🔵 Intellipaat Linux Course: https://intellipaat.com/linux-training/
In this Linux Administration Tutorial video, you will learn what is Linux, how to install Linux, how to setup kernel parameters, how to install & remove software, RPM in Linux, various commands in Linux, and various Linux services & systems in detail.

#LinuxAdministrationTutorial #LinuxTutorial #LinuxCourse #Linux #LinuxAdministration #LinuxForBeginners #Intellipaat #LinuxCommands #Intellipaat

The following topics are covered in this video:
00:00:00 - Linux Administration Tutorial
00:38:00 - Introduction to Linux
00:11:42 - Basics of Shell
00:17:47 - Top Shells in Linux
00:21:49 - Basics of Kernal
00:28:01- How to Install Linux?
00:29:39 - Quiz
00:59:54 - Quiz
01:17:22 - Basic Linux Commands
01:32:54 - Linux UI vs Terminal
01:37:14 - How to login to remote Linux?
01:41:46 - How to run a command as admin in Linux?
01:45:05 - Good to know commands in Linux
01:53:42 - Displaying - using Echo
02:00:08 - Set and unset a Variable
02:11:51 - Using Expr
02:17:15 - Header File of Shell Script - using Shebang (#!)
02:20:49 - Text Editors and Creating a File
02:25:24 - Hands-on: Creating and saving a file in Vim
02:28:21 - Understanding Linux File Permissions
02:47:17 - Chmod and Chown
03:00:41 - Displaying content in a File
03:11:46 - Unix Process Control Commands
03:34:41 - Linux Shell Scripting Tutorial
04:28:12 - Shell Scripting: Loops and Iterations
05:16:09 - Unix vs Linux
05:22:57 - Linux Interview Questions

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🔵 Interested to learn Linux still more? Please check a similar Linux certification blog here: https://intellipaat.com/blog/linux-certification/

Are you looking for something more? Enroll in our Linux course and become a certified Linux Professional (https://intellipaat.com/linux-training/). It is a 16 hrs instructor-led Linux training provided by Intellipaat which is completely aligned with industry standards and certification bodies.

🔵 If you’ve enjoyed this Linux Tutorial, Like us and Subscribe to our channel for more similar Linux videos and free Splunk tutorials.
Got any questions about the Linux course or how to download Linux? Ask us in the comment section below.
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1. 24*7 Lifetime Access & Support
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3. Job Assistance
4. Mentors with +14 yrs
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6. Lifetime free Course Upgrade
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🔵 Why should you watch this Linux Tutorial?

Linux is a powerful open-source operating system that is being used by a large section of the corporate world. This OS ensures that you have the power to configure, manage and secure your systems. We are offering the top linux tutorial that has been created with extensive inputs from the industry experts so that you can learn linux easily.

🔵 Who should watch this Linux Tutorial video?

Since this Linux video with hands on can be taken by anybody, so if you are a software engineer and IT professionals, Linux developers and administrators, or a beginner in technology then you must watch these linux tutorials to take your skills to the next level.

🔵 Why should you opt for a Linux career?

If you want to fast-track your career then you should strongly consider Linux. The reason for this is that it is one of the fastest-growing technology. There is a huge demand for professionals in Linux. The salaries for Linux Professionals are fantastic. There is a huge growth opportunity in this domain as well. Hence this Intellipaat Linux tutorial is your stepping stone to a successful career!
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🔥PROMPT ENGINEERING WITH GENERATIVE AI: https://www.edureka.co/prompt-....engineering-generati
Explore the field of artificial intelligence through our Generative AI Tutorial. This video will break down the intricate workings of the generative AI model and give you useful information and pointers for utilizing generative AI in your projects, covering everything from the fundamentals of the technology to its applications, frameworks, and changing the landscape of industries. This course is a crucial place to start, whether you're a professional looking to implement AI-driven solutions or a newcomer excited to learn about AI's creative potential.

✅ 00:00 - Generative AI Tutorial
✅ 02:10 - Introduction to AI
✅ 02:48 - Working of AI
✅ 03:45 - What is Generative AI
✅ 05:00 - AI Prompt Writing
✅ 06:35 - Text-to-Text Generative AI
✅ 07:42 - Prompt Writing Rules
✅ 08:47 - ChatGPT-3.5
✅ 09:15 - ChatGPT-4
✅ 11:24 - Google Gemini
✅ 12:22 - Text-to-Image Generative AI
✅ 13:41 - DezGo
✅ 13:50- Hands-On Tutorial

✅ Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

🔵 DevOps Online Training: http://bit.ly/3VkBRUT
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🌕 RPA Online Training: http://bit.ly/3GFHKYB
🔵 Python Online Training: http://bit.ly/3Oubt8M
🌕 Azure Online Training: http://bit.ly/3i4P85F

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
🌕 Cloud Architect Masters Program: http://bit.ly/3OvueZy
🔵 Data Scientist Masters Program: http://bit.ly/3tUAOiT
🌕 Big Data Architect Masters Program: http://bit.ly/3tTWT0V
🔵 Machine Learning Engineer Masters Program: http://bit.ly/3AEq4c4
🌕 Business Intelligence Masters Program: http://bit.ly/3UZPqJz
🔵 Python Developer Masters Program: http://bit.ly/3EV6kDv

🔴 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

📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
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📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

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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.
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What kinds of jobs can you get with Prompt Engineering skills?‎

Here are some potential job roles:

Machine Learning Engineer
Data Scientist
Natural Language Processing (NLP) Engineer
AI Research Scientist
Software Engineer (AI/ML)
Data Engineer
Content Generation Specialist
Conversational AI Developer
AI Product Manager
AI Ethicist

Remember that the job market and the demand for specific skills can change over time, so staying updated on industry trends and job postings is essential.

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Who are the instructors for Prompt Engineering Course?

All the instructors at edureka are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by edureka for providing an awesome learning experience to the participants.

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

Learn in-demand Machine Learning skills now → https://ibm.biz/BdK65D
Learn about watsonx → https://ibm.biz/BdvxRj

Large language models-- or LLMs --are a type of generative pretrained transformer (GPT) that can create human-like text and code. There's a lot of talk about GPTs and LLMs lately, but they've actually been around for years! In this video, Martin Keen briefly explains what a LLM is, how they relate to foundation models, and then covers how they work and how they can be used to address various business problems.

AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdK65X

#llm #gpt #gpt3 #largelanguagemodel #watsonx #GenerativeAI #Foundationmodels

🔥Purdue - Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=W7Yrx_IdIiY&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=W7Yrx_IdIiY&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Advanced Executive Program In Applied Generative AI - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=W7Yrx_IdIiY&utm_medium=DescriptionFirstFold&utm_source=Youtube

This Gen AI Full Course video by simplilearn helps us learn everything about Generative AI. The Introduction to Gen AI Full Course covers key topics such as What is AI and How it Works, the Evolution of AI, and a Roadmap to Become a Gen AI Engineer, along with advanced subjects like Generative Adversarial Tutorial, Transformers in AI, Langchain, ML Projects for Resume, and Top 10 AI Technologies, including deep dives into OpenAI ChatGPT-01 Model, LLM Benchmarking, and AI Career Opportunities.

Following are the topics covered in the Gen AI Full Course:

00:00:00 Introduction to Gen AI Full Course
00:08:08 Introduction to What is AI and How it works
00:08:53 What is Gen AI
00:19:32 Roadmap to become a Gen AI Engineer
00:35:11 AI Trends for future
00:36:31 Evolution of AI
01:00:50 Open ai chatgpt o1 model
01:02:40 AI Carrer opportunities
01:10:03 Top 10 AI Technologies
01:25:03 Deep Learning
01:33:20 Search GPT
01:35:35 Langchain
01:48:06 ML Projects for resume
02:50:29 Generative Adversarial Tutorial
02:59:51 What are Gans
03:00:52 Transformers in AI
03:13:21 LSTM
03:14:36 Gen Ai vs AI
03:23:39 Introduction to LLM
04:24:52 What is ML
05:21:24 ML Tutorial for beginners
07:26:47 Reinforcement Learning
08:56:26 Recurrent Neural Network
09:16:17 CHatgpt analyse
09:25:10 LLM Benchmarkeing
10:15:53 Hugging Face and its tutorial

✅ What is Gen AI?
Generative artificial intelligence, also known as generative AI or gen AI for short, is a type of artificial intelligence (AI) that can create new content and ideas, including conversations, stories, images, videos, and music. It can learn human language, programming languages, art, chemistry, biology, or any complex subject matter. It reuses what it knows to solve new problems.

✅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_

#generativeai #genai #ai #machinelearning #llm #simplilearn #2024

➡️ About Professional Certificate Program in Generative AI and Machine Learning

The Generative AI and Machine Learning course enriches your career journey with comprehensive coverage of machine learning, deep learning, NLP, generative AI, reinforcement learning, computer vision, and more. Combining theory with hands-on practice, it offers live virtual sessions, projects with integrated labs, and masterclasses by IIT Guwahati faculty.

Key Features

✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
✅ 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
✅ Simplilearns JobAssist helps you get noticed by top hiring companies

Learning Path
✅ IITG AI: Program Induction
✅ IITG AI: Programming Fundamentals
✅ IITG AI: Python for Data Science (IBM)
✅ IITG AI: Applied Data Science with Python
✅ IITG AI: Machine Learning
✅ IITG AI: Deep Learning with TensorFlow (IBM)
✅ IITG AI: Deep Learning Specialization
✅ IITG AI: Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ IITG AI: Advanced Generative AI

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

👉 Enroll Now: https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=W7Yrx_IdIiY&utm_medium=Description&utm_source=Youtube

MIT 15.773 Hands-On Deep Learning Spring 2024
Instructor: Rama Ramakrishnan
View the complete course: https://ocw.mit.edu/courses/15....-773-hands-on-deep-l
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

Introduction and overview of the course covering the history and background of the field.

License: Creative Commons BY-NC-SAMore information at https://ocw.mit.edu/termsMore courses at https://ocw.mit.eduSupport 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.

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education

October 17, 2025
This lecture covers:
• Pretraining
• Quantization
• Hardware optimization
• Supervised finetuning (SFT)
• Parameter-efficient finetuning (LoRA)

To follow along with the course schedule and syllabus, visit: https://cme295.stanford.edu/syllabus/

Chapters:
00:00:00 Introduction
00:07:19 Pretraining
00:13:26 FLOPs, FLOPS
00:16:34 Scaling laws, Chinchilla law
00:24:49 Training optimizations overview
00:31:09 Data parallelism with ZeRO
00:35:51 Model parallelism
00:38:26 Flash Attention
00:52:37 Quantization
00:56:00 Mixed precision training
01:02:31 Supervised finetuning
01:09:21 Instruction tuning
01:37:53 Parameter-efficient finetuning with LoRA
01:45:16 QLoRA

Afshine Amidi is an Adjunct Lecturer at Stanford University.

Shervine Amidi is an Adjunct Lecturer at Stanford University.

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

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education

November 21, 2025
This lecture covers:
• LLM-as-a-judge overview
• Best practices and benefits
• Biases and pitfalls

To follow along with the course schedule and syllabus, visit: https://cme295.stanford.edu/syllabus/

Chapters:
00:00:00 Introduction
00:07:08 Inter-rater agreement metrics
00:18:24 Rule-based metrics
00:21:00 METEOR, BLEU ROUGE
00:28:00 LLM-as-a-judge
00:33:44 Structured outputs
00:36:48 Variants
00:38:47 Position, verbosity, self-enhancement bias
00:47:22 Best practices
00:54:06 Factuality
01:00:15 Agent evaluation
01:23:50 Benchmarks
01:25:12 Knowledge with MMLU
01:29:34 Reasoning AIME, PIQA
01:33:57 Coding with SWE-bench
01:36:15 Safety with HarmBench
01:40:51 Agents with Tau-Bench

Afshine Amidi is an Adjunct Lecturer at Stanford University.

Shervine Amidi is an Adjunct Lecturer at Stanford University.

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

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

Covers some of the more advanced concepts behind convolutional neural networks. In particular, the topics are

- Inception architectures
- Transfer learning

Here are the links to the related, previous videos:
- Intro to CNNs Part 1 https://www.youtube.com/watch?v=7ftuaShIzhc
- Intro to CNNs Part 2 (1/2) https://www.youtube.com/watch?v=mZmyp0JjH6s

🔥 Python Programming Certification Course: https://www.edureka.co/python-....programming-certific
Python Interview Questions and Answers - https://www.edureka.co/blog/in....terview-questions/py
Explore the vast world of Python programming through our comprehensive video, "Python Interview Questions". In this video, we will explore 50 important Python interview questions to prepare for cracking Python interviews. These questions are suitable for everyone, whether you're just starting out or already know a lot. We explain each answer in detail, helping both beginners and experienced programmers feel more confident for their Python interviews. If you want to brush up on what you know or learn something new, this video will help you understand Python better.

✅ 00:00 - Introduction to Python Interview Questions
✅ 01:20 - Beginners Level Python Interview Questions
✅ 14:05 - Intermediate Level Python Interview Questions
✅ 26:45 - Advanced Level Python Interview Questions

✅ Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

#pythoninterview #pythoninterviewquestions #interviewquestions #interviewpreparation #python #edureka

📝Feel free to share your comments below.📝

𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

🔵 DevOps Online Training: http://bit.ly/3VkBRUT
🌕 AWS Online Training: http://bit.ly/3ADYwDY
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🔵 Machine Learning Engineer Masters Program: http://bit.ly/3AEq4c4
🌕 Business Intelligence Masters Program: http://bit.ly/3UZPqJz
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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

🔵 Advanced Certificate Program in Cloud Computing with E&ICT Academy, IIT Guwahati: https://bit.ly/43vmME8

📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain
📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_learning/
📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
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📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

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What is Python?

Python is a widely used programming language that can be used for small and large-scale projects. Python allows you to seamlessly integrate web development with data analysis. Python's wide adoption is due in part to its standard library, accessibility, and support for multiple paradigms, such as procedural, functional and object-oriented programming styles. Python modules can interact with many databases making it an excellent choice to learn data science and machine-learning.
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What skills or experience do I need to already have before starting to learn Python?

Python is beginner-friendly, and no prior programming experience is required. Basic computer literacy and problem-solving skills are beneficial but not mandatory.

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Is this Online Python Course for IT professionals?

No, It is not necessary to be an IT professional to be enrolled in this course. If you have programming knowledge, that will be an additional advantage. Many Non IT professionals completed the Python Course by enrolling at Edureka and placed in top MNCs such as Google, TCS, Maxgen Technologies, etc.

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

In this video we learn about a very important object detection metric in Mean Average Precision (mAP) that is used to evaluate object detection models. In the first part of the video we try to understand how this method works and then move on to PyTorch to implement this from scratch.

GitHub Repository:
https://github.com/aladdinpers....son/Machine-Learning

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Object Detection Playlist:
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PyTorch Playlist:
https://www.youtube.com/playli....st?list=PLhhyoLH6Ijf

0:00 - Introduction
0:09 - Explanation of mAP
8:19 - Implementation in PyTorch

All rights owned by Universal Pictures

Bayesian Deep Learning and a Probabilistic Perspective of Model Construction
ICML 2020 Tutorial

Bayesian inference is especially compelling for deep neural networks. The key distinguishing property of a Bayesian approach is marginalization instead of optimization. Neural networks are typically underspecified by the data, and can represent many different but high performing models corresponding to different settings of parameters, which is exactly when marginalization will make the biggest difference for accuracy and calibration.

The tutorial has four parts:

Part 1: Introduction to Bayesian modelling and overview (Foundations, overview, Bayesian model averaging in deep learning, epistemic uncertainty, examples)

Part 2: The function-space view (Gaussian processes, infinite neural networks, training a neural network is kernel learning, Bayesian non-parametric deep learning)

Part 3: Practical methods for Bayesian deep learning (Loss landscapes, functional diversity in mode connectivity, SWAG, epistemic uncertainty, calibration, subspace inference, K-FAC Laplace, MC Dropout, stochastic MCMC, Bayes by Backprop, deep ensembles)

Part 4: Bayesian model construction and generalization (Deep ensembles, MultiSWAG, tempering, prior-specification, posterior contraction, re-thinking generalization, double descent, width-depth trade-offs, more!)

Slides: https://cims.nyu.edu/~andrewgw/bayesdlicml2020.pdf
Associated Paper: "Bayesian Deep Learning and a Probabilistic Perspective of Generalization" (NeurIPS 2020)
https://arxiv.org/pdf/2002.08791.pdf


Thanks to Kevin Xia (Columbia) for help in preparing the video.

This video on Project Management Professional covers all the concepts from basics to advanced. Also, it covers all the information about Project Management like what Project Management is ?, what is A Project ?, what are the Components of Project Management ?, What is A Project Life Cycle ?, and what are the Key Focus Areas in Project Management?

These are the facts we will be discussing in this video:
00:00 Introduction
01:34 What is Project Management?
02:38 What is A Project?
03:15 Components of Project Management
05:14 What is A Project Life Cycle?
09:10 Key Focus Areas in Project Management

🔥Explore Our Free Courses With Completion Certificate by SkillUp: https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=WhatIsPMP&utm_medium=Description&utm_source=youtube

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The PMP certification is the global gold standard for project management professionals. Keep abreast of the changes in the project management practices updated in the PMBOK guide - 6th edition and pass the PMP® exam on your first attempt with Simplilearn’s new PMP course. The course covers new trends, emerging practices, and tailoring considerations, and places a greater emphasis on strategic and business knowledge. It also includes a new section on the role of the project manager.

PMP Certification Course Overview
The course covers new trends, emerging practices, tailoring considerations, and core competencies required of a Project Management professional. Placing a greater emphasis on strategic and business knowledge, this course also includes a new section on the role of the project manager in both large and small companies.

PMP Course Key Features:
- 35 contact hours/PDUs
- 8 industry case studies, 20 industry-based scenarios
- 6 hands-on projects, 7 simulation test papers (200 questions each)

Eligibility:
The PMP® certification is an essential professional requirement for senior project manager roles across all industries. The course is best suited for: Project Managers, Associate/Assistant Project Managers, Team Leads/Team Managers, Project Executives/Project Engineers, Software Developers, and Any professional aspiring to be a Project Manager.

Pre-requisites:
You should have a secondary degree (i.e. high school diploma, associate’s degree, or the global equivalent) with 7,500 hours of leading and directing projects along with 35 hours of project management education. OR You should have a four-year degree with 4,500 hours of leading and directing projects along with 35 hours of project management education.

Learn more at: https://www.simplilearn.com/post-graduate-diploma-management?utm_campaign=WhatIsPMP&utm_medium=Description&utm_source=youtube

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Learn how to use Pandas and Python for Data Analysis, to Data Cleaning and Data Wrangling. You will learn by creating real life projects interactively to help you take the next step in your Data Science Career.

Learn more about the projects at https://www.datawars.io/freecodecamp

⚠️ Important! We encourage you to try to resolve the projects by yourself first! And watch the solution afterwards ⚠️

💻 Course created by Santiago Basulto from DataWars.
🔗 Find more interactive Data Science projects solve at: https://www.datawars.io

⭐️ Projects Covered ⭐️
⌨️ (0:00:00) Introduction

⌨️ (0:02:22) DataFrames practice: working with English Words [🟢 Easy]
This project focuses on the basics of pandas DataFrames, including understanding its structures and modifying them. The data we're using is a big dictionary of english words.
🔗 Solve the project by yourself: https://www.datawars.io/fcc-english-words

⌨️ (0:33:26) Filtering and sorting with Pokemon data [🟢 Easy]
This project focuses on the main tasks of Data Analysis: filtering and sorting and question/answering. The dataset includes information of pokemons from all generations (to make it more fun!)
🔗 Solve the project by yourself: https://www.datawars.io/fcc-filtering-pokemon

⌨️ (1:24:30) The Birthday Paradox in the NBA [🟡 Intermediate]
The Birthday Paradox answers the question: how many people do you need in the same room in order to have a probability of at least 50% that two people share a birthday. The answer is astonishing! You'll use your findings to find which teams in the NBA share player's birthdays.
🔗 Solve the project by yourself: https://www.datawars.io/fcc-birthday-nba

⌨️ (1:55:28) Matching Strings by Similarity using Levenshtein distance [🟡 Intermediate]
One of the most challenging tasks of Data Cleaning is dealing with Strings. This project is all about string handling and advanced techniques, as using the Combinatorics and the Levenshtein distance to find irregularities in company names.
🔗 Solve the project by yourself: https://www.datawars.io/fcc-string-similarity

⌨️ (2:24:15) Data Cleaning with Google Playstore dataset [🟡 Intermediate]
An all-encompassing project that covers all the aspects of Data Cleaning, including: finding and fixing null values, duplicate values, outliers and more. The data was scraped from the Google Playstore which means that is full of irregularities. The project finishes with some Data Analysis tasks!
🔗 Solve the project by yourself: https://www.datawars.io/fcc-data-cleaning-playstore

⌨️ (3:18:34) Premier League Match Analysis [🔴 Advanced]
This project increases the complexity of your Data Analysis skills, as it combines Data Cleaning, with some analysis based on grouping operations. The dataset comes from the Premier League, the top-division Football/Soccer league in England.
🔗 Solve the project by yourself: https://www.datawars.io/fcc-premier-league

⌨️ (3:53:46) NBA 2017 season analysis: joining and groupby practice [🔴 Advanced]
This project puts your Data Wrangling skills to a test, by asking you to merge different dataframes, clean them, and finish doing some analysis and question/answering. The dataset contains the full information of 2017 NBA statistics.
🔗 Solve the project by yourself: https://www.datawars.io/fcc-nba-analysis


🎉 Thanks to our Champion and Sponsor supporters:
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NEWSLETTER ✉️ http://DylanCurious.com
PATREON 💰 https://patreon.com/DylanCurious (Monthly Video Call)

Hey there, it's me Dylan Curious! Today, we're delving deep into the realm of AGI or artificial general intelligence. Picture this: your childhood toy, favorite video game character, or cartoon figure not just following programmed instructions, but actually thinking and creating on its own. Sounds like science fiction, right? That's AGI for you!

AGI isn't just a toy robot dancing in pre-set patterns. Imagine it inventing its dance moves, composing its own songs, and then asking for your thoughts on its creativity. Mind-blowing, isn't it? A huge shoutout to Casey Armstrong for his informative blog post that inspired some of this content.

Now, let's hear from the experts. Elon Musk, back in 2016, anticipated we'd see AGI in 5 to 10 years. Fast forward to today, 2023, and we're right in the heart of that prediction. On the other hand, Dr. Alan D. Thompson has this fascinating countdown on lifearchitect.ai, forecasting AGI’s debut in June 2026. With such technological advancements, it makes one wonder if we're months away from AGI, rather than years.

Speaking of big names, Mark Zuckerberg envisions a brighter and more optimistic AGI future. He dreams of open source AI enhancing sectors like healthcare and education. David Shapiro, based on a Morgan Stanley report, sees AGI as a game-changer for tech giants, with possibilities of AGI being actualized within 18 months!

Demis Hassabis from DeepMind believes we're on the cusp of achieving AGI in just a few years. Sam Altman of OpenAI anticipates AGI within a 10 to 20-year frame. Dario Amodei, CEO of Anthropic, estimates 2-3 years, underscoring the rapid advancements in the field. And then there's the visionary Ray Kurzweil, predicting AI surpassing the Turing test by 2029.

So, where do I stand in this AGI timeline? I believe we might have already touched the fringes of AGI. Perhaps AGI, in its true essence, would be recognized only when it's embodied, mimicking human-like traits. Dive into this rollercoaster journey of AGI with me, and let's unravel the future together.

Make sure to like, share, and subscribe for more AI insights and don't forget to hit that bell icon for updates!

CURIOUS FUTURE: @dylan_curious
↪ https://www.youtube.com/channe....l/UCpdyFxSktWo3W6kMY

CURIOUS PODCAST: @dontsweatitpod
↪ https://www.youtube.com/channe....l/UChChPrDzfifYB9Si1

CURIOUS FRIENDS: @vegasfriends
↪ https://www.youtube.com/channe....l/UCJ2Q3smwCLmbEDDA3

00:00 - What if Your Toy Could THINK? Exploring AGI!
00:39 - 7 AI-Experts Predicting Short AGI Timelines
00:56 - Elon Musk: What His Silence Tells Us About AGI
01:43 - Dr. Alan D. Thompson: AGI Countdown Predicts 2026
03:21 - Mark Zuckerberg: When Will Strong AI Arrive?
04:15 - David Shapiro: Is AGI Really Coming in October 2024?
05:08 - Demis Hassabis: Human-Level AI in a Few Years
06:37 - Sam Altman: Optimistic About AGI’s Near Future?
07:34 - Dario Amodei (CEO of Anthropic): AGI in 2-3 Years?
08:28 - Ray Kurzsweil: AGI in 2-3 Years?
09:22 - Dylan Curious: GPT-4: The AI with Human-Level Intelligence?

SOURCES:
https://www.linkedin.com/pulse..../7-ai-experts-predic
https://twitter.com/CrowdsourcingKC
https://www.youtube.com/watch?v=PJwcds_tiQo&ab_channel=DrAlanD.Thompson
https://lifearchitect.ai/agi/
https://www.youtube.com/watch?v=YXQ6OKSvzfc&ab_channel=DavidShapiro~AI
@DaveShap
https://www.cnbc.com/2023/08/1....4/nvidia-shares-up-7
https://www.youtube.com/watch?v=Gfr50f6ZBvo&ab_channel=LexFridman
https://abcnews.go.com/Technol....ogy/openai-ceo-sam-a
https://www.youtube.com/watch?v=Nlkk3glap_U&ab_channel=DwarkeshPatel
@DwarkeshPatel
https://www.youtube.com/watch?v=4GQrLjvudJ4&ab_channel=AIforGood
@AIforGood

WATCH THE FULL VIDEO ⤵
https://www.youtube.com/watch?v=EzyNxcFUWgI

#AI #artificialintelligence #tech #tingtingin #AnastasiInTech #MattVidPro #mreflow #godago #AllAboutAI #BrieKirbyson #NicholasRenotte #aiexplained-official #OlivioSarikas #AdrianTwarog #aiadvantage #obscuriousmind #max-imize #DavidShapiroAutomator #DelightfulDesign #promptmuse #mattwolfe #agi #toyintelligence #videogameai #robotdance #openai #elonmusk #predictions #caseyarmstrong #crowdsourcingkc #drallandthompson #gpt4 #markzuckerberg #davidshapiro #nvidia #anthropic #demishassabis #deepmind #samaltman #darioamodei #raykurzweil #turingtest #chatgpt #futuretech #intelligencevsconsciousness #robotics #emergentai #multimodalai #llm #large languagemodels

🔥Edureka Tensorflow Training: https://www.edureka.co/ai-deep....-learning-with-tenso
This Edureka LSTM Explained video will help you in understanding why we need Recurrent Neural Networks (RNN) and what exactly it is. It also explains few issues with training a Recurrent Neural Network and how to overcome those challenges using LSTMs.
00:00 Introduction
00:36 Agenda
00:47 Introduction to NLP
01:46 Ways to Process Text Data
02:57 Recurrent Neural Networks
22:02 Long Short-term Memory
51:46 LSTM Use Cases
53:45 Real Time Applications of LSTM

🔹Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE
🔹Check our complete Deep Learning With TensorFlow Blog Series: http://bit.ly/2sqmP4s

🔴Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV

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#Edureka #DeepLearningEdureka #LSTMExplained #NeuralNetworks #DeepLearningTraining #DeepearningTutorial #EdurekaTraining

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.


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

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.

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

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.


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

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🔥Enroll for Intellipaat's Executive Certification Program in AI & ML: https://intellipaat.com/epgc-a....i-and-machine-learni

#MachineLearningCourse #MachineLearningFullCourse #MachineLearningTutorial #MachineLearningTutorialForBeginners #MLCourse #MachineLearningWithPython #MachineLearning #MachineLearningProjects #Intellipaat

Unlock the world of Machine Learning with this comprehensive Machine Learning Full Course 2025 by Intellipaat! This 11-hour complete machine learning course is your ultimate guide to mastering the basics and advanced concepts of machine learning. Designed for beginners and enthusiasts, this course covers key topics like machine learning algorithms, hands-on Python implementations, and real-world projects. Whether you’re starting your ML journey or brushing up your skills, this ML course has everything to accelerate your career in the tech industry.

💡 What you’ll learn in this course:
👨‍💻 Machine Learning fundamentals explained step-by-step.
👨‍💻 In-depth coverage of algorithms like regression, classification, clustering, and more.
👨‍💻 Python implementation of machine learning techniques.
👨‍💻 Insights into ML project development and deployment.
👨‍💻 Real-world examples to make concepts practical and applicable.

💻 Why choose this course?
Machine Learning is one of the most in-demand skills of the decade, and having a strong foundation in it can open doors to countless opportunities. This course not only helps you understand ML concepts but also equips you with hands-on experience to stand out in a competitive job market.

📖 Below are the concepts covered in this 'Machine Learning Full Course 2025':
00:00:00 - Introduction to Machine Learning Course
00:02:39 - What is Machine Learning?
00:53:55 - Types of ML: Supervised and Unsupervised Learning
01:11:11 - ML Examples and Myths
02:42:07 - Introduction to Reinforcement Learning
03:25:35 - Linear Regression: Introduction and Examples
03:52:00 - Linear Regression: Errors and Finding the Best Line (Hyperbole/Intercept)
04:14:08 - Linear Regression Hands-On: Single and Multiple Linear Regression
05:12:42 - R-Squared Explained
05:23:25 - Assumptions of Linear Regression
05:34:29 - Logistic Regression: Introduction
06:22:51 - Understanding Odds
06:28:36 - Probability vs. Odds
06:34:24 - Derivation of Sigmoid Function
07:19:03 - Balanced vs. Imbalanced Data
07:26:13 - Confusion Matrix
07:42:51 - Precision Explained
08:00:43 - Hands-On Logistic Regression
08:54:41 - Naive Bayes Explained
09:26:59 - Decision Tree Algorithm
09:55:51 - Understanding Entropy
10:29:14 - Types of Nodes in Decision Trees
10:36:00 - Underfitting vs. Overfitting

📌 Don’t miss out! Subscribe to Intellipaat for more career-transforming content.

Q1. Is this Machine Learning course suitable for beginners?
Yes, this course is perfect for beginners, with a strong focus on foundational concepts, step-by-step explanations, and practical applications.

Q2. What tools will I learn in this ML course?
You’ll primarily work with Python and its libraries like NumPy, Pandas, matplotlib, and scikit-learn, which are essential for machine learning projects.

Q3. How can I benefit from this Machine Learning course?
This course helps you develop skills in data analysis, algorithm implementation, and problem-solving, giving you a competitive edge in the tech industry.

➡️ About the Course
Gain expertise in Artificial intelligence and Machine Learning through an Executive Post Graduate Certification program in AI and ML offered by iHUB DivyaSampark, a Technology Innovation Hub of IIT Roorkee, in collaboration with Intellipaat This AI and ML program is in collaboration with tech giants Microsoft. Get classes and guidance directly from IIT Faculty and industry experts, with personalized 1:1 mentorship. Become IIT certified AI and ML expert with this online BootCamp.

➡️Who should take this course?
☑️ Individuals with a bachelor’s degree and a keen interest in learning AI and ML
☑️ IT professionals looking for a career transition as Machin learning experts or AI engineers.
☑️ Professionals aiming to move ahead in their IT career
☑️ Developers and Project Managers
☑️ Freshers who aspire to build their career in the field of Artificial Intelligence and Machine

✅ Key Features - (Course Features)
👉🏼 620 Hrs of Applied Learning
👉🏼 Learn from IIT Faculty & Industry Practitioners
👉🏼 50+ Industry Projects & Case Studies
👉🏼 One-on-One with Industry Mentors
👉🏼 Placement Assistance
👉🏼 Resume Preparation and LinkedIn Profile Review
👉🏼 24*7 Support
👉🏼 1:1 Mock Interview
👉🏼 Certification from Microsoft
👉🏼 Up to Rs. 50 Lakhs startup Incubation Support*

📌 Do subscribe to Intellipaat channel & come across more relevant Tech content: https://goo.gl/hhsGWb

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📚For more information, please write back to us at [email protected] or call us at IND: +91-7022374614 / US : 1-800-216-8930

Agents are everywhere these days, but with so much information available, it’s easy to feel overwhelmed. Most tutorials and videos focus on specific frameworks without covering the fundamental principles behind these systems.

This course takes a different approach. Over four modules, you'll learn to implement the four core agentic patterns from scratch, using just Python and Groq LLMs:

* Reflection Pattern
* Tool Use Pattern
* Planning Pattern
* Multi-Agent Pattern

Explore the written lessons on my Substack blog:

https://theneuralmaze.substack.com/

Check out the code here:

https://github.com/neural-maze/agentic_patterns

––––––––––––––––––––––––––––––

If you like this content, you can also follow me here:

📩 Substack - https://theneuralmaze.substack.com/
💼 LinkedIn - https://www.linkedin.com/in/migueloteropedrido/
💻 GitHub - https://github.com/MichaelisTrofficus
🐦 Twitter - https://x.com/moteropedrido

––––––––––––––––––––––––––––––

––––––––––––––––––––––––––––––

0:00 Introduction
2:48 Module 1 - Reflection Pattern
20:40 Module 2 - Tool Pattern
44:22 Module 3 - Planning Pattern
1:13:16 Module 4 - MultiAgent Pattern
1:41:00 Conclusion

––––––––––––––––––––––––––––––
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Creative Commons — Attribution 3.0 Unported — CC BY 3.0
Free Download / Stream: https://bit.ly/3wVnIXs
Music promoted by Audio Library https://bit.ly/3TDW3TT
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Carefree by Kevin MacLeod http://incompetech.com
Creative Commons — Attribution 4.0 International — CC BY 4.0
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Music ⓒ - Kevin MacLeod

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• Morocco — Amine Maxwell | Free Backgr...
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For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education

November 14, 2025
This lecture covers:
• Retrieval-augmented generation
• Advanced RAG techniques
• Function calling
• Agents
• ReAct framework

To follow along with the course schedule and syllabus, visit: https://cme295.stanford.edu/syllabus/

Chapters:
00:00:00 Introduction
00:06:38 RAG overview
00:27:39 Similarity search with SBERT and bi-encoders
00:34:25 Heuristic search with BM25
00:37:54 HyDE and contextual retrieval
00:41:00 Prompt caching
00:45:24 Re-ranking with cross-encoders
00:47:49 Retrieval evaluation with NDCG, MRR
00:59:28 Tool calling
01:26:22 Tool selection
01:29:17 Model Context Protocol (MCP)
01:31:56 Agents with ReAct
01:42:16 Safety and closing thoughts

Afshine Amidi is an Adjunct Lecturer at Stanford University.

Shervine Amidi is an Adjunct Lecturer at Stanford University.

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