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In this video on the Power BI full course, we'll learn the basics of power bi and understand the different components of Power B, how to use Dax functions to derive value out of your data, and how to publish dashboards on to the power bi service.

Dataset Link - https://drive.google.com/drive..../folders/1De_OsIU_M_

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➡️About Caltech Data Analytics Bootcamp
The Caltech Data Analytics Bootcamp is ideal for working professionals from all backgrounds. Develop core skills such as mastering Excel, creating data-driven presentations, data manipulation with SQL, analyzing data with Python, and data visualization with Tableau. Learn data analysis with tools such as AWS.

✅Key Features
- Simplilearn Career Service helps you get noticed by top hiring companies
- Data Analytics Bootcamp Certificate from Caltech CTME
- Caltech CTME Circle Membership
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- Access to integrated Data Analytics Labs

✅Skills Covered
- Data Analytics
- Statistical Analysis using Excel
- Data Analytics using Python
- Data Visualization with Tableau
- Linear and Logistic Regression
- Data Manipulation
- & more

Learn more at: https://www.simplilearn.com/data-analytics-bootcamp?utm_campaign=PowerBi-IydphZy_Pfo&utm_medium=Descriptionff&utm_source=youtube

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🔥 Python Certification Training: https://www.edureka.co/data-sc....ience-python-certifi
This Edureka video on 'Predictive Analysis Using Python' covers the concept of making predictions based on data analysis and modeling using machine learning. Following are the topics discussed in this session:
00:00 - Introduction
00:53 - What is Predictive Analysis?
01:44 - Applications of Predictive Analysis
04:34 - Steps Involved in Predictive Analysis
08:54 - Predictive Analysis Using Python

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🔹Blog Series: http://bit.ly/2sqmP4s

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How it Works?

Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. Machine Learning training will provide a deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in the python programming language. Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real-life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in the python programming language to enhance your learning experience.

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Why Learn Machine Learning using Python?

Data Science is a set of techniques that enables computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.

After completing this Machine Learning Certification Training using Python, you should be able to:
Gain insight into the 'Roles' played by a Machine Learning Engineer
Automate data analysis using python
Describe Machine Learning
Work with real-time data
Learn tools and techniques for predictive modeling
Discuss Machine Learning algorithms and their implementation
Validate Machine Learning algorithms
Explain Time Series and it’s related concepts
Gain expertise to handle business in the future, living the present
Who should go for this Machine Learning Certification Training using Python?

Edureka’s Python Machine Learning Certification Course is a good fit for the below professionals:
Developers aspiring to be a ‘Machine Learning Engineer'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
'Python' professionals who want to design automatic predictive models
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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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🔥Edureka’s Generative AI Master course: https://www.edureka.co/masters....-program/generative-
Explore the fundamentals and applications of Generative AI in this comprehensive Generative AI Full course, featuring tutorials on essential concepts such as Text Classification, Autoencoders, GANs, and models like ChatGPT. Delve into the basics of Generative AI, Artificial Intelligence, Machine Learning, and Deep Learning while exploring popular tools like TensorFlow and Keras. Gain insights into various types of AI and learn how to become an AI Engineer.


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

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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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🔥Purdue - Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=VfxTH3U7-ns&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=VfxTH3U7-ns&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Advanced Executive Program In Applied Generative AI - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=VfxTH3U7-ns&utm_medium=DescriptionFirstFold&utm_source=Youtube

The Gen AI Full Course 2025 By Simplilearn covers various concepts of Generative AI, starting with an Introduction to Artificial Intelligence and the concept of Generative AI. It outlines a roadmap to becoming a Gen AI Engineer, focusing on essential tools like OpenAI ChatGPT models and AI career options. The course dives deep into Deep Learning, Search GPT, LangChain, and OpenAI Sora. It includes tutorials on Generative Adversarial Networks (GANs), Transformers, LSTM, LLMs, and Machine Learning fundamentals. Advanced topics include Reinforcement Learning, Recurrent Neural Networks, ChatGPT analysis, LLM Benchmarking, and Open AI Strawberry. The course provides hands-on insights into GAN applications, Transformer models, and neural networks essential for Gen AI professionals.

Following are the Topics covered in this Gen AI Full Course 2025 By Simplilearn

00:00:00 Introduction to Gen AI Full Course
00:08:08 What is Artificial Intelligence
00:08:53 What is Generative AI
00:19:32 Roadmap to become a Gen AI Engineer
00:33:07 Gen ai tools for job interview
00:48:31 Open ai chatgpt o1 model
00:50:21 AI Careers to explore
01:04:02 Deep Learning Tutorial
01:12:19 Search GPT Tutorial
01:14:34 Langchain Tutorial
01:37:28 Openai sora Tutorial
02:22:05 Generative Adversarial Tutorial
02:31:27 What are GANS
02:32:28 Transformers in AI
02:44:57 LSTM Tutorial
02:46:21 Large Language Models Tutorial
03:47:34 What is Machine Learning
04:44:06 Machine Learning Tutorial
06:49:29 Reinforcement Learning Tutorial
10:12:12 Recurrent Neural Network Tutorial
10:32:03 ChatGPT analyze Tutorial
10:40:56 LLM Benchmarking Tutorial
10:46:38 Open AI Strawberry Tutorial

✅ 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

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➡️ 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
✅ Academic Masterclass
✅ Industry Masterclass

👉 Learn More At: https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=VfxTH3U7-ns&utm_medium=Description&utm_source=Youtube

🧪AI Agents Labs for Free: https://kode.wiki/3Wh4DZ6

Learn everything about AI agents from scratch in this comprehensive tutorial. No prior knowledge required. We'll take you from zero to building production-ready AI systems with hands-on labs.

🎯 What You'll Learn:
• AI Fundamentals - LLMs, tokens, embeddings, and context windows
• LangChain - Simplify AI development with pre-built components
• Prompt Engineering - Zero-shot, few-shot, and chain-of-thought techniques
• Vector Databases - Semantic search with ChromaDB and Pinecone
• RAG (Retrieval Augmented Generation) - Build intelligent document search
• LangGraph - Create multi-step AI workflows and agents
• MCP (Model Context Protocol) - Connect AI to external tools

🔧 Hands-On Labs Include:
✓ Making your first OpenAI API calls
✓ Building semantic search engines
✓ Creating RAG systems for document retrieval
✓ Developing multi-agent workflows
✓ Integrating external tools with MCP

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00:00 - Introduction to AI Agents
00:40 - How LLMs work in real time?
04:56 - Embeddings & Vector Representations
05:56 - How LangChain works?
10:12 - Practice Labs - Your First AI API Call
14:57 - Practice Labs - LangChain
17:57 - Prompt Engineering Techniques
21:21 - Practice Labs - Master Prompt Engineering
24:46 - Vector Databases Deep Dive
31:27 - Practice Labs - Build Semantic Search Engine
35:15 - RAG (Retrieval Augmented Generation)
38:14 - Practice Labs - RAG Implementation
42:14 - LangGraph for AI Workflows
45:51 - Practice Labs - Build Stateful AI Workflow
48:51 - Model Context Protocol (MCP)
51:56 - Practice Labs - Advanced MCP Concepts
55:21 - Conclusion

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MIT 18.642 Topics in Mathematics with Applications in Finance, Fall 2024
Instructors: Vasily Strela, Jake Xia, and 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

This video provides an introductory overview of a course combining mathematical theory and real-world financial applications, featuring lectures by academics and industry experts. The instructors emphasize the practical use of mathematics in finance, covering topics like bond math, portfolio optimization, and machine learning, while utilizing tools such as RStudio Cloud for data analysis. Additionally, the course includes guest speakers from prominent financial institutions, offering students exposure to cutting-edge quantitative finance concepts and industry practices.

License: Creative Commons BY-NC-SA
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More courses at https://ocw.mit.edu
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MIT 3.020 Thermodynamics of Materials, Spring 2021
Instructor: Rafael Jaramillo

View the complete course: https://ocw.mit.edu/courses/3-....020-thermodynamics-o
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

This first class session introduces entropy and spontaneous processes, molecular interactions, and enthalpy, as well as the scope and use of thermodynamics.

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

We're going to build a variational autoencoder capable of generating novel images after being trained on a collection of images. We'll be using handwritten digit images as training data. Then we'll both generate new digits and plot out the learned embeddings. And I introduce Bayesian theory for the first time in this series :)

Code for this video:
https://github.com/llSourcell/....how_to_generate_imag

Mike's Winning Code:
https://github.com/xkortex/how...._to_win_slot_machine

SG's Runner up Code:
https://github.com/esha-sg/Int....ro-DeepLearning-Sira

Please subscribe! And like. And comment. That's what keeps me going.

2 things
-The embedding visualization at the end would be more spread out if i trained it for more epochs (50 is recommended) but i just used 5.
-The code in the video doesn't fully implement the reparameterization trick (to save space) but check the GitHub repo for details on that.

More Learning resources:
https://jaan.io/what-is-variat....ional-autoencoder-va
http://kvfrans.com/variational....-autoencoders-explai
http://blog.fastforwardlabs.co....m/2016/08/12/introdu
http://blog.fastforwardlabs.co....m/2016/08/22/under-t
http://blog.evjang.com/2016/11..../tutorial-categorica
https://jmetzen.github.io/2015-11-27/vae.html

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🔥 Prompt Engineering with LLM Course: https://www.edureka.co/prompt-....engineering-generati
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Dive into the world of artificial intelligence with this comprehensive LLM Prompt Engineering Full Course by edureka! in collaboration with Veranda Enterprise. In this course, you'll learn how to effectively communicate with large language models like ChatGPT by mastering the art of prompt engineering. From the fundamentals of zero-shot and few-shot prompting to advanced techniques like chain-of-thought and structured prompting, this course is designed to equip you with the practical skills needed to build powerful AI-driven applications. Whether you're a developer, data scientist, or complete beginner, this full course provides real-world examples, hands-on demos, and expert tips to help you unlock the full potential of generative AI. Start your journey into prompt engineering and take your AI skills to the next level.

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