners #WhatIsChatGPT #ChatGPT #ChatGPTWorking #ChatGPTTutorial #GPT #OpenAI #AI #Simplilearn
GPT aka Generative Pre-training Transformer has come a long way. Before the introduction of GPT, Natural Language Processing was used to deal with specific tasks with large amounts of data.ChatGPT uses deep learning techniques to generate human-like text. It is based on the machine learning model derived from the class called the Large Language Model.
ChatGPT is a byproduct of instrutGPT. InstructGPT introduced a strategy for integrating human feedback into the training process to match model outputs. This innovative technology made chatGPT exceptional.ChatGPT possesses the ability to automate content creation on social media, create chatbots on e-commerce sites, provide medical assistance by acting as a symptom checker, write code, and assist a developer.
✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH
⏩ Check out more Artificial Intelligence videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULyr_
➡️ 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…
👉 Learn More At: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=14March2023HowChatGPTWorks&utm_medium=Description&utm_source=youtube
🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688
🔥Professional Certificate Program in Generative AI and Machine Learning - IITG (India Only) - https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=pypqhQgi6yA&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Purdue - Ai And Machine Learning Post Graduate Certificate Program - https://www.simplilearn.com/applied-ai-course?utm_campaign=pypqhQgi6yA&utm_medium=DescriptionFirstFold&utm_source=Youtube
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
✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH
⏩ Check out More AI Videos By Simplilearn: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULyr_
➡️ 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
🔥🔥 *Interested in Attending Live Classes? Call Us:* IN - 18002127688 / US - +18445327688
✅ Inspiring Success Stories of Simplilearn's Learners: https://www.simplilearn.com/reviews?utm_campaign=10May24HowToUseChatGPTMemory&utm_medium=Description&utm_source=youtube
Learn how to build your own large language model, from scratch. This course goes into the data handling, math, and transformers behind large language models. You will use Python.
✏️ Course developed by @elliotarledge
💻 Code and course resources: https://github.com/Infatoshi/fcc-intro-to-llms
Join Elliot's Discord server: https://discord.gg/pV7ByF9VNm
⭐️ Contents ⭐️
(0:00:00) Intro
(0:03:25) Install Libraries
(0:06:24) Pylzma build tools
(0:08:58) Jupyter Notebook
(0:12:11) Download wizard of oz
(0:14:51) Experimenting with text file
(0:17:58) Character-level tokenizer
(0:19:44) Types of tokenizers
(0:20:58) Tensors instead of Arrays
(0:22:37) Linear Algebra heads up
(0:23:29) Train and validation splits
(0:25:30) Premise of Bigram Model
(0:26:41) Inputs and Targets
(0:29:29) Inputs and Targets Implementation
(0:30:10) Batch size hyperparameter
(0:32:13) Switching from CPU to CUDA
(0:33:28) PyTorch Overview
(0:42:49) CPU vs GPU performance in PyTorch
(0:47:49) More PyTorch Functions
(1:06:03) Embedding Vectors
(1:11:33) Embedding Implementation
(1:13:06) Dot Product and Matrix Multiplication
(1:25:42) Matmul Implementation
(1:26:56) Int vs Float
(1:29:52) Recap and get_batch
(1:35:07) nnModule subclass
(1:37:05) Gradient Descent
(1:50:53) Logits and Reshaping
(1:59:28) Generate function and giving the model some context
(2:03:58) Logits Dimensionality
(2:05:17) Training loop + Optimizer + Zerograd explanation
(2:13:56) Optimizers Overview
(2:17:04) Applications of Optimizers
(2:18:11) Loss reporting + Train VS Eval mode
(2:32:54) Normalization Overview
(2:35:45) ReLU, Sigmoid, Tanh Activations
(2:45:15) Transformer and Self-Attention
(2:46:55) Transformer Architecture
(3:17:54) Building a GPT, not Transformer model
(3:19:46) Self-Attention Deep Dive
(3:25:05) GPT architecture
(3:27:07) Switching to Macbook
(3:31:42) Implementing Positional Encoding
(3:36:57) GPTLanguageModel initalization
(3:40:52) GPTLanguageModel forward pass
(3:46:56) Standard Deviation for model parameters
(4:00:50) Transformer Blocks
(4:04:54) FeedForward network
(4:07:53) Multi-head Attention
(4:12:49) Dot product attention
(4:19:43) Why we scale by 1/sqrt(dk)
(4:26:45) Sequential VS ModuleList Processing
(4:30:47) Overview Hyperparameters
(4:32:14) Fixing errors, refining
(4:34:01) Begin training
(4:35:46) OpenWebText download and Survey of LLMs paper
(4:37:56) How the dataloader/batch getter will have to change
(4:41:20) Extract corpus with winrar
(4:43:44) Python data extractor
(4:49:23) Adjusting for train and val splits
(4:57:55) Adding dataloader
(4:59:04) Training on OpenWebText
(5:02:22) Training works well, model loading/saving
(5:04:18) Pickling
(5:05:32) Fixing errors + GPU Memory in task manager
(5:14:05) Command line argument parsing
(5:18:11) Porting code to script
(5:22:04) Prompt: Completion feature + more errors
(5:24:23) nnModule inheritance + generation cropping
(5:27:54) Pretraining vs Finetuning
(5:33:07) R&D pointers
(5:44:38) Outro
🎉 Thanks to our Champion and Sponsor supporters:
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https://github.com/krishnaik06..../Google-Gemini-Crash
In this video we will learn about we can create gen ai Large Language models and Large Image models app using Google Gemini pro and Vision.
Timestamp:
00:00:00 Introduction
00:01:22 Google Gemini Pro And Vision Demo
00:28:48 End To End LLM and LIM App
00:54:06 Conversational Q&A APP
01:08:30 Chat With Multiple Pdf
01:37:39 MultiLanguage Invoice extractor
02:03:26 Health MAnagement APP Using Gemini Pro
-----------------------------------------------------------------------------------------------------------
Support me by joining membership so that I can upload these kind of videos
https://www.youtube.com/channe....l/UCNU_lfiiWBdtULKOw
---------------------------------------------------------------------------------------------------------------------------
►Data Science Projects:
https://www.youtube.com/watch?v=S_F_c9e2bz4&list=PLZoTAELRMXVPS-dOaVbAux22vzqdgoGhG&pp=iAQB
►Learn In One Tutorials
Statistics in 6 hours: https://www.youtube.com/watch?v=LZzq1zSL1bs&t=9522s&pp=ygUVa3Jpc2ggbmFpayBzdGF0aXN0aWNz
Machine Learning In 6 Hours: https://www.youtube.com/watch?v=JxgmHe2NyeY&t=4733s&pp=ygUba3Jpc2ggbmFpayBtYWNoaW5lIGxlYXJuaW5n
Deep Learning 5 hours : https://www.youtube.com/watch?v=d2kxUVwWWwU&t=1210s&pp=ygUYa3Jpc2ggbmFpayBkZWVwIGxlYXJuaW5n
►Learn In a Week Playlist
Statistics:https://www.youtube.com/watch?v=11unm2hmvOQ&list=PLZoTAELRMXVMgtxAboeAx-D9qbnY94Yay
Machine Learning : https://www.youtube.com/watch?v=z8sxaUw_f-M&list=PLZoTAELRMXVPjaAzURB77Kz0YXxj65tYz
Deep Learning:https://www.youtube.com/watch?v=8arGWdq_KL0&list=PLZoTAELRMXVPiyueAqA_eQnsycC_DSBns
NLP : https://www.youtube.com/watch?v=w3coRFpyddQ&list=PLZoTAELRMXVNNrHSKv36Lr3_156yCo6Nn
---------------------------------------------------------------------------------------------------
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"🔥Introduction to Generative AI: https://www.edureka.co/introduction-generative-ai?
🔥Google I/O 2024, the annual developer conference held by Google, delivered a multitude of groundbreaking announcements and innovative advancements that are set to shape the future of technology. Held virtually and in-person, this year's event was a blend of immersive experiences, keynote presentations, and hands-on demos that captivated the global tech community. Do watch this video to know the key highlights from Google I/O 2024.
✅ 00:00 - Google I/O 2024
✅ 01:36 - GOOGLE WORKSPACE WITH GEMINI 1.5 Pro
✅ 02:14 - GOOGLE PHOTOS
✅ 03:24 - AI AGENTS
✅ 03:41 - PROJECT ASTRA
✅ 04:31 - Gemini 1.5 Flash
✅ 05:03 - VEO
✅ 05:16 - Google Search with AI
✅ 05:56 - Gems in Gemini 1.5 pro
✅ 06:25 - AI IN ANDROID
✅ 06:47 - Gemma Open Models
✅ 07:14 - Responsible AI
"
"✅Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV
📝Feel free to share your comments below.📝
𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬
🔵 DevOps Online Training: http://bit.ly/3VkBRUT
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🔵 Power BI Online Training: http://bit.ly/3VntjMY
🌕 Selenium Online Training: http://bit.ly/3EVDtis
🔵 PMP Online Training: http://bit.ly/3XugO44
🌕 Salesforce Online Training: http://bit.ly/3OsAXDH
🔵 Cybersecurity Online Training: http://bit.ly/3tXgw8t
🌕 Java Online Training: http://bit.ly/3tRxghg
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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬
🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬
🔵 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
🔵 Advanced Certificate Program in Cloud Computing with E&ICT Academy, IIT Guwahati: https://bit.ly/43vmME8
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📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_learning/
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📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/
- - - - - - - - - - - - - -
What is Generative AI?
Generative AI is a branch of artificial intelligence that focuses on producing or creating fresh content, such as images, text, audio, or even videos, that closely resembles data generated by humans. In contrast to conventional AI models that learn to identify patterns or make decisions based on existing data (discriminative models), generative AI models are trained to produce new data that mirrors the original training data.
- - - - - - - - - - - - - -
What is Prompt Engineering?
Prompt engineering involves optimizing artificial intelligence engineering for multiple purposes. It includes refining large language models (LLMs) using specific prompts and recommended outputs. Additionally, it focuses on enhancing input to different generative AI services to make text or images. With advancements in generative AI tools, prompt engineering becomes crucial for generating diverse content, such as robotic process automation bots, 3D assets, scripts, robot instructions, and various digital artifacts.
How can I get started with Generative AI?
- - - - - - - - - - - - - -
To get started with Introduction to Generative AI, you can:
Enroll in the Introduction to Generative AI Learning Path course.
Read research papers and books on Generative AI.
Experiment with open-source code repositories and frameworks.
Join online communities and forums to learn from others and seek advice.
For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: +18338555775 (toll-free)."
🔥 Edureka Big Data Courses: https://www.edureka.co/big-data-and-analytics
This Edureka video gives you a brief introduction to Big Data and how it is revolutionizing in various domains. In this quick guide, the following topics will be covered:
1. What Is Big Data?
2. Popular Use case of Big Data
3. Career Prospects in Big Data
----------------------------------------------
Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV
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Become an expert in the exciting new world of Big Data, get trained in cutting edge technologies, and work on real-life industry-grade projects.
----------------------------------------------
Why BIG Data?
The adoption of Big Data is growing across industries, which has resulted in an increased demand for Big Data Engineers. However, the supply is inadequate, leading to a large number of job opportunities. In this environment, professionals with appropriate skills can command higher salaries.
-----------------------------------------------
PG Program in Big Data Engineering
1. Ranked 2nd among NITs by MHRD
2. Recognized as an Institute of National Importance
3. Ranked among the Top 150 universities in Asia by Times Higher Education World University Rankings
-----------------------------------------------
Program Features
1. Mentorship from NITR faculty
2. Placement Assistance
3. Alumni Status
4. Industry Networking
-----------------------------------------------
Industry Projects
1. Retail: Forecasting Trends and Demand
2. Finance/Banking: Predictive Analytics & Fraud Detection
3. Social Media: Sentiment Analysis
-----------------------------------------------
Mentors & Instructors
Ashok Kumar Turk
Professor | NITR
Bibhudatta Sahoo
Associate Professor | NITR
Korra Sathya Babu
Assistant Professor Grade-I | NITR
--------------------------------------------
Is this program for me?
If you’re passionate about Big Data Engineering and want to pursue a career in this field, this program is for you. Whether you’re a fresher or a professional, this program is designed to equip you with the skills you need to rise to the top for a career in Big Data Engineering.
Is there any eligibility criteria for this program?
A potential candidate must have a Bachelor’s Degree preferably in BCA, MCA, and B.Tech.
Will I get any certificate at the end of the course?
Yes, you will receive a Post-Graduate industry-recognized certificate from NIT Rourkela upon the successful completion of the course.
For more information, Please write back to us at [email protected] or call us at IND: +91-9606058418 / US: 18338555775 (toll-free).
🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
This 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐓𝐮𝐭𝐨𝐫𝐢𝐚𝐥 is intended as a Crash Course on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 for Beginners. 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 has been growing in popularity exponentially. But, 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 is still not known to many people. In this video, I aim to show you the different ways in which you can use 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 for yourself.
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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬
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Transformer Neural Networks are the heart of pretty much everything exciting in AI right now. ChatGPT, Google Translate and many other cool things, are based on Transformers. This StatQuest cuts through all the hype and shows you how a Transformer works, one-step-at-a time.
NOTE: If you're interested in learning more about Backpropagation, check out these 'Quests:
The Chain Rule: https://youtu.be/wl1myxrtQHQ
Gradient Descent: https://youtu.be/sDv4f4s2SB8
Backpropagation Main Ideas: https://youtu.be/IN2XmBhILt4
Backpropagation Details Part 1: https://youtu.be/iyn2zdALii8
Backpropagation Details Part 2: https://youtu.be/GKZoOHXGcLo
If you're interested in learning more about the SoftMax function, check out:
https://youtu.be/KpKog-L9veg
If you're interested in learning more about Word Embedding, check out: https://youtu.be/viZrOnJclY0
If you'd like to learn more about calculating similarities in the context of neural networks and the Dot Product, check out:
Cosine Similarity: https://youtu.be/e9U0QAFbfLI
Attention: https://youtu.be/PSs6nxngL6k
If you'd like to support StatQuest, please consider...
Patreon: https://www.patreon.com/statquest
...or...
YouTube Membership: https://www.youtube.com/channe....l/UCtYLUTtgS3k1Fg4y5
...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store...
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...or just donating to StatQuest!
paypal: https://www.paypal.me/statquest
venmo: @JoshStarmer
Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
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0:00 Awesome song and introduction
1:26 Word Embedding
7:30 Positional Encoding
12:53 Self-Attention
23:37 Encoder and Decoder defined
23:53 Decoder Word Embedding
25:08 Decoder Positional Encoding
25:50 Transformers were designed for parallel computing
27:13 Decoder Self-Attention
27:59 Encoder-Decoder Attention
31:19 Decoding numbers into words
32:23 Decoding the second token
34:13 Extra stuff you can add to a Transformer
#StatQuest #Transformer #ChatGPT
MIT 14.01 Principles of Microeconomics, Fall 2023
Instructor: Prof. Jonathan Gruber
View the complete course: https://ocw.mit.edu/14-01F23
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6
In this lecture, Prof. Gruber talks about how consumers make decisions with budget constraints and constrained choice. How do consumers make decisions when they face a limit on their resources? Keywords: constrained choice, budget constraints, consumer preference, SNAP
License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu
Support OCW at http://ow.ly/a1If50zVRlQ
We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments.
Course details: https://stanford.io/4qjWTCk
Think back to the first time you had to tell a direct report their work wasn’t good enough, or persuade your supervisor to change course. For most new managers, those difficult conversations might not have gone as planned. But research shows these early moments can shape the trajectory of your entire career. The good news is you don’t have to wait for the next high-stakes conversation to get it right.
In this course, Stanford faculty combine decades of research with the emergent superpowers of generative AI to give you a “practice field” for leadership. You will rehearse critical conversations in a low-stakes environment and gain the skills and confidence to lead with authority and empathy.
You will learn to:
- Craft clear, respectful communication strategies that shift outcomes
- Give and receive constructive feedback that accelerates growth
Using generative AI, you will role-play high-pressure situations such as confronting difficult team members, motivating diverse talent, or disagreeing with your manager. Each practice round gives you structured, real-time feedback on tone, presence, and empathy so you can iterate and improve.
The course begins with three preset scenarios drawn from the experiences of Stanford alumni.
For each, you will:
- Observe: Hear how young leaders confronted real challenges
- Practice: Role-play with an AI partner as your conversational counterpart
- Get Feedback: Receive personalized feedback from our tough conversation AI coach
-Reflect and Repeat: Apply insights, refine your approach, and try again
Finally, you will design your own AI conversation partner for a current workplace challenge, building a personalized tool you can use beyond the course. Along the way, Stanford faculty share research, alumni share lived experiences, and you gain the playbook to shift your career trajectory.
Please note: This course requires a free ChatGPT account to participate in practice activities.
![Intro to Deep Learning -- L12 Intro to Convolutional Neural Networks (Part 1) [Stat453, SS20]](https://i.ytimg.com/vi/7ftuaShIzhc/maxresdefault.jpg)
Sebastian's books: https://sebastianraschka.com/books/
The lecture slides are available at: https://github.com/rasbt/stat4....53-deep-learning-ss2
Introduces the main ideas behind Convolutional Neural Networks (CNNs). The topics are:
Challenges of Image Classification
Convolutional Neural Network Basics
CNN Architectures
What a CNN Can See
CNNs in PyTorch
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.
