Top Christmas Songs of All Time 🎅🏼 Best Christmas Music Playlist

🎄 Immerse yourself in the joyful and spirited atmosphere of Christmas as we present a carefully curated selection of the best Christmas songs from various eras.

"We Wish You A Merry Christmas" and other timeless classics come together to create a harmonious blend of holiday cheer. Whether you're preparing for a festive gathering, decorating your home, or simply enjoying the magic of Christmas, our playlist is designed to add the perfect musical touch to your celebrations.

🎅 Experience the magic of the season with melodies that have stood the test of time and continue to bring joy to hearts around the world. From traditional carols to contemporary hits, our compilation captures the essence of Christmas, making it a memorable and heartwarming experience for everyone.

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👉 Merry Christmas to all the music lovers. This playlist is perfect for setting the mood for the holiday season and includes all the Christmas songs you know and love. Enjoy!
May the magic of Christmas fill your heart with warmth and love. Merry Christmas!

💌 Contact: [email protected]
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🔥Purdue - Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=PPckIbZyD2I&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=PPckIbZyD2I&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Advanced Executive Program In Applied Generative AI - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=PPckIbZyD2I&utm_medium=DescriptionFirstFold&utm_source=Youtube

This Generative AI Full Course 2025 by Simplilearn provides a structured learning path, starting with the fundamentals of Generative AI and a detailed roadmap to mastering it. Learners explore top AI technologies, including DeepSeek R1, Deep Learning, and Search GPT, followed by essential tools like LangChain. The course dives into Generative Adversarial Networks (GANs), Transformers, and Long Short-Term Memory (LSTM) networks, forming the foundation of modern AI models. It then introduces Large Language Models (LLMs), Machine Learning concepts, and Reinforcement Learning, leading into practical applications like ChatGPT analysis and OpenAI Sora. Advanced topics include LLM benchmarking, Hugging Face tutorials, and OpenAI's ChatGPT O1 model. Practical insights into Generative AI tools for job interviews, Agentic AI, and AI monetization strategies help learners stay ahead in the field. The course concludes with a look at Google Quantum AI and Machine Learning interview preparation, ensuring a strong grasp of both theoretical and applied AI concepts.

Following are the topics covered in the Generative AI Full Course 2025:

0:00:00 Introduction to Gen AI Full Course 2025
0:00:45 What is Gen AI
0:11:24 Roadmap Gen AI
0:20:31 Top 10 AI Technologies
0:44:37 Deepseek r1
0:51:36 Deep Learning
0:59:53 Search GPT
1:02:08 Langchain
1:58:43 Generative Adversarial Tutorial
2:08:05 What are Gans
2:09:06 Transformers in AI
2:21:35 LSTM
2:22:59 Introduction to LLM
3:24:12 What is Machine Learning
4:20:44 Machine Learning Tutorial
6:26:07 Reinforcement Learning
6:45:58 CHatgpt analyse
6:56:54 Openai sora
7:05:47 LLM Benchmarkeing
7:56:30 Hugging Face and its tutorial
8:11:54 Open ai chatgpt o1 model
8:17:03 Gen ai tools for job interview
8:54:05 Agentic AI
9:11:10 Money with ai agents
9:19:33 Google Quantam AI
9:31:36 Machine Learning Interview Questions

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

⏩ Check out the Artificial Intelligence training videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULa5a

#genai #generativeai #artificialintelligence #ai #machinelearning #llm #simplilearn #2025

➡️ About Professional Certificate Program in Generative AI and Machine Learning

Dive into the future of AI with our Generative AI & Machine Learning course, in collaboration with E&ICT Academy, IIT Guwahati. Learn tools like ChatGPT, OpenAI, Hugging Face, Python, and more. Join masterclasses led by IITG faculty, engage in hands-on projects, and earn Executive Alumni Status.

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
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

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

Learning Path:
✅ Program Induction
✅ Programming Fundamentals
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning with TensorFlow (IBM)
✅ Deep Learning Specialization
✅ Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ Advanced Generative AI
✅ Capstone
Electives:
✅ ADL & Computer Vision
✅ NLP and Speech Recognition
✅ Reinforcement Learning

👉 Learn More At: https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=PPckIbZyD2I&utm_medium=Description&utm_source=Youtube

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

Extracting texts of various sizes, shapes and orientations from images containing multiple objects is an important problem in many contexts, especially, in connection to e-commerce, augmented reality assistance system in a natural scene, content moderation in social media platform, etc. The text from the image can be a richer and more accurate source of data than human inputs which can be used in several applications like Attribute Extraction, Offensive Text Classification, Product Matching, Compliance use cases, etc. Extracting text is achieved in 2 stages. Text detection: The detector detects the character locations in an image and then combines all characters close to each other to form a word based on an affinity score which is also predicted by the network. Since the model is at a character level, it can detect in any orientation. Post this, the text is then sent through the Recognizer module. Text Recognition: Detected text regions are sent to the CRNN-CTC network to obtain the final text. CNN’s are incorporated to obtain image features that are then passed to the LSTM network as shown in the below figure. Connectionist Temporal Classification(CTC) decoder operation is then applied to the LSTM outputs for all the time steps to finally obtain the raw text from the image.

Key Takeaways:

1. Understanding the need for text extraction from Product Images.
2. Deep Learning Techniques for detecting highly oriented text.
3. End to End understanding of CRNN-CTC network for text recognition with TF 2.0
4. Need for CTC loss and theoretical understanding of the same.
5. Usage of Text Extraction in various fields/domains.

About:
Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business.
Read more here: https://databricks.com/product/unifie...
Connect with us:
Website: https://databricks.com
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Instagram: https://www.instagram.com/databricksinc/ Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. https://databricks.com/databricks-named-leader-by-gartner

People claim that 70-80% of household dust is dead skin, but is it true?
Thanks to Google for sponsoring this video! Learn more about Search here: https://www.google.com/search/howsearchworks/

Special thanks to J.M.E.H van Bronswijk, author of 'House Dust Biology'. We exchanged emails to make sure I got my facts straight for this video. Below is an excerpt from her email to me, responding to my claims that start with a dash:

- Around half of airborne dust particles under 100um are skin scales
This is true for climates, regions and seasons where people live mostly indoors.
The 1 to 2 g of skin scales shed each 24 hours will end up in places where people are present (and rub their skin or have textile moving over the skin).
You can also look at it from a different angle: What else has the same size and could contribute? That will usually be pollen from outdoor sources, also depending on season, region and climate, as well as the ventilation regime of the building.
However, taken as the median value over a whole year, I consider your statement correct for regions with a temperate climate.

- 53% of dust particles vacuumed from a mattress were found to be skin scales
It depends a little on the type of mattress. For polyether mattresses the amount may even be larger.
For mattresses made of natural material it could be less since the mattress-material will also give off small particles.

- larger particles consist mostly of fibers, eg. cotton, paper, wool, synthetics
That's true .. including bread crumbs ..... 🙂

- skin scales seem to form a larger fraction of dust where we spend more time, e.g. in or near bed.
..... and on the couch used to view television or be active in gaming.
It has to do with the constant production of skin scales over the 24 hours.

- skin scales form a smaller fraction of dust if there are significant other sources, e.g. carpeting, dirt from outside etc.
Yes, everyting you walk on with your shoes or that recieves dirt from the outside with other means, will have a lessr percentage of human skin scales.
However, do not forget the skin scales of pets that will also be an active allergen for many people, and a food source for house dust mites.

Information on dust particle size ©ISO. This material is adapted from ISO 7708:1995, with permission of the American National Standards Institute (ANSI) on behalf of the International Organization for Standardization. All rights reserved.

Research and Writing by AJ Fillo and Derek Muller
Editing, Audio Mix & Master, and Computer animations by Jonny Hyman
Dust and character animation by Ivy Tello
Filming by Raquel Nuno
Thumbnail by Fictionalhead https://www.youtube.com/fictionalhead

Intro Music composed by Jonny Hyman
Additional Music from Epidemic Sound: Colored Spirals, Observations

🔥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.

🔹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

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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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A combination of Prompt Engineering and ChatGPT to learn the internals and technology behind large language models powering the new era of Artificial Intelligence.

A List of all prompts and keywords use in this video:
- https://github.com/prodramp/De....epWorks/blob/main/Ch

== Video Timeline ==
(00:00) Content Intro
(01:30) ChatGPT
(02:43) Transformer architecture
(09:10) Keywords Generation
(13:38) Text embedding
(17:43) Encoder and Decoder
(18:32) Self attention
(18:45) Multi-head self attention
(21:56) PyTorch Code Multi-head self attention
(23:37) Scaled Dot Product Attention
(27:45) Key deep learning methods
(28:53) Large language models
(29:49) LLM Parameter Count (Python Code)
(31:38) DALL-E large language model
(33:17) Key Differences DALL-E & ChatGPT
(34:20) List all Prompts
(34:40) ChatGPT Session Summary

Please visit:
https://prodramp.com | @prodramp
https://www.linkedin.com/company/prodramp

Content Creator:
Avkash Chauhan (@avkashchauhan)
https://www.linkedin.com/in/avkashchauhan

Tags:
#llm #chatgpt #promptengineering #openai #python #artificialintelligence

📌Generative AI Course: Masters Program : https://www.edureka.co/masters....-program/generative-
🔥Integrated MS+PGP Program in Data Science & AI:https://www.edureka.co/dual-ce....rtification-programs

Learn the fundamentals of generative artificial intelligence in this beginner-friendly course (2025 edition). We’ll cover what generative AI is, how it differs from traditional AI, key architectures (GANs, VAEs, Transformers), hands-on examples, prompt engineering, and real-world applications you can build today. No prior AI or deep-learning experience required.

✅ What you’ll learn:

What is generative AI & why it matters in 2026
Core models: GAN (Generative Adversarial Network), VAE (Variational Autoencoder)
Transformer architecture and large language models (LLMs)
Text-, image-, and audio-generation use cases
Basics of prompt-engineering and building your own simple GenAI app
Ethical, bias, and safety considerations for generative systems

📌 By the end of this course you’ll be equipped to explore your own generative-AI experiments and skill up for deeper tools.

🔔 If you enjoyed this video, Subscribe & hit the bell icon so you won’t miss further AI-tutorials in 2026. Leave a comment if you have questions or want to see a project walkthrough.

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

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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.

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐏𝐲𝐭𝐡𝐨𝐧 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 (Use code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎") : https://www.edureka.co/python-....programming-certific
This Edureka session on Python OOPS concepts (Python OOPs Blog: http://bit.ly/2JlVhFJ​) will help you understand Python Classes and Objects with examples. It will also explain the concept of OOPS in Python.
Topics Covered
00:00:00 Introduction
00:00:27 Why do we need functions?
00:01:53 What are Functions?
00:02:42 Hands-on
00:39:50 Object Oriented concepts
00:40:37 Python OOP is different than other OOP's
00:42:47 Use Case

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

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The Penetration Testing Full Course by Simplilearn covers essential topics in cybersecurity and ethical hacking. It starts with a cybersecurity tutorial for beginners, followed by an overview of ethical hacking and penetration testing basics. The course explores cybersecurity career roadmaps, salaries for penetration testers, and top cybersecurity certifications. Learners can discover hacking gadgets, phishing attacks, and Wireshark tutorials for network analysis. The course also introduces EthicalHacker GPT and highlights common cybersecurity mistakes and interview questions for aspiring professionals.

The following are the topics covered in the Penetration Testing Full Course:

00:00:00 Introduction to Penetration Testing Full Course
00:14:24 Cyber Security Tutorial For Beginners
00:22:19 What is Ethical Hacking
00:36:13 Top 5 Cybersecurity Certifications
01:01:34 Penetration Testing Tutorial for beginners
01:14:06 Cybersecurity Engineer roadmap
01:21:24 Penetration Tester Salary
03:56:50 Ethical Hacking Tutorial For Beginners
03:57:33 Top 7 Dangerous Hacking Gadgets
04:16:01 Phishing Attacks
04:33:30 EthicalHacker GPT
Toughest Cybersecurity Certifications
Common Cybersecurity Mistakes
Wireshark tutorial for beginners
Cyber security Interview Questions

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#ethicalhacking #cybersecurity #cybersecuritycertification #cybersecuritytutorial #simplilearn #2025

What Is Penetration Testing in Cyber Security?
Penetration testing is a controlled form of hacking into a web application or a mobile application, cyber security experts use ethical hacking techniques to find the flaws and then try to fix weaknesses. The results of a penetration test can be used to improve a system's security posture and patch vulnerabilities.

➡️ About Cyber Security Expert Masters Program
This cybersecurity expert program readies individuals for CEH, CompTIA Security+, and CISSP certifications, offering a holistic defense strategy against dynamic cyber threats. CEH emphasizes ethical hacking, CompTIA focuses on foundational security concepts, and CISSP covers advanced principles and management.

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Claude Code isn’t just another coding tool. t’s a game-changer for automation, DevOps, and productivity. Imagine combining the simplicity of Unix commands with the intelligence of an AI-powered assistant. That’s what Claude Code delivers.

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MIT 18.642 Topics in Mathematics with Applications in Finance, Fall 2024
Instructor: Peter Kempthorne
View the complete course: https://ocw.mit.edu/courses/18....-642-topics-in-mathe
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

The lecture introduces linear algebra with a focus on its applications in quantitative finance, covering vector and matrix fundamentals, portfolio valuation, and concepts like short selling, arbitrage, and contingent claims. It further explores stochastic matrices and Markov chains, eigenvalues and eigenvectors, and their roles in modeling financial markets, culminating in discussions on no-arbitrage conditions, market completeness, and pricing measures essential for option pricing theory.

License: Creative Commons BY-NC-SA
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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.

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐒𝐞𝐥𝐞𝐧𝐢𝐮𝐦 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠: https://www.edureka.co/seleniu....m-certification-trai code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎")
This video by Edureka helps you understand how to handle multiple windows when you are testing an application using Selenium. Following are the topics covered in this video:
00:00:00 Introduction
00:01:22 What is Selenium Webdriver?
00:03:29 Basic pre-requisites to run the test cases
00:04:05 Handling multiple windows in Selenium
00:05:29 Demo

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Database vs Data Warehouse vs Data Lake | Today we take a look at these 3 different ways to store data and the differences between them.

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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.

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

⏩ Check out more Artificial Intelligence videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULyr_

➡️ About Post Graduate Program In AI And Machine Learning

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

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Explore the capabilities of AI with our latest YouTube video on ChatGPT's revolutionary memory feature. In this How To Use ChatGPT Memory comprehensive video, we detail how ChatGPT remembers information from your past interactions to tailor and enhance your ongoing experiences. We'll guide you through how this memory mechanism captures essential information and seamlessly integrates it into future discussions. Through vivid real-life scenarios, we demonstrate the practical applications of this technology—from improving project management to customizing educational content and remembering personal preferences. This video is perfect for anyone curious about the practical impacts of AI in daily life and those interested in the technical aspects of how AI can adapt and learn over time. Tune in to discover how ChatGPT's memory is making AI interactions more intuitive and impactful.

In this How To Use ChatGPT Memory video, we start with:
00:00:00 Introduction to ChatGPT Memory Feature
00:01:18 Features of ChatGPT's Memory Feature
00:01:48 How to enable and Manage ChatGPT's Memory Feature
00:03:39 Introducing Temporary Chat Feature
00:06:21 Applications of ChatGPT's Memory Feature using prompts
00:10:52 Delete or Remove ChatGPT's Memory
00:15:31 Other Examples of ChatGPT's Memory Feature using prompts

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⏩ Check out More AI Videos By Simplilearn: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULyr_

➡️ About Post Graduate Program In AI And Machine Learning

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

✅ Key Features

- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
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- Master Classes delivered by Purdue faculty and IBM experts
- Simplilearn's JobAssist helps you get noticed by top hiring companies
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- Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools

✅ Skills Covered

- ChatGPT
- Generative AI
- Explainable AI
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- Supervised Learning
- Unsupervised Learning
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🔥NIT Warangal Post Graduate Diploma in AI & Machine Learning with Edureka: https://www.edureka.co/nitw-ai-ml-pgp
This Edureka video of "Chatbots using TensorFlow" gives you an idea about what are chatbots and how did they come into existence. It provides a brief introduction about all the layers involved in creating a chatbot using TensorFlow and Machine Learning.

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Check out our Deep Learning blog series: https://bit.ly/2xVIMe1
Check out our complete Youtube playlist here: https://bit.ly/2OhZEpz

---------------------------------------Edureka Post Graduate Courses-------------------------------------------

🔵 Artificial and Machine Learning PGD: https://bit.ly/3AylL0q

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

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.

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Why Learn Deep Learning With TensorFlow?

TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.

Machine learning is one of the fastest-growing and most exciting fields out there, and Deep Learning represents its true bleeding edge. Deep learning is primarily a study of multi-layered neural networks, spanning over a vast range of model architectures. Traditional neural networks relied on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kinds of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which constitutes the vast majority of data in the world.

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#Autoencoder #Tensorflow #DeepLearning #NeuralNetworks #python #MachineLearning #DimensionalityReduction
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