🔥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-

Join us for the AI & ML Full Course 2025, a complete live tutorial hosted by edureka! designed to help you master Artificial Intelligence and Machine Learning from the ground up. This live session will guide you through key concepts such as supervised and unsupervised learning, deep learning, neural networks, natural language processing, and real-world model deployment. Whether you're a beginner looking to enter the world of AI or a professional aiming to enhance your skills, this course is structured to make complex topics easy to understand. Using hands-on projects and Python-based examples, you’ll gain the practical knowledge needed to build intelligent systems and data-driven applications. This session is ideal for students, job seekers, developers, and tech enthusiasts who want to stay ahead in the AI/ML landscape in 2025. Make sure to join live to engage with instructors in real time and earn your certificate of participation. Subscribe to our channel and turn on notifications so you don’t miss this powerful learning experience.
00:00:00 Introduction
00:01:47 What is Artificial Intelligence?
00:07:49 Types of Artificial Intelligence
00:18:56 AI vs Machine Learning vs Deep Learning
00:32:41 Artificial Intelligence with Python
02:11:47 What is Machine Learning?
02:23:29 Types of Machine Learning Models
02:30:35 Machine Learning Algorithm
02:52:29 Linear Regression Algorithm
02:59:55 Logistic Regression Algorithm
03:47:04 Linear Regression Vs Logistic Regression
03:50:35 Decision Tree Algorithm
04:36:09 Random Forest
05:01:24 KNN Algorithm
05:33:47 Naive Bayes Classifier
05:55:28 Support Vector Machine
06:20:59 K- Means Clustering Algorithm
06:44:19 Hierarchical Clustering
06:50:41 Apriori Algorithm Explained
07:08:11 What is Deep Learning?
07:30:14 Artificial Neural Network
08:02:35 Convolutional Neural Network
08:23:06 Recurrent Neural Networks
08:52:02 LSTM Explained
09:45:59 Transformers Neural Networks Explained
09:56:02 What are GANs?
10:08:22 Future of AI/ML
10:22:58 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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Please write back to us at [email protected] or call us at IND: 9606058406 / US: +18885487823 (toll-free) for more information.

In this detailed video, we delve into the fascinating world of Generative AI in Telugu. We explore the concepts of Artificial Intelligence (AI), Deep Learning (DL), Machine Learning (ML), Natural Language Processing (NLP), and the revolutionary GPT-3 model. Join us as we unravel the intricacies of Generative AI and its applications in various fields. Additionally, we discuss the crucial topic of Discrimination AI, shedding light on the ethical considerations and challenges associated with this technology. If you're interested in understanding the advancements and implications of AI in Telugu, this video is a must-watch! #GenerativeAI #Telugu #ArtificialIntelligence

🔴 𝐋𝐞𝐚𝐫𝐧 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐅𝐨𝐫 𝐅𝐫𝐞𝐞! 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐘𝐨𝐮𝐓𝐮𝐛𝐞 𝐂𝐡𝐚𝐧𝐧𝐞𝐥: https://edrk.in/DKQQ4Py
🔥 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐖𝐞𝐛 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐂𝐨𝐮𝐫𝐬𝐞 : https://www.edureka.co/complete-web-developer (Use code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎")
This Edureka video on Build MERN Stack App from Scratch" will provide you with fundamental concepts of MongoDB, Express.js, React.js, and Node.js with hands-on.

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

📝Feel free to share your comments below.📝

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
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🔴 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 : https://bit.ly/43vmME8

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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.

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

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

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

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

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---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐚𝐬𝐭𝐞𝐫𝐬 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬---------

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----------------------------------
How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

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

About the Course
Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.

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

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

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

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 where consumer decisions come from, beginning with consumer preferences. He then builds on these concepts to explain the utility function, which is a mathematical expression of consumer preference. Keywords: micoreconomics, consumer demand, preferences, utility function

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

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

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

Other recommended resources on the topic.

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

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

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

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

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

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

Timestamps

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

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

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

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

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

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

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For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai

November 18, 2025
This lecture covers career advice and a guest speaker.

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

Please follow along with the course schedule and syllabus: https://cs230.stanford.edu/syllabus/

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

Guest Speaker
Laurence Moroney
Best-selling AI author and award-winning researcher

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

🟢 Listen on Spotify: https://magicmusic.lnk.to/theBestPop

Tracklist:
0:00:00 01 V.GIRL, lost., Pop Mage - Flowers
0:03:08 02 Harley Bird, lost. _ Pop Mage - Attention
0:06:50 02 Harley Bird, lost., Pop Mage - Save Your Tears
0:09:54 03 Benlon, Pop Mage - We Don_t Talk Anymore
0:13:53 03 lost. , Honeyfox, Pop Mage - I Like The Way You Kiss Me (Acoustic)
0:16:30 04 Die for You - The Weeknd (Tiyon)
0:20:38 05 Hannah Gracelynn, lost., Pop Mage - Infinity
0:23:51 05 Honeyfox, lost., Pop Mage - Dancing With Your Ghost
0:26:51 05 Honeyfox, lost., Pop Mage - Kings & Queens
0:29:49 05 lost. _ Pop Mage - Mood
0:32:33 05 Mingue, lost. _ Pop Mage - I Love You 3000
0:36:00 06 Honeyfox _ lost. _ Pop Mage - A Thousand Years
0:39:58 06 Honeyfox, lost., Pop Mage - Legends Never Die
0:42:34 06 loudoun, lost., Pop Mage - Until I Found You
0:45:39 07 Honeyfox, lost., Pop Mage - Let Me Down Slowly
0:49:11 07 Onyra, lost., Pop Mage - 7 Years
0:52:55 08 Jemma Johnson, lost., Pop Mage - See You Again
0:56:02 08 Vince Palmeri, lost., Pop Mage - I'm Good (Blue)
0:59:20 09 Honeyfox, lost., Pop Mage - Can't Help Falling In Love With You
1:02:06 09 lost., Honeyfox, Pop Mage - Heat Waves
1:04:56 10 Honeyfox, lost., Pop Mage - Comethru
1:08:08 10 Michelle Ray, lost., Pop Mage - Apologize
1:11:13 Simon Erics, lost. _ Pop Mage - Bad Liar
1:15:27 Timmy Commerford, lost., Pop Mage - At My Worst
1:18:43 Zelli King, lost., Pop Mage - Love Is Gone
1:21:40

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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.

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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.

Recorded live at the Agent Engineering Session Day from the AI Engineer Summit 2025 in New York. Learn more at https://ai.engineer and purchase tickets to our next event, the AI Engineer World's Fair, in SF June 3 - 5 here: https://ti.to/software-3/ai-en....gineer-worlds-fair-2

About Barry:

Barry is a member of technical staff on Anthropic's Applied AI team, focusing on developing agentic systems with enterprises and startups. Previously, he was a tech lead on the Monetization genAI team at Meta, where he claimed the inaugural 'AI Engineer' title. He holds degrees in Computer Science and Industrial Engineering from Northwestern