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This Edureka video on Machine Learning Tutorial will give you an introduction to Machine Learning with practical examples.
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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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Who should go for this Course?
Edureka’s Python Machine Learning Certification Course is a good fit for the below professionals:
Developers aspiring to be a ‘Machine Learning Engineer'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
'Python' professionals who want to design automatic predictive models
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This video on What is Machine Learning will make you understand the basics of Machine Learning and how Machine Learning works. By the end of this tutorial, you will be able to understand the different types of Machine Learning algorithms and some of the breakthroughs in the Machine Learning field. You will also learn what machine learning has to offer in terms of career opportunities in this machine learning tutorial.
This Machine Learning tutorial video will cover the following topics:
00:00 - 00:55 Real-life applications of Machine Learning
00:55 - 01:56 Challenges before Machine Learning
01:56 - 02:41 How did Machine Learning evolve?
02:41 - 03:48 Why Machine Learning / Machine Learning benefits
03:48 - 04:48 What is Machine Learning?
04:48 - 05:22 Types of Machine Learning
05:22 - 08:44 Machine Learning algorithms
08:44 - 12:57 Breakthroughs in Machine Learning
12:57 - 14:38 Machine Learning future
14:30 - 15:26 Machine Learning career
15:26 - 17:10 Machine Learning job trends
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What is Machine Learning?
Machine Learning is a method that enables computers to imitate and adapt human-like behaviour, just like you and me. It isn’t programmed to perform a task. It analyses the data it has received previously, learns from it, and makes predictions or decisions for the problem scenario. In a way, the computer is training itself to perform a task the right way, after it learns everything it can from the data.
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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.
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This video introduces you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. Attention is used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering.
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Welcome to Simplilearn's Introduction to Prompt Engineering video! In this video, we'll take a few minutes to explain what prompt engineering is and why it's becoming a game-changer in the world of AI. From understanding the basics of prompt engineering to exploring some of the most common use cases, we'll cover everything you need to know to get started with this exciting topic. So, let's dive in and explore the world of prompt engineering together!
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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
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- 3 Capstones and 25+ Projects with industry data sets from Twitter, Uber, Mercedes Benz, and many more
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- 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…
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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.
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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…
👉 Learn More At: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=14March2023HowChatGPTWorks&utm_medium=Description&utm_source=youtube
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Learn the essentials of working with AI in the cloud from @ExamProChannel. This comprehensive course covers the complete generative AI development lifecycle - from fundamental concepts through practical implementation, including prompt engineering, development tools, deployment, optimization, and advanced topics like RAGs and AI agents.
More course info: https://www.exampro.co/exp-genai-001
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⭐️ Contents ⭐️
- 00:00:00 Introduction
- 00:54:16 AI and ML Fundamentals
- 03:02:21 Gen AI Primer
- 03:32:55 Data and ML
- 03:47:56 LLM Basics
- 04:12:22 AI Powered Assistants
- 04:24:42 Env Setup
- 06:12:17 Prompt Engineering
- 07:00:25 WorkBenches and Playgrounds
- 07:44:09 Model as a Service
- 08:36:26 LLM DevTools and Workflow
- 11:52:07 AI Code Assistants
- 14:04:37 App Prototyping
- 17:21:06 Containers
- 18:12:43 Serving
- 18:19:51 AI Delivery Platform
- 19:40:45 GenAI Hardware
- 19:50:21 Framework
- 19:51:49 LLM Customization
- 19:52:35 SFT
- 19:56:25 Size Optimization
- 20:26:04 RAGS
- 22:21:19 Agents
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This Video on Cloud Computing Full course by simplilearn will help you learn the basics of cloud computing. this Simplilearn video is a complete tutorial for cloud computing engineers. It begins with an introduction to cloud computing, followed by a detailed explanation of AWS and its features. Next, you'll explore a roadmap to becoming a cloud engineer, along with insights into cloud security. The video also covers cloud service models and a comparison of AWS vs. Azure. Moving ahead, you'll find exciting cloud computing project ideas to enhance your portfolio. Lastly, the video discusses essential cloud computing certifications to help you advance your career. This comprehensive tutorial is designed to equip you with the skills and knowledge needed to excel in the field of cloud computing.
00:00:00 Introduction to Cloud Computing
00:05:23 What is Cloud Computing
00:10:15 What is AWS?
00:19:36 How to become Cloud Engineer
03:20:20 Cloud Computing Tutorial
03:26:51 What is Cloud Security
08:14:18 Cloud Computing Service Models
08:24:35 AWS Vs Azure
08:25:20 Cloud Computing Project ideas
08:40:13 Cloud Computing Certifications
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➡️ About AWS Cloud Practitioner Course
AWS Cloud Practitioner course is for individuals seeking an overall understanding of Amazon Web Services Cloud, independent of specific technical roles. To build AWS Cloud knowledge, you will learn about AWS Cloud concepts, services, security, architecture and support. This course also helps prepare for the AWS Certified Cloud Practitioner exam. Providers: Microsoft Azure, AWS, and GCP.
Key Features
✅ Official AWS live class training content
✅ Self-paced learning videos authored by AWS
✅ Live online training from AWS Authorized Instructors
✅ 1-day Instructor-Led Training Course for accelerated learning
Skills Covered
✅ AWS Cloud Adoption Framework
✅ AWS Global Infrastructure
✅ AWS data migration solutions
✅ Storage and databases
✅ AWS IAM security levels
✅ AWS Compute Services
✅ Amazon Cloud
✅ Front and Edge locations
✅ Networking concepts
✅ Pay_As_You_Go pricing model
✅ AWS pricing models and support
Learning Path
✅ Lesson 01: Introduction to Amazon Web Services
✅ Lesson 02: Compute in the Cloud
✅ Lesson 03: Global Infrastructure and Reliability
✅ Lesson 04: Networking
✅ Lesson 05: Storage and Databases
✅ Lesson 06: Security
✅ Lesson 07: Monitoring and Analytics
✅ Lesson 08: Pricing and Support
✅ Lesson 09: Migration and Innovation
✅ Lesson 10: AWS Certified Cloud Practitioner Basics
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Correction (10:26). The probabilities are wrong. The correct ones are here:
For Die 1: 0.4^4 * 0.2^2 * 0.1^1 * 0.1^1 * 0.2^2
For Die 2: 0.4^4 * 0.1^2 * 0.2^1 * 0.2^1 * 0.1^2
For Die 3: 0.1^4 * 0.2^2 * 0.4^1 * 0.2^1 * 0.1^2
Kullback Leibler (KL) divergence is a way to measure how far apart two distributions are.
In this video, we learn KL-divergence in a simple way, using a probability game with dice.
Shannon entropy and information gain: https://www.youtube.com/watch?v=9r7FIXEAGvs&t=1066s&pp=ygUic2hhbm5vbiBlbnRyb3B5IGluZm9ybWF0aW9uIHRoZW9yeQ%3D%3D
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The Gini Impurity Index is a measure of the diversity in a dataset. In this short video you'll learn a very simple way to calculate it using probabilities.
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This is the ultimate, no-code guide to building and deploying your first AI agent in under 30 minutes using N8N!
In this step-by-step tutorial, you'll learn how to connect the world's best AI models with a powerful no-code automation platform (N8N) to create an agent that works for you 24/7.
What you will build:
- A completely automated AI Agent that can consume a long piece of content, like a YouTube video (or article/document), and instantly process it.
- We'll specifically create an agent that summarizes a video and generates polished infographics from the summary, all automatically!
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- The no-code stack for building reliable AI agents.
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No coding is required. If you want to get ahead in the AI revolution, this is an in-depth guide that can help you.
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🤖 Confused about AI agents and agentic AI? This video clears it up! AI agents are specific applications solving multi-step problems independently, while agentic AI is the entire research field making these agents possible. Think of AI agents as specific medicines and agentic AI as pharmaceutical science. Today's AI agents aren't AGI yet—they're specialized tools for specific purposes. Understanding these developments is essential as increasingly sophisticated agents emerge to automate various tasks. 🔍💡
#AIAgents #AgenticAI #ArtificialIntelligence #FutureTech #BusinessTechnology #AGI #TechTrends
This Claude Code Tutorial teaches you what I wish I knew as a software developer about Claude Code before I started AI coding. Get started here: https://clau.de/kevinstratvert
You can vibe code with other tools, or you can build durable software with tools like Claude Code. First, I'll walk you through how to install it on Mac or Windows.
Next, you’ll connect Claude Code to VS Code and learn how to build your first app - including how best to structure your prompts and what details are useful for Claude to know.
You'll review Claude's Plan mode like a senior engineer and learn how to work faster once you trust the changes it makes.
Next, you'll learn how to use Claude Code with an existing codebase - focusing on how to get it to analyze your coding standards so future changes are consistent. (Heavy use of CLAUDE.md)
Finally, you’ll execute a major architecture change and learn how best to work with Claude Code throughout the process.
Host: David DeWinter
Sponsor: Anthropic
📚 RESOURCES
Commands and Prompts to Copy ➜ https://drive.google.com/drive..../folders/1ZFRZcOCfep
CLAUDE.md guidance ➜ http://humanlayer.dev/blog/wri....ting-a-good-claude-m
Claude Code Best Practices by Anthropic ➜ https://www.anthropic.com/engi....neering/claude-code-
⌚ TIMESTAMPS
0:00 - Install Claude Code
2:08 - Create New App
7:56 - Existing App
11:48 - Architecture Change
14:31 - Your Next Steps
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MIT 8.04 Quantum Physics I, Spring 2013
View the complete course: http://ocw.mit.edu/8-04S13
Instructor: Allan Adams
In this lecture, Prof. Adams gives a panoramic view on various experimental evidence that indicates the inadequacy of pre-quantum physics. He concludes the lecture with a short discussion on Bell's inequality.
License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu
MIT 22.01 Introduction to Nuclear Engineering and Ionizing Radiation, Fall 2016
Instructor: Michael Short
View the complete course: https://ocw.mit.edu/22-01F16
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6
Prof. Short uses all the concepts introduced thus far to introduce the study of nuclear materials and radiation damage - his field of study. The concept of ionizing radiation creating nuclear displacements, not just electron ionization, is introduced as the first event in radiation damage. The structural defects produced from these displacements are shown to cluster, move, and evolve, resulting in drastic changes to material properties. Key structural material properties and their formal definitions are introduced and demystified by watching a pair of Finnish scientists smash various items with a 50 ton hydraulic press.
License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu