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( ** Apache Spark Training - https://www.edureka.co/apache-....spark-scala-certific ** )
This Edureka Spark Architecture Tutorial video will help you to understand the Architecture of Spark in depth. It includes an example where we will create an application in Spark Shell using Scala. It will also take you through the Spark Web UI, DAG and Event Timeline of the executed tasks.
The following topics are covered in this video:
1. Apache Spark & Its features
2. Spark Eco-system
3. Resilient Distributed Dataset(RDD)
4. Spark Architecture
5. Word count example Demo using Scala.
Check our complete Apache Spark and Scala playlist here: https://goo.gl/ViRJ2K
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#ApacheSparkTutorial #SparkArchitecture #Edureka
How it Works?
1. This is a 4 Week Instructor led Online Course, 32 hours of assignment and 20 hours of project work
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 work on a project, based on which we will provide you a Grade and a Verifiable Certificate!
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About the Course
This Spark training will enable learners to understand how Spark executes in-memory data processing and runs much faster than Hadoop MapReduce. Learners will master Scala programming and will get trained on different APIs which Spark offers such as Spark Streaming, Spark SQL, Spark RDD, Spark MLlib and Spark GraphX. This Edureka course is an integral part of Big Data developer's learning path.
After completing the Apache Spark and Scala training, you will be able to:
1) Understand Scala and its implementation
2) Master the concepts of Traits and OOPS in Scala programming
3) Install Spark and implement Spark operations on Spark Shell
4) Understand the role of Spark RDD
5) Implement Spark applications on YARN (Hadoop)
6) Learn Spark Streaming API
7) Implement machine learning algorithms in Spark MLlib API
8) Analyze Hive and Spark SQL architecture
9) Understand Spark GraphX API and implement graph algorithms
10) Implement Broadcast variable and Accumulators for performance tuning
11) Spark Real-time Projects
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Who should go for this Course?
This course is a must for anyone who aspires to embark into the field of big data and keep abreast of the latest developments around fast and efficient processing of ever-growing data using Spark and related projects. The course is ideal for:
1. Big Data enthusiasts
2. Software Architects, Engineers and Developers
3. Data Scientists and Analytics professionals
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Why learn Apache Spark?
In this era of ever-growing data, the need for analyzing it for meaningful business insights is paramount. There are different big data processing alternatives like Hadoop, Spark, Storm and many more. Spark, however, is unique in providing batch as well as streaming capabilities, thus making it a preferred choice for lightning fast big data analysis platforms.
The following Edureka blogs will help you understand the significance of Spark training:
5 Reasons to Learn Spark: https://goo.gl/7nMcS0
Apache Spark with Hadoop, Why it matters: https://goo.gl/I2MCeP
For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
๐ฅEdureka Data Science Master Program: https://www.edureka.co/masters....-program/data-scient
This Edureka session on Machine Learning with Tree-Based Models in Python will help you understand the Bagging & Boosting concepts in detail.
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About the Masters Program
Edurekaโs Machine Learning Engineer Masters Program makes you proficient in techniques like Supervised Learning, Unsupervised Learning and Natural Language Processing. It includes training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning such as Deep Learning, Graphical Models and Reinforcement Learning.
The Master's Program Covers Topics LIke:
Python Programming
PySpark
HDFS
Spark SQL
Machine Learning Techniques and Artificial Intelligence Types
Tokenization
Named Entity Recognition
Lemmatization
Supervised Algorithms
Unsupervised Algorithms
Tensor Flow
Deep learning
Keras
Neural Networks
Bayesian and Markovโs Models
Inference
Decision Making
Bandit Algorithms
Bellman Equation
Policy Gradient Methods
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Prerequisites
There are no prerequisites for enrolment to the Masters Program. However, as a goodwill gesture, Edureka offers a complimentary self-paced course in your LMS on SQL Essentials to brush up on your SQL Skills. This program is designed and developed for an aspirant planning to build a career in Machine Learning or an experienced professional working in the IT industry.
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For online Data Science training write to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).
๐ฅ๐๐๐ฎ๐ซ๐๐ค๐ ๐๐ข๐๐ซ๐จ๐ฌ๐จ๐๐ญ ๐๐ณ๐ฎ๐ซ๐ ๐๐๐ซ๐ญ๐ข๐๐ข๐๐๐ญ๐ข๐จ๐ง ๐๐ซ๐๐ข๐ง๐ข๐ง๐ ๐๐จ๐ฎ๐ซ๐ฌ๐ (๐๐ฌ๐ ๐๐จ๐๐: ๐๐๐๐๐๐๐๐๐) :https://www.edureka.co/microso....ft-certified-azure-s
The "Azure Architect Full Course" provides a thorough overview of essential Azure topics, including computing, networking, storage, security, and more. This Full Course is designed for aspiring Azure architects and provides practical insights into building scalable and secure solutions on the Microsoft Azure cloud platform.
00:00:00 Introduction
00:02:53 What is Azure?
00:14:07 Quiz
00:14:29 How To Create Azure Free Account?
00:20:07 Introduction to Azure Portal
00:35:07 Microsoft Azure Demo
01:09:04 Azure Virtual Machine
01:30:50 Quiz
01:31:14 Microsoft Azure Storage Overview
02:14:21 Azure Active Directory
02:41:18 Azure Load Balancer
03:14:44 Quiz
03:15:06 Azure Firewall
03:44:45 Quiz
03:45:06 Azure App Service
04:02:31 Quiz
04:03:03 Azure Database Services
04:33:49 Azure Data Factory
05:05:14 Quiz
05:05:37 Azure Databricks
05:39:02 Quiz
05:39:24 Azure Data Lake
05:54:05 Quiz
05:54:28 Azure Machine Learning
06:20:54 Introduction To Azure Kubernetes Service (AKS)
07:10:40 ARM Templates
07:38:57 Introduction to Azure IoT
07:57:18 What is Azure Service Bus?
08:54:26 AI on Microsoft Azure
09:07:00 Azure Certifications
09:17:17 How to become an Azure Data Engineer?
09:41:50 Azure Interview Questions And Answers
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๐ฅPurdue - Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=3eT5gjnNgUI&utm_medium=DescriptionFirstFold&utm_source=Youtube
๐ฅProfessional Certificate Program in Generative AI and Machine Learning - IITG (India Only) - https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=3eT5gjnNgUI&utm_medium=DescriptionFirstFold&utm_source=Youtube
๐ฅAdvanced Executive Program In Applied Generative AI - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=3eT5gjnNgUI&utm_medium=DescriptionFirstFold&utm_source=Youtube
This Gen AI Full Course video by Simplilearn will help you learn everything about Generative AI (Gen AI). The Gen AI full Course will begin with an in-depth exploration of generative artificial intelligence and its applications. It starts with an explanation of what Gen AI is, followed by the evolution of AI and a detailed roadmap for mastering generative AI. The course highlights future AI trends, top AI technologies, and career opportunities in the field. It includes hands-on machine learning projects for practice and tutorials on LangChain, deep learning, and advanced AI concepts like transformers, LSTMs, and recurrent neural networks. Additional topics include OpenAI tools such as ChatGPT, SearchGPT, and Sora, along with benchmarking large language models (LLMs) and generative adversarial networks. Reinforcement learning and machine learning tutorials are also covered, culminating with interview questions to prepare learners for AI-related roles.
The Full course covers the following topics:
00:00:00 Introduction to Gen AI Full Course
00:00:45 What is Gen AI
00:11:17 Evolution of AI
00:21:39 Roadmap Gen AI
00:37:18 AI Trends for the Fututre
00:37:59 Top 10 AI Technologies
00:47:50 AI Carrers
00:55:05 ML Projects For Practice
01:15:06 Wht is Langchain
01:34:03 Deep Learning Tutorial For Beginners
01:49:27 Open ai chatgpt o1 model
01:57:44 Search GPT
02:08:40 Openai sora
02:17:33 LLM Benchmarkeing
03:02:10 Generative Adversarial Tutorial
03:08:22 LSTM
03:09:23 Transformers in AI
03:17:04 Introduction to LLM
04:18:17 What is Machine Learning
05:14:49 Machine Learning Tutorial
07:20:12 Reinforcement Learning
08:49:51 Recurrent Neural Network
09:09:42 CHatgpt analyse
09:21:49 MAchine Learning Interview questions
โ
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โฉ Check out the Artificial Intelligence training videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULa5a
#genai #generativeai #artificialintelligence #ai #machinelearning #llm #simplilearn #2025
โก๏ธ 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:
โ
Program completion certificate from E&ICT Academy, IIT Guwahati
โ
Curriculum delivered in live virtual classes by seasoned industry experts
โ
Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
โ
Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
โ
Opportunity to earn an 'Executive Alumni Status' from E&ICT Academy, IIT Guwahati
โ
Eligibility for a campus immersion program organized at IIT Guwahati
โ
Exclusive hackathons and โask-me-anythingโ sessions by IBM
โ
Certificates for IBM courses and industry masterclasses by IBM experts
โ
Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
โ
Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
โ
Simplilearn's JobAssist helps you get noticed by top hiring companies
Skills Covered:
โ
Generative AI
โ
Prompt Engineering
โ
Chatbot Development
โ
Supervised and Unsupervised Learning
โ
Model Training and Optimization
โ
Model Evaluation and Validation
โ
Ensemble Methods
โ
Deep Learning
โ
Natural Language Processing
โ
Computer Vision
โ
Reinforcement Learning
โ
Machine Learning Algorithms
โ
Speech Recognition
โ
Statistics
Learning Path:
โ
Program Induction
โ
Programming Fundamentals
โ
Python for Data Science (IBM)
โ
Applied Data Science with Python
โ
Machine Learning
โ
Deep Learning with TensorFlow (IBM)
โ
Deep Learning Specialization
โ
Essentials of Generative AI, Prompt Engineering & ChatGPT
โ
Advanced Generative AI
โ
Capstone
Electives:
โ
ADL & Computer Vision
โ
NLP and Speech Recognition
โ
Reinforcement Learning
โ
Academic Masterclass
โ
Industry Masterclass
๐ Learn More At: https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=3eT5gjnNgUI&utm_medium=Description&utm_source=Youtube
๐ฅ Weโre launching the Modern Route-Full Stack Generative & Agentic AI Batch ๐ฅ
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Starts: 15th March 2026
โฐ Time: 8 PM โ 11 PM IST
๐๏ธ Schedule: Every Saturday & Sunday
This is not old-school AI โ
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from GenAI to Agentic AI, end-to-end & hands-on ๐
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๐ https://www.krishnaik.in/liveclass2/genai?id=9
If you were waiting for the right time, right roadmap, and right guidance โ
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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. CNNโs 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 Sparkโข, 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
Facebook: https://www.facebook.com/databricksinc
Twitter: https://twitter.com/databricks
LinkedIn: https://www.linkedin.com/company/databricks
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 ..... ๐
- 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 ยฉISO. 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
Top Christmas Songs of All Time ๐
๐ผ Best Christmas Music Playlist
๐ 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.
๐
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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๐ 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!
๐ Contact: [email protected]
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๐ฅPurdue - Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=PPckIbZyD2I&utm_medium=DescriptionFirstFold&utm_source=Youtube
๐ฅProfessional 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
๐ฅAdvanced 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
โ
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โฉ Check out the Artificial Intelligence training videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULa5a
#genai #generativeai #artificialintelligence #ai #machinelearning #llm #simplilearn #2025
โก๏ธ 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:
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Program completion certificate from E&ICT Academy, IIT Guwahati
โ
Curriculum delivered in live virtual classes by seasoned industry experts
โ
Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
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Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
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Opportunity to earn an 'Executive Alumni Status' from E&ICT Academy, IIT Guwahati
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Eligibility for a campus immersion program organized at IIT Guwahati
โ
Exclusive hackathons and โask-me-anythingโ sessions by IBM
โ
Certificates for IBM courses and industry masterclasses by IBM experts
โ
Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
โ
Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
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Simplilearn's JobAssist helps you get noticed by top hiring companies
Skills Covered:
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Generative AI
โ
Prompt Engineering
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Chatbot Development
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Supervised and Unsupervised Learning
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Model Training and Optimization
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Model Evaluation and Validation
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Ensemble Methods
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Deep Learning
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Natural Language Processing
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Computer Vision
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Reinforcement Learning
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Machine Learning Algorithms
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Speech Recognition
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Statistics
Learning Path:
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Program Induction
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Programming Fundamentals
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Python for Data Science (IBM)
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Applied Data Science with Python
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Machine Learning
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Deep Learning with TensorFlow (IBM)
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Deep Learning Specialization
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Essentials of Generative AI, Prompt Engineering & ChatGPT
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Advanced Generative AI
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Capstone
Electives:
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ADL & Computer Vision
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NLP and Speech Recognition
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Reinforcement Learning
๐ 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
๐ฅ๐๐๐ฎ๐ซ๐๐ค๐ ๐๐ฒ๐ญ๐ก๐จ๐ง ๐๐๐ซ๐ญ๐ข๐๐ข๐๐๐ญ๐ข๐จ๐ง ๐๐ซ๐๐ข๐ง๐ข๐ง๐ (Use code "๐๐๐๐๐๐๐๐๐") : https://www.edureka.co/python-....programming-certific
This Edureka session on Python OOPS concepts (Python OOPs Blog: http://bit.ly/2JlVhFJโ) 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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๐ฅEdureka 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.
๐นCheck our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE
๐นCheck 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!
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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 โHello Wordโ 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
๐Generative AI Course: Masters Program : https://www.edureka.co/masters....-program/generative-
๐ฅIntegrated 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). Weโll 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.
โ
What youโll 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
๐ By the end of this course youโll be equipped to explore your own generative-AI experiments and skill up for deeper tools.
๐ If you enjoyed this video, Subscribe & hit the bell icon so you wonโt miss further AI-tutorials in 2026. Leave a comment if you have questions or want to see a project walkthrough.
๐ด ๐๐๐๐ซ๐ง ๐๐ซ๐๐ง๐๐ข๐ง๐ ๐๐๐๐ก๐ง๐จ๐ฅ๐จ๐ ๐ข๐๐ฌ ๐
๐จ๐ซ ๐
๐ซ๐๐! ๐๐ฎ๐๐ฌ๐๐ซ๐ข๐๐ ๐ญ๐จ ๐๐๐ฎ๐ซ๐๐ค๐ ๐๐จ๐ฎ๐๐ฎ๐๐ ๐๐ก๐๐ง๐ง๐๐ฅ: https://edrk.in/DKQQ4Py
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๐ฅ๐๐๐ฎ๐ซ๐๐ค๐ ๐๐๐ฅ๐๐ง๐ข๐ฎ๐ฆ ๐๐๐ซ๐ญ๐ข๐๐ข๐๐๐ญ๐ข๐จ๐ง ๐๐ซ๐๐ข๐ง๐ข๐ง๐ : https://www.edureka.co/seleniu....m-certification-trai code "๐๐๐๐๐๐๐๐๐")
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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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.
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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.
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