Sliding window object detection is a technique that allows you to detect objects in a picture. This technique is not very efficient as it is very compute intensive. Recently new techniques has been discovered that tried to improve performance such as R CNN, Fast R CNN, Faster R CNN etc. YOLO (You only look once) is a state of the art most modern technique that outperforms all other previous techniques such as sliding window object detection, R CNN, Fast and Faster R CNN etc. We will cover YOLO in future videos.

Deep learning playlist: https://www.youtube.com/playli....st?list=PLeo1K3hjS3u
Machine learning playlist : https://www.youtube.com/playli....st?list=PLeo1K3hjS3u

#objectdetection #deeplearningobjectdetection #slidingwindowobjectdetection #deeplearningtutorial

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❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

This video explains the original GPT model, "Improving Language Understanding by Generative Pre-Training". I think the key takeaways are understanding that they use a new unlabeled text dataset that requires the pre-training language modeling to incorporate longer range context, the way that they format input representations for supervised fine-tuning, and the different NLP tasks this is evaluated on!

Paper Links:
GPT: https://s3-us-west-2.amazonaws.....com/openai-assets/r
DeepMind "A new model and dataset for long range memory": https://deepmind.com/blog/arti....cle/A_new_model_and_
SQuAD: https://rajpurkar.github.io/SQuAD-explorer/explore/v2.0/dev/Oxygen.html?model=BiDAF%20+%20Self%20Attention%20+%20ELMo%20(single%20model)%20(Allen%20Institute%20for%20Artificial%20Intelligence%20[modified%20by%20Stanford])&version=v2.0
MultiNLI: https://www.nyu.edu/projects/bowman/multinli/
RACE: https://arxiv.org/pdf/1704.04683.pdf
Quora Question Pairs: https://www.quora.com/q/quorad....ata/First-Quora-Data
CoLA: https://arxiv.org/pdf/1805.12471.pdf

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🔥Edureka DevOps Training: https://www.edureka.co/devops-....certification-traini
This Edureka "Docker Compose Tutorial" will take you through the fundamentals of Docker Compose and its role in multi-container applications. You will learn what Docker and Docker compose is, the benefits of Docker compose, microservices, and how to write a compose file, basic commands of docker-compose, and finally, a demo on docker-compose where you set up and run a Django-based application using Docker-Compose.
The following are the topics covered in the tutorial:
00:00 Agenda
01:25 What is Docker?
05:35 Why Docker-Compose
10:45 What is Docker-Compose?
15:10 Docker-Compose Installation
19:45 Docker-Compose Hands-on
37:15 Summary

Code Files: https://drive.google.com/drive..../folders/1QcGbSpt21W

🔹Check our complete DevOps playlist here: http://goo.gl/O2vo13
🔹Check our Blog playlist here: https://bit.ly/3gfNuZr
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How it Works?
1. This is a 4 Week Instructor led Online Course.
2. Course consists of 24 hours of online classes, 25 hours of assignment, 20 hours of project
3. 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.
4. You will get Lifetime Access to the recordings in the LMS.
5. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!

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

About the Course
Edureka’s DevOps online training is designed to help you master key tools of Devops lifecycle like Docker, Puppet, Jenkins, Nagios, GIT, Ansible, SaltStack and Chef used by a DevOps Engineer for automating multiple steps in SDLC. During this course, our expert DevOps instructors will help you:

1. Understand the concepts and necessities of DevOps
2. Understand the need for DevOps and the day-to-day real-life problems it resolves
3. Learn installation and configuration of common infrastructure servers like Apache, and Nginx for the Enterprise
4. Learn popular DevOps tools like Jenkins, Puppet, Chef, Ansible, SaltStack, Nagios and GIT
5. Implement automated system update, installations and deployments
6. Learn Virtualization Concepts
7. Configuration deployment and packaging, continuous integration using GIT
8. Fine tune Performance and set-up basic Security for Infrastructure
9. Manage server operations using Code which is popularly known as Infrastructure as a Code
10. Understand the need for and concepts of Monitoring and Logging.

Along with the above mentioned topics, to help you master the most popular DevOps tools, you will also receive 3 additional self-paced courses including presentations, class recordings, assignments, solutions for the following tools:

1: Ansible - Covers Introduction, Setup & Configuration, Ansible Playbooks, 37 Ansible Modules, Different Roles and Command Line usage. 2: Chef - Covers Introduction, Building the Cook Book, Node Object & Search, Data-bags, Chef environment, Roles, Deploying Nodes in Production and using the Open Source Chef Server.

3: Puppet - Covers Puppet Infrastructure & run-cycle, the Puppet Language, Environment defining Nodes and Modules, Provisioning a Web Server and Executing Modules Against A Puppet Master.

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

Who should go for this course?
DevOps practitioners are among the highest paid IT professionals today, and the market demand for them is growing rapidly. With emergence of new job roles around DevOps philosophy, anyone aspiring to get into these new roles, can take up this DevOps course. Some of these roles are:

1. DevOps Architect
2. Automation Engineer
3. Software Tester
4. Security Engineer
5. Integration Specialist
6. Release Manager

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Project Work
1. Host a dummy webpage using Apache Web Server.
2. Write shell script which reports:
a) Various system configurations related to the user and the OS.
b) Data related to load on the server.
c) Top 5 processes with maximum number of threads.
d) Sort the services by memory
3. Install Nagios on a VM node for monitoring the various parameter of the VM.

For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free).

Ms. Coffee Bean explains how a huge collaboration of researchers managed to extract training data from large language models like GPT-2. Why is this even possible and what does this mean for even larger models like GPT-3?
Discussed paper:
" Extracting Training Data from Large Language Models" explained by Carlini et al. 2020.

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🔥 Optionally, pay us a coffee to boost our Coffee Bean production! ☕
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📺 GPT-3 – what you need to know: https://youtu.be/5fqxPOaaqi0

Outline:
* 00:00 Large Language Models
* 01:55 GPT-2
* 02:33 Why is it possible?
* 03:38 k-eidetic memorization
* 04:21 How does the attack work?
* 05:49 How bad is it?
* 08:12 What to do?

📄 Paper explained: Carlini, N., Tramer, F., Wallace, E., Jagielski, M., Herbert-Voss, A., Lee, K., ... & Oprea, A. (2020). Extracting Training Data from Large Language Models. arXiv preprint arXiv:2012.07805. https://arxiv.org/pdf/2012.07805.pdf

-------------------------------------------------------------
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#AICoffeeBreak #MsCoffeeBean #GPT #MachineLearning #AI #research

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In this video on Project Management Full Course, we shall begin learning the basics of project management. As we move forward, we shall verse ourselves with different project management concepts like project planning, project time, cost quality, and communication management. We will learn about project manager roles and different project management tools. Finally, in this project management tutorial for beginners, we shall see some Project Management interview questions to excel in any Project Management interview.
By the end of this course, you'll have everything you need to know about Project Management. So without further ado, let's jump in!
00:00 Project management full course - Introduction
02:05 What is project management?
12:28 Project lifecycle
34:41 Job roles and responsibility
39:30 Project management certifications
53:00 What is PMP?
01:05:00 Project management detailed guide
05:03:00 Trello Tutorial
06:25:33 Project manager interview questions and answers

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Post Graduate Program in Project Management
Become a digital-age project leader with our Post Graduate Program in Project Management in partnership with the University of Massachusetts Amherst. Aligned with the Project Management Professional (PMP) certification, learn the frameworks, tools, and skills to drive transformational projects. The Post Graduate Program in Project Management focuses on managing quality, risk and complexity, delivering results, understanding strategy, and implementing best practices. This program aligns with the Project Management Institute standards and provides an opportunity to earn 146 PDUs required for the renewal of multiple project management certifications.

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✅Earn the 35 Contact hours and 7 simulation exams to ace the PMP exam

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In this video on What Is Pi Network, we embark on a journey through the world of Pi Network. Discover what sets Pi apart from other cryptocurrencies as we unravel its unique features and functionalities. Gain a deeper understanding of how Pi works, including its innovative mining approach and decentralized nature. We'll also delve into the current price of Pi and explore its potential trajectory in the ever-evolving crypto market. Join us as we peer into the future of Pi coin and discuss the possibilities it holds for reshaping the landscape of digital currency. Get ready to dive into the exciting realm of Pi Network!

00:00 Introduction
02:10 What is Pi network ?
03:30 What makes Pi different from others ?
04:44 How Pi works ?
06:14 Pi network price
06:59 What is the future of Pi coin ?

✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

#pi #pinetwork #blockchain #2024 #simplilearn

➡️About Professional Certificate Program In Blockchain
The blockchain certification program helps the learners start from the fundamentals and then cover all the technical and functional aspects needed to build any blockchain solution using the best tools and techniques in the industry. In this program, they will build smart contracts, and bitcoin wallets, create transactions, fabricode, and more.

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This Machine Learning vs Deep Learning vs Artificial Intelligence video will help you understand the differences between ML, DL, and AI, and how they are related to each other. The tutorial video will also cover what Machine Learning, Deep Learning, and Artificial Intelligence entail, how they work with the help of examples, and whether they really are all that different.

This Machine Learning Vs Deep Learning Vs Artificial Intelligence video will explain the topics listed below:
Start (0:00)
1. Artificial Intelligence example ( 00:29 )
2. Machine Learning example ( 01:29 )
3. Deep Learning example ( 01:44 )
4. Human vs Artificial Intelligence ( 03:34 )
5. How Machine Learning works ( 06:11 )
6. How Deep Learning works ( 07:09 )
7. AI vs Machine Learning vs Deep Learning ( 12:33 )
8. AI with Machine Learning and Deep Learning ( 13:05 )
9. Real-life examples ( 15:29 )
10. Types of Artificial Intelligence ( 17:50 )
11. Types of Machine Learning ( 20:32 )
12. Comparing Machine Learning and Deep Learning ( 22:46 )
13. A glimpse into the future ( 25:46 )

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📚ML vs DL vs AI Article: https://bit.ly/3fh6HIP

Machine Learning Articles: https://www.simplilearn.com/what-is-artificial-intelligence-and-why-ai-certification-article?utm_campaign=What-is-Machine-Learning-7JhjINPwfYQ&utm_medium=Tutorials&utm_source=youtube


You can also go through the Slides here: https://goo.gl/cdQ7uy

#SimplilearnMachineLearning #SimplilearnAI #SimplilearnDeepLearning #Artificialintelligence #MachineLearningTutorial

➡️ 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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- Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more
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👉 Learn More At:




👉 Learn More At:

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These harmonies never fail to give us the chills. Welcome to MsMojo, and today we’re counting down our picks for the most epic, emotionally fulfilling instances of harmony in music. Our countdown includes “California Dreamin,’” “The Sound of Silence,” “Be My Baby,” and more! Which song gives YOU the chills? Let us know in the comments!

Watch more great music videos here:
Top 10 Hauntingly Beautiful Songs in Animated Movies - https://youtu.be/xSvg7H6UQtM
Top 10 Darkest & Creepiest Songs in Musicals - https://youtu.be/xkuPqUeA0Ms
Top 20 Greatest Music Videos of All Time - https://youtu.be/5Otvn1mBrcQ

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MsMojo is a leading producer of reference online video content of Top 10 Lists, Origins, Biographies, Commentary and more on Pop Culture, Celebrity, Movies, Music, TV, Film, Video Games, Politics, News, Comics, Superheroes. Your trusted authority on ranking Pop Culture.

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🔥PGP in Generative AI and ML in collaboration with Illinois Tech: https://www.edureka.co/executi....ve-programs/pgp-gene
🔥Generative AI Course: Masters Program: https://www.edureka.co/masters....-program/generative- (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎")

This *Artificial Intelligence Full Course* covers everything about AI, from basics like machine learning and neural networks to advanced topics in computer vision and natural language processing. It's designed for all levels, packed with explanations, coding demos, and real-world insights to make AI understandable and exciting for beginners and experienced enthusiasts alike.

00:00:00:00 Introduction
00:01:48:07 What is Artificial Intelligence?
00:08:29:09 Types Of Artificial Intelligence
00:18:43:02 AI vs Machine Learning vs Deep Learning
00:32:27:07 What is Deep Learning
00:43:39:18 What is LLM (Large Language Model)
01:00:09:22 What is Generative AI?
01:15:28:11 What is AI Ethics
01:24:04:29 What is Responsible AI
01:32:18:20 Artificial Intelligence with Python
03:11:14:03 Artificial Neural Network
03:43:02:21 Recurrent Neural Networks
04:11:54:12 Convolutional Neural Network
04:32:29:08 Introduction to TensorFlow
04:56:06:27 Prompt Engineering
05:15:31:10 Prompt Engineering For Code Generation
05:24:49:25 Building a Chatbot with Prompt Engineering
05:40:53:15 OpenAI o3-mini Model
05:48:04:16 What is Agentic AI?
05:59:09:11 Introduction to Midjourney
06:17:41:11 How to use Midjourney?
06:25:24:24 GitHub Copilot
06:42:43:18 What is Vibe Coding?
06:51:53:18 Top 5 AI Frameworks
07:06:38:25 How AI is Transforming Studio Ghibli-Style Animation?
07:12:05:17 AI in Web Development
07:37:16:23 AI in Healthcare
07:45:59:00 AI in Retail
07:52:07:10 AI in Automotive
08:02:02:10 AI for Marketing
08:14:38:04 AI for Business
08:20:06:03 AI in Finance
08:28:41:23 AI for HR
08:35:03:06 AI in Manufacturing
08:41:30:17 AI in Cybersecurity
08:51:19:09 AI for Startup
08:59:52:18 AI for Testing
09:05:18:12 AI for Ethical Hacking
09:10:12:11 AI on Microsoft Azure
09:22:37:15 AI and Industry 4.0
09:27:38:22 AI Engineer Learning Path
09:34:50:17 Top 15 AI Skills You Need to Know
09:43:10:28 Build AI Applicant Tracking System (ATS)
09:58:44:24 Artificial Intelligence Interview Questions & Answers

🔴 𝐋𝐞𝐚𝐫𝐧 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐅𝐨𝐫 𝐅𝐫𝐞𝐞! 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐘𝐨𝐮𝐓𝐮𝐛𝐞 𝐂𝐡𝐚𝐧𝐧𝐞𝐥: https://edrk.in/DKQQ4Py

📢📢Check out the latest 2025 video on Top 10 Technologies for the most up-to-date insights!
📌 Top 10 Technologies to Learn in 2025 → https://youtu.be/5kjWh8lBxC4

📝Feel free to share your comments below.📝

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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Dr. Raj Dandekar (MIT PhD) conducted a 7-hour small language model workshop. This is part 1 of that workshop.

In this, we cover the following four aspects:

1. 00:00 Introduction to SLM
2. 40:15 Dataset loading
3. 53:36 Tokenization
4. 01:24:42 Creating input-output pairs

If you want to get access to the detailed lecture notes, register here: https://vizuara.ai/courses/bui....ld-slm-from-scratch-

MIT 6.868J The Society of Mind, Fall 2011
View the complete course: http://ocw.mit.edu/6-868JF11
Instructor: Marvin Minsky

In this lecture, students discuss Chapter 1 of The Emotion Machine, covering topics such as love, infatuation, and the Self.

License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu

MIT 14.01 Principles of Microeconomics, Fall 2023
Instructor: Prof. Jonathan Gruber
View the complete course: https://ocw.mit.edu/14-01F23
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

In this lecture, Prof. Gruber talks about how consumers make decisions with budget constraints and constrained choice. How do consumers make decisions when they face a limit on their resources? Keywords: constrained choice, budget constraints, consumer preference, SNAP

License: Creative Commons BY-NC-SA
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For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai

October 21, 2025
This lecture covers deep reinforcement learning.

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

To follow along with the course schedule and syllabus, visit: https://cs230.stanford.edu/syllabus/

More lectures will be published regularly.
View the playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

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

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

eep learning networks are mechanical systems which “learn” by modeling high-level abstractions in datasets, and cycling through trial-and-error guesses with feedback, to establish an optimally-weighted system that can make accurate predictions about new data. LSTM RNNs (long short term memory Recurrent Neural Nets) is a deep learning method that overcomes some of the limitations in classical time series forecasting (non-linearity, fixed-time windows, time lag specification, and multivariate forecasting). Hence, deep learning is emerging as an important forecasting technique for coping with exponentially growing data, and the ability to expediently process and direct these data. In the future, deep learning smart networks might provide an advanced computational infrastructure for tackling real-time predictive data science problems such global health monitoring, energy storage and transmission, and financial risk assessment. Slides: https://www.slideshare.net/lab....logga/deep-learning-