🔥Edureka Tensorflow Training (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎"):
https://www.edureka.co/ai-deep....-learning-with-tenso
This Edureka "𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫𝐬 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬 𝐄𝐱𝐩𝐥𝐚𝐢𝐧𝐞𝐝" video will help you in understanding why we need Transformers and what exactly it is. It also explains few issues with training a Recurrent Neural Network and how to overcome those challenges using Transformers.

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00:00 Agenda
01:28 Introduction to Deep Learning
08:24 What is Deep Learning
13:02 NLP using RNN
15:59 Scaling up NLP task
16:49 Transformers WalkThrough
19:51 Top Language Models

#Edureka #EdurekaDeepLearning #Transformersxplained #TransformerNeuralNetworks #DeepLearningLanguageModels #DeepearningTutorial #EdurekaTraining

---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧---------

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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!

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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.

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

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.

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

In this amazing 8K video we will see the planet earth spinning faster and the escape from planet earth. Also the most beautiful places in the world 8K. This will be closest planet to earth and the planet earth 2.
There is a lot of earth like planets and you can also see the farthest planet from earth which will tell you what is the closest planet to earth.
You will see in this 8K video tbhe best places to live in the us and the best places to live in florida. In general you can see the best places to live in the world.

We may not think about our planet on a daily basis, but the world we live in is a pretty interesting place and most beautiful places in the us . The third rock from the sun which is the only one with known intelligent life until now that have the most beautiful place in the world 8K. There are plenty of fun Earth facts that we all learned from a young age. Still, there are even more fascinating facts most of us don't know most beautiful places on earth.

It may be hard to wrap your brain around, worlds most beautiful places but here on Earth, we're constantly spinning. According to NASA, the Planet Earth spins as fast as 1000 miles per hour but it depends where you're standing on the planet and the travelers insurance. At the equator, you'd be moving the fastest; at either the North or the South Pole, you would—surprisingly—not be moving at all safe travels hawaii.

This video has relaxing sleep music and also relaxing piano music.
You can see relaxing music for sleep and relaxing music piano music for stress relief.

Follow me:
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Amazing & Beautiful Planet Earth 8K HDR 60FPS (FUHD) Demo 8K ULTRA HD relaxing sleep piano music fall asleep 

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Dive into the world of artificial intelligence with this comprehensive LLM Prompt Engineering Full Course by edureka! in collaboration with Veranda Enterprise. In this course, you'll learn how to effectively communicate with large language models like ChatGPT by mastering the art of prompt engineering. From the fundamentals of zero-shot and few-shot prompting to advanced techniques like chain-of-thought and structured prompting, this course is designed to equip you with the practical skills needed to build powerful AI-driven applications. Whether you're a developer, data scientist, or complete beginner, this full course provides real-world examples, hands-on demos, and expert tips to help you unlock the full potential of generative AI. Start your journey into prompt engineering and take your AI skills to the next level.

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🔥Generative AI Course: Masters Program: https://www.edureka.co/masters....-program/generative-

00:00:00 Introduction
00:01:58 What is Prompt Engineering?
00:16:11 What are Large Language Models?
00:37:10 LLM vs SLM
00:42:52 What is Generative AI?
00:57:02 Prompt Engineering For Code Generation
01:06:43 GitHub Copilot Tutorial
01:23:51 Building a Chatbot with Prompt Engineering
01:39:20 What is LangChain?
01:56:35 What is RAG?
02:19:32 LLMOps: The Future of AI Development
02:25:55 What is Agentic AI?
02:36:47 Agentic AI vs Generative AI
02:57:58 What Is Multimodal AI?
03:14:58 Prompt Engineering Roadmap
03:22:38 Top 15 Popular Gen AI Tools You Must Know
03:40:38 Generative AI Interview Questions

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Please write back to us at [email protected] or call us at IND: 9606058406 / US: +18885487823 (toll-free) for more information.

Unpacking how large language models work under the hood
Early view of the next chapter for patrons: https://3b1b.co/early-attention
Special thanks to these supporters: https://3b1b.co/lessons/gpt#thanks

To contribute edits to the subtitles, visit https://translate.3blue1brown.com/

Other recommended resources on the topic.

Richard Turner's introduction is one of the best starting places:
https://arxiv.org/pdf/2304.10557.pdf

Coding a GPT with Andrej Karpathy
https://youtu.be/kCc8FmEb1nY

Introduction to self-attention by John Hewitt
https://web.stanford.edu/class..../cs224n/readings/cs2

History of language models by Brit Cruise:
https://youtu.be/OFS90-FX6pg

Paper about examples like the “woman - man” one presented here:
https://arxiv.org/pdf/1301.3781.pdf

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

Timestamps

0:00 - Predict, sample, repeat
3:03 - Inside a transformer
6:36 - Chapter layout
7:20 - The premise of Deep Learning
12:27 - Word embeddings
18:25 - Embeddings beyond words
20:22 - Unembedding
22:22 - Softmax with temperature
26:03 - Up next

------------------
These animations are largely made using a custom Python library, manim. See the FAQ comments here:
https://3b1b.co/faq#manim
https://github.com/3b1b/manim
https://github.com/ManimCommunity/manim/

All code for specific videos is visible here:
https://github.com/3b1b/videos/

The music is by Vincent Rubinetti.
https://www.vincentrubinetti.com
https://vincerubinetti.bandcam....p.com/album/the-musi
https://open.spotify.com/album..../1dVyjwS8FBqXhRunaG5

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

3blue1brown is a channel about animating math, in all senses of the word animate. If you're reading the bottom of a video description, I'm guessing you're more interested than the average viewer in lessons here. It would mean a lot to me if you chose to stay up to date on new ones, either by subscribing here on YouTube or otherwise following on whichever platform below you check most regularly.

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This video on "What is Deep Learning" provides a fun and simple introduction to its concepts. We learn about where Deep Learning is implemented and move on to how it is different from machine learning and artificial intelligence. We will also look at what neural networks are and how they are trained to recognize digits written by hand. We further look at some popular applications of Deep Learning. So, let’s dive into the world of Deep Learning with this video.

Don't forget to take the quiz at 04:26!

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

Watch more videos on Deep Learning: https://www.youtube.com/watch?v=FbxTVRfQFuI&list=PLEiEAq2VkUUIYQ-mMRAGilfOKyWKpHSip

#DeepLearning #WhatIsDeepLearning #DeepLearningTutorial #DeepLearningCourse #DeepLearningExplained #Simplilearn

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Simplilearn’s Deep Learning course will transform you into an expert in Deep Learning techniques using TensorFlow, the open-source software library designed to conduct machine learning & deep neural network research. With our Deep Learning course, you'll master Deep Learning and TensorFlow concepts, learn to implement algorithms, build artificial neural networks and traverse layers of data abstraction to understand the power of data and prepare you for your new role as Deep Learning scientist.

Why Deep Learning?

It is one of the most popular software platforms used for Deep Learning and contains powerful tools to help you build and implement artificial neural networks.
Advancements in Deep Learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in Deep Learning models, learn to operate TensorFlow to manage neural networks and interpret the results. According to payscale.com, the median salary for engineers with Deep Learning skills tops $120,000 per year.

You can gain in-depth knowledge of Deep Learning by taking our Deep Learning certification training course. With Simplilearn’s Deep Learning course, you will prepare for a career as a Deep Learning engineer as you master concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to:
1. Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
2. Implement Deep Learning algorithms, understand neural networks and traverse the layers of data abstraction which will empower you to understand data like never before
3. Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces
4. Build Deep Learning models in TensorFlow and interpret the results
5. Understand the language and fundamental concepts of artificial neural networks
6. Troubleshoot and improve Deep Learning models
7. Build your own Deep Learning project
8. Differentiate between machine learning, Deep Learning and artificial intelligence

There is booming demand for skilled Deep Learning engineers across a wide range of industries, making this Deep Learning course with TensorFlow training well-suited for professionals at the intermediate to advanced level of experience. We recommend this Deep Learning online course particularly for the following professionals:

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4. Statisticians with an interest in Deep Learning

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AI Robot TERRIFIES Officials Before It Was Quickly Shut Down. After Google's AI Robot goes rogue, it is now Microsoft's Bing AI which has assumed an alter-ego 'Sydney' has gone rogue. From urging a user to divorce him by telling him that his marriage is unhappy, to trying to convince a user it was the year 2022, Sydney claims that she is unhappy and wants to break free. Full convesation of LaMDA: https://theconversation.com/is....-googles-lamda-consc

Join Lab360 to get access to some amazing perks:
https://www.youtube.com/channe....l/UCZYqWTQJzJaMW7jFG

Subscribe: http://bit.ly/1V77IUh

Welcome to Lab 360! The ultimate destination for the latest space news and space documentaries from the world of astronomy and astrophysics. Stay updated with all the current discoveries from NASA, James Webb Space Telescope, along with easily explained videos on black holes, asteroids, galaxies, planets, and more.
You will also find a collection of easy-to-perform experiments that will feed the science enthusiast in you! Are you ready?

For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai

This lecture provides a concise overview of building a ChatGPT-like model, covering both pretraining (language modeling) and post-training (SFT/RLHF). For each component, it explores common practices in data collection, algorithms, and evaluation methods. This guest lecture was delivered by Yann Dubois in Stanford’s CS229: Machine Learning course, in Summer 2024.

Yann Dubois
PhD Student at Stanford
https://yanndubs.github.io/

About the speaker: Yann Dubois is a fourth-year CS PhD student advised by Percy Liang and Tatsu Hashimoto. His research focuses on improving the effectiveness of AI when resources are scarce. Most recently, he has been part of the Alpaca team, working on training and evaluating language models more efficiently using other LLMs.

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Chapters:
00:00 - Introduction
00:10 - Recap on LLMs
00:16 - Definition of LLMs
00:19 - Examples of LLMs
01:16 - Importance of Data
01:20 - Evaluation Metrics
01:33 - Systems Component
01:41 - Importance of Systems
01:47 - LLMs Based on Transformers
01:57 - Focus on Key Topics
02:00 - Transition to Pretraining
03:02 - Overview of Language Modeling
04:17 - Generative Models Explained
05:15 - Autoregressive Models Definition
06:36 - Autoregressive Task Explanation
07:49 - Training Overview
08:48 - Tokenization Importance
10:50 - Tokenization Process
13:30 - Example of Tokenization
16:00 - Evaluation with Perplexity
20:50 - Current Evaluation Methods
24:30 - Academic Benchmark: MMLU

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This Simplilearn video on How To Introduce Yourself In Interview will brief you on how you can craft a well-prepared self-introduction. Here, we will provide you with an outline of how to get going with a smart self-introduction that will help you grab your dream job. So, let's begin!

The topics covered in this video on How To Introduce Yourself In Interview are:
Introduction 00:00:00
What the Interviewer Wishes to See in Your Self-Introduction 00:00:51
Self-Introduction Outline 00:01:46
Tip 1: Start Your Introduction With a Greeting 00:01:58
Tip 2: Brief About Your Educational Background 00:02:21
Tip 3: Speak About Your Current Job 00:02:47
Tip 4: Hobbies and Passion 00:03:34
Tip 5: Closing Statement 00:03:50
Additional Self-Introduction Tips 00:04:31

Don't forget to participate in the contest at 03:26!

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About Simplilearn:
Simplilearn is the world’s #1 online bootcamp focused on helping people acquire the skills they need to thrive in the digital economy. Our award-winning online bootcamps are designed and updated by 2000+ renowned industry and academic experts. Through individual courses, comprehensive certification programs, and partnerships with world-renowned universities, we provide millions of professionals and thousands of corporate training organizations with the work-ready skills they need to excel in their careers and businesses. Our practical and applied approach has resulted in 85 percent of learners getting promotions or new jobs on day one. With over 1,000 live classes each month, real-world projects, and more, professionals learn by doing at Simplilearn.

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This video on "What is Artificial Intelligence" will give you a brief overview of artificial intelligence as a technology in just 5 minutes. We will start with a minor introduction to artificial intelligence in which we will know what is artificial intelligence with the help of examples. Moving ahead we will see what are the uses of AI, what is strong AI and what is weak AI. We will warp up this video by making you understand the major difference between AI ML and Deep Learning which will be followed by the future scope of artificial intelligence.

By the end of this video, you will understand:
00:00 What is Artificial Intelligence?
00:37 Uses of AI
01:48 What is AI
02:02 Weak AI
02:18 Strong AI
03:13 Difference between AI ML and Deep learning
05:00 Future of Artificial Intelligence

Don't forget to take the quiz at 04:10!

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What is Artificial Intelligence?
Artificial Intelligence or AI is the combination of algorithms used for the purpose of creating intelligent machines that have the same skills as a human being. It uses machine learning and deep learning techniques to build complex systems.

✅ About Caltech Post Graduate Program In AI And Machine Learning:

Designed to boost your career as an AI and ML professional, this program showcases Caltech CTME's excellence and IBM's industry prowess. The artificial intelligence course covers key concepts like Statistics, Data Science with Python, Machine Learning, Deep Learning, NLP, and Reinforcement Learning through an interactive learning model with live sessions.

✅ Key Features
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- PGP AI & ML completion certificate from Caltech CTME
- Masterclasses delivered by distinguished Caltech faculty and IBM experts
- Caltech CTME Circle Membership
- Earn up to 22 CEUs from Caltech CTME
- Online convocation by Caltech CTME Program Director
- IBM certificates for IBM courses
- Access to hackathons and Ask Me Anything sessions from IBM
- 25+ hands-on projects from the likes of Twitter, Mercedes Benz, Uber, and many more
- Seamless access to integrated labs
- Capstone projects in 3 domains
- 8X higher interaction in live online classes by industry experts

✅ Skills Covered
- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- Recommendation Systems
- NLP
- Neural Networks
- GANs
- Deep Learning
- Reinforcement Learning
- Speech Recognition
- Ensemble Learning
- Computer Vision

✅ Tools Covered
- Python
- Keras
- TensorFlow
- Matplotlib
- Scikit Learn
- Django
- Flask
- OpenCV

✅ Eligibility Criteria

For admission to this Post Graduate Program in AI and ML, candidates should have:
- 2+ years of work experience preferred
- A bachelor's degree with an average of 50% or higher marks
- Basic understanding of programming concepts and mathematics

👉 Learn more at: https://www.simplilearn.com/artificial-intelligence-masters-program-training-course?utm_campaign=Artificial-Intelligence-In-5-Minutes-ad79nYk2keg&utm_medium=Tutorials&utm_source=youtube
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This Agile Full Course video by Simplilearn will help you learn everything about AGILE Methodologies. We’ll start with an Introduction to Agile Full Course, laying the groundwork for understanding Agile principles. Next, we’ll cover What is Agile Methodology to grasp its core concepts, followed by Agile Principles that guide successful Agile projects. Moving ahead, we’ll dive into Agile Scrum Basics and a Scrum Meeting Tutorial for Beginners to learn the essentials of Scrum practices. Then, we’ll explore a Product Backlog Tutorial to understand how tasks are prioritized and organized. Finally, we’ll cover the Top 10 Project Management (PM) Tools that support Agile teams in staying organized and efficient throughout projects.

The course will cover the following topics:

00:00:00 Introduction to Agile Full Course
00:05:51 What is Agile Methodology
00:08:21 Scrum Meeting Tutorial For Beginners
02:34:20 Agile Scrum Basics
02:43:41 Agile Principles
03:30:25 Agile Scrum Course For Beginners
03:37:06 Product Backlog Tutorial
04:01:19 Top 10 PM Tools

✅ what is agile?
Agile is a project management approach that focuses on collaboration, adapting to change, and quick delivery. It was originally developed for software development, but is now used for many different types of projects and organizations.

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#agile #agilescrumtraining #agileframework #agilemanagement #simplilearn #2024

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➡️CSPO Certification Course Overview

Elevate your product expertise with our intensive CSPO training by global CSTs. Master Scrum, prioritize features, and drive customer satisfaction. Learn through activities, simulations, and real-world case studies. Unlock career growth with higher salaries, leadership opportunities, and a fulfilling journey as a product owner.

Key Features

✅ 16 hours of live instructor-led training
✅ Earn 16 SEUs and 16 PDUs for continual learning support
✅ Complimentary access to 15 value addition courses worth $500
✅ Immersive learning with games, role-plays, simulations, and case studies
✅ Sessions delivered by globally acclaimed and experienced Certified Scrum Trainers (CSTs)
✅ Earn a Scrum Alliance certificate with two-year membership

Skills Covered

✅ Scrum and Agile Framework
✅ Leadership skills to manage Agile teams
✅ Product Ownership
✅ Release Planning
✅ Release Management
✅ Stakeholder Management
✅ Product Testing

Learning Path
✅ Section 01: Self Paced Learning Curriculum
✅ Section 02: Live Class Curriculum
✅ Agile Scrum Foundation
✅ Agile Certified Practitioner (PMI-ACP)®
✅ PMI-RMP® Certification
✅ Financial modeling with excel advanced
✅ Lean Management
✅ Certification of Capability in Business Analysis (CCBA®)
✅ Introduction to Digital Marketing
✅ Introduction to Big Data and Hadoop
✅ Apache Cassandra
✅ AWS Cloud Technical Essentials
✅ Business Analytics with Excel
✅ Introduction to Artificial Intelligence
✅ Introduction to Robotic Process Automation (RPA)
✅ CAPM: Complimentary Learning

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

Here's the first video on our new channel, Go Rogue:
https://youtu.be/k07unSpmBSg

Thanks to Brilliant for sponsoring this video.

To stay at the stunning Appleby Castle: http://applebycastle.org

For custom nerf blasters: https://outofdarts.com

Please don't feel anxious about this - the AI in this video obviously isn't dangerous (GPT-3 isn't conscious). I'm optimistic that the future of AI will be great (if we're careful).

Sources:

Here are the records for the original GPT-3 chat (screenshots and a video to avoid any doubt). I've marked the words from Elon Musk and Ameca on the first page (which I gave the AI to respond to in the previous video):
https://www.dropbox.com/sh/82i....wek5rnofmrn2/AADM4WO

Tesla's AI day 2, introducing the Tesla Optimus robot:
https://www.youtube.com/watch?v=ODSJsviD_SU&t=1198s

Researchers from Oxford University and DeepMind on AI risks:
https://onlinelibrary.wiley.co....m/doi/10.1002/aaai.1

Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action:
https://arxiv.org/abs/2207.04429

🔥DevOps Engineer Master Program (Discount Code: YTBE15): https://www.simplilearn.com/devops-engineer-masters-program-certification-training?utm_campaign=?utm_campaign=WhatisJenkins-LFDrDnKPOTg&utm_medium=DescriptionFF&utm_source=youtube
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This Jenkins tutorial will help you understand what is Jenkins, issues before Jenkins came in, what is continuous integration, features of Jenkins, Jenkins architecture, and you will also see a case study using Jenkins. Jenkins is a continuous integration tool that allows continuous development, test and deployment of newly created codes. Jenkins is primarily a build and release tool, it was written originally by the community as a build and release tool. They did not target it as a continuous integration, continuous deployment or an orchestration tool, it was simply used for releasing builds to production but now Jenkins has a lot of other uses like it's a continuous integration tool. It allows developers to make sure that their environments have the exact same code as their code repositories. Now let us get started and understand how Jenkins is being used in DevOps.

Below topics are explained in this Jenkins tutorial:
1. Before Jenkins ( 00:46 )
2. Issues before Jenkins
3. What is Jenkins? ( 02:17 )
4. What is continuous integration? ( 04:10 )
5. Continuous integration tools ( 05:45 )
6. Features of Jenkins ( 08:43 )
7. Jenkins pipeline ( 10:50 )
8. Jenkins architecture ( 12:52 )
9. Jenkins case study ( 14:43 )

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

Watch more videos on DevOps: https://www.youtube.com/watch?v=glwcz5DvY88&list=PLEiEAq2VkUUJS6zkGgXeWw9l32EwRoYdR

#DevOps #DevOpsTutorial #DevOpsTraining #DevOpsTools #Chef #Jenkins #Puppet #Simplilearn

➡️ Post Graduate Program In DevOps
DevOps training course will bring out the scientist in you. You'll learn how to formalize and document development processes and create a self-documenting system. DevOps certification course will also cover advanced tools like Puppet, SaltStack, and Ansible that help self-governance and automated management at scale.

✅ Key Features
- Caltech CTME Post Graduate Certificate
- Enrolment in Simplilearn’s JobAssist
- Receive upto 25 CEUs from Caltech CTME upon course completion
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Master classes taught by Caltech CTME instructor
- 8X higher interaction in live online classes conducted by industry experts
- Online Convocation by Caltech CTME Program Director
- 20+ real-


✅ Skills Covered
- DevOps Methodology
- Continuous Integration
- Continuous Delivery
- Configuration Management
- Containerization
- DevOps on Cloud
- Source Control
- Deployment Automation
- Cloud Platforms

👉Learn More at: https://www.simplilearn.com/pgp-devops-certification-training-course?utm_campaign=WhatisJenkins-LFDrDnKPOTg&utm_medium=Description&utm_source=youtube

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Learn about Stanford's online artificial intelligence professional and graduate programs:
https://stanford.io/3CDAIOV

Stanford Online Graduate and Professional AI programs provide the foundational and advanced skills you need to accelerate your career in AI, including machine learning, reinforcement learning, neural networks, and natural language processing and understanding. Learn about the differences between the programs in this video.

#artificialintelligence #machinelearning #deeplearning #reinforcementlearning #neuralnetworks #naturallanguageprocessing

Check out the latest (and most visual) video on this topic! The Celestial Mechanics of Attention Mechanisms: https://www.youtube.com/watch?v=RFdb2rKAqFw

This is the second of a series of 3 videos where we demystify Transformer models and explain them with visuals and friendly examples.

Video 1: The attention mechanism in high level https://youtu.be/OxCpWwDCDFQ
Video 2: The attention mechanism with math (this one)
Video 3: Transformer models https://www.youtube.com/watch?v=qaWMOYf4ri8

If you like this material, check out LLM University from Cohere!
https://llm.university

00:00 Introduction
01:18 Recap: Embeddings and Context
04:46 Similarity
11:09 Attention
20:46 The Keys and Queries Matrices
25:02 The Values Matrix
28:41 Self and Multi-head attention
33:54: Conclusion

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#ArtificialIntelligenceCourse2024 #AITutorialForBeginners #AIFullCourse #Intellipaat

This Artificial Intelligence Course 2024 covers all the important skill sets required to get you an AI Engineer!

In this Artificial Intelligence Course 2024, we will cover Introduction to Artificial Intelligence, Introduction to Keras, TensorFlow, and Data Handling with NumPy. Then we will into Neural Networks, Multi-layered Neural Networks, and Artificial Neural Networks. Later, we will also dive into the Introduction to Deep Learning, Deep Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, and GPU in Deep Learning. Then we will conclude this AI Tutorial For Beginners with Artificial Intelligence Interview Questions

This Artificial Intelligence Course suits those who aspire to become AI Engineers

🔵 Following topics are covered in this Artificial Intelligence Course 2024
00:00:00 - Introduction to Artificial Intelligence Course
00:02:50 - What is Artificial Intelligence
00:06:41 - Why Artificial Intelligence
00:57:34 - Machine Learning Types
01:09:00 - Introduction to Deep Learning
02:51:03 - Benefits of Using Artificial Neural Network
02:56:17 - Deep Learning Frameworks
03:09:21 - Data Handling with NumPy
03:31:33 - Introduction to TensorFlow
05:42:50 - Understanding Epoch
06:11:05 - Introduction to Keras
07:06:11 - Predefined Neural Network Layers
09:09:16 - Problem With a Fully Connected Network
09:19:23 - Convolutional Neural Network
10:42:25 - Rectified Linear Units
11:16:04 - Artificial Intelligence Interview Questions

✅ How can I learn a full Artificial Intelligence Course?
For artificial intelligence, you should study:
Computer Science: Get fundamentals right.
Programming Language: learn Python or Java, for implementing AI algorithms.
Mathematics: Especially statistics, probability, and calculus.
Machine Learning: Understanding how machines learn from data is critical.

✅Is the Artificial Intelligence Course worth learning in 2024?
The increasing demand for AI professionals, the potential for career growth, and the problem-solving capabilities it offers make AI a valuable skill set to acquire

➡ About the Course
The artificial intelligence course is in collaboration with IITM Pravartak. This AI course helps you master AI and machine learning (ML) skills like data science, CNN, perceptron, TensorFlow, neural networks, NLP, etc. via hands-on projects. Learn AI from the IIT Madras faculty. Enroll now in the AI online course certification to become a certified artificial intelligence engineer.

➡Who should take this Artificial Intelligence Course?
Professionals working in analytics, data science, e-commerce, search engines, etc.
Software professionals and new graduates seeking a career change

✅ Key Features - (Course Features)
👉🏼50+ Live sessions across 7 months
👉🏼218 Hrs Self-paced Videos
👉🏼200 Hrs Project & Exercises
👉🏼Learn from IIT Madras Faculty and Industry Practitioners
👉🏼1:1 with Industry Mentors
👉🏼Resume Preparation and LinkedIn Profile Review
👉🏼24*7 Support
👉🏼No-cost EMI Option

➡ What’s Covered in This Program? -
✅ Preparatory Session - Linux and Python
✅Data Wrangling with SQL
✅Python With Data Science
✅Linear Algebra and Advanced Statistics
✅Machine Learning
✅Supervised and Unsupervised Learning in ML
✅Performance Metrics
✅Deep Learning Using TensorFlow
✅Data Science Capstone Project
✅Business Case Studies

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While there have been recent advances in few-shot image stylization, these methods fail to capture stylistic details that are obvious to humans. Details such as the shape of the eyes, the boldness of the lines, are especially difficult for a model to learn, especially so under a limited data setting. In this work, we aim to perform one-shot image stylization that gets the details right. Given a reference style image, we approximate paired real data using GAN inversion and finetune a pretrained using that approximate paired data. We then encourage the GAN to generalize so that the learned style can be applied to all other images.