GPT-3 has taken the world by storm, and for good reason: It lets you generate text with just a few prompts (i.e. 'few-shot learning') or even with no prompts and just the instruction (i.e. 'zero-shot learning'). But there are scenarios where the model does not deliver satisfying results out of the box. In these cases we need to train the GPT-3 model with our own dataset to improve the performance. In this talk he explored how this can be done and we saw a real-life application of this.

This speech by Heiko Hotz was held on November 18 at Data Science Conference Europe 2022 in person in Belgrade.

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

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🔥Edureka Machine Learning Certification Training: https://www.edureka.co/machine....-learning-certificat
This Edureka video on 'Data Exploration - Extract, Transform, Load' is the third class in the Python Machine Learning Series which gives a brief introduction to how we can explore the data starting from extraction and leading up to loading the data in a program.

🟠 𝐂𝐥𝐚𝐬𝐬 𝐒𝐜𝐡𝐞𝐝𝐮𝐥𝐞 🟠

[𝗦𝗮𝘁𝘂𝗿𝗱𝗮𝘆 - 𝟭𝟱𝘁𝗵 𝗔𝘂𝗴𝘂𝘀𝘁]
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Class 6 - Data Modeling 1 - Feature Engineering
Class 7 - Data Modeling 2 - Training The Model
Class 8 - Data Modeling 3 - Model Evaluation
Class 9 - Machine Learning Example
Class 10 - Advanced Machine Learning

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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.
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ChatGPT Full Course 2024 by simplilearn is a latest variant of ChatGPT Full Course. the couse will guide the aspiring AI Engineers to learn the critical AI and machine learning and ChatGPT AI models from the very Basic To Advanced This ChatGPT Tutorial by simplileatn will cover how to use ChatGPT 4 Omni, Data Analysis with chatGPT, programming with chatgpt, automation with chatgpt and much more. The ChatGPT full course with 4 Omni demonstration will cover the following topics:

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00:02:22 Top AI Tools
00:00:07:50 What is GPT 4?
00:13:52 Automate Excel using ChatGPT
01:24:12 How to Build a Website Using ChatGPT
02:06:35 How To Use ChatGPT For Web Development
02:32:22 Can ChatGPT Solve LeetCode Problems?
04:02:21 Create a Telegram Bot Using ChatGPT
04:19:21 Automate WhatsApp using ChatGPT
04:29:45 Build a Game using Python and ChatGPT
04:54:25 ChatGPT in Cybersecurity
05:24:09 ChatGPT for UI/UX Design
06:10:28 How to use ChatGPT for SEO?
07:02:19 Chat GPT for Content Creation
07:06:14 Master SEO Content Using ChatGPT
7:11:53 Explore 10 Mind-Blowing GPTs Inside ChatGPT - WebPilot Will Amaze You
7:23:43 OpenAI ChatGPT-4o
7:40:21 How To Use ChatGPT Memory ?
7:45:51 ChatGPT For Voice Activated AI Assiatant
7:58:04 How To Use ChatGPT Plugins - Step-By-Step Guide
8:07:15 ChatGPT 4.0 vs Gemini 1.5
8:17:11 WEB SCRAPPING Using CHATGPT
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9:03:03 How To Write Resume Using ChatGPT
9:08:40 What Is Multimodal AI?

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This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions.

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High Quality HDR 12K VIDEO ULTRA HD 120FPS, 60FPS, 30FPS For Your HDR 8K resolution devices. Amazing combination of 16k sensor and one of the sharpest lenses in the world Zeiss Otus set in addition of HDR brings image to life! You can use this collection of Hight Resolution clips in your Tv For The Living Room, Office, Lounge, Waiting Room, Spa, Showroom, Restaurant and more. Play It On Your LG Qled TV, Samsung Oled TV, Smart TV, Sony Device, Samsung Technology, Roku, Apple TV, IPad Pro, Apple XDR, Chromecast, Xbox, Playstation and more.

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In this video we go through the most basic and essential tensor operations that really build the foundation to TensorFlow 2.0 and is important to know before moving on to building neural networks which we will start with in the next tutorial! :)

Knowledge in Linear Algebra is very important to have an easier time understanding many tensor operations we go through so I would view as a prerequisite. I think if you don't have that then this series by 3Blue1Brown can be helpful:
https://www.youtube.com/playli....st?list=PLZHQObOWTQD

I learned a lot and was inspired to make these TensorFlow videos by the TensorFlow Specialization on Coursera. Below you'll find both affiliate and non-affiliate links, the pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
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OUTLINE:
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20:40 - Ending words

Difference between AI/ML/DL?? How they are interlinked??

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"Symmetry, as wide or narrow as you may define its meaning, is one idea by which man through the ages has tried to comprehend and create order, beauty, and perfection." and that was a quote from Hermann Weyl, a German mathematician who was born in the late 19th century.

The last decade has witnessed an experimental revolution in data science and machine learning, epitomised by deep learning methods. Many high-dimensional learning tasks previously thought to be beyond reach -- such as computer vision, playing Go, or protein folding -- are in fact tractable given enough computational horsepower. Remarkably, the essence of deep learning is built from two simple algorithmic principles: first, the notion of representation or feature learning and second, learning by local gradient-descent type methods, typically implemented as backpropagation.

While learning generic functions in high dimensions is a cursed estimation problem, many tasks are not uniform and have strong repeating patterns as a result of the low-dimensionality and structure of the physical world.

Geometric Deep Learning unifies a broad class of ML problems from the perspectives of symmetry and invariance. These principles not only underlie the breakthrough performance of convolutional neural networks and the recent success of graph neural networks but also provide a principled way to construct new types of problem-specific inductive biases.

This week we spoke with Professor Michael Bronstein (head of graph ML at Twitter) and Dr.
Petar Veličković (Senior Research Scientist at DeepMind), and Dr. Taco Cohen and Prof. Joan Bruna about their new proto-book Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

Enjoy the show!

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
https://arxiv.org/abs/2104.13478

[00:00:00] Tim Intro
[00:01:55] Fabian Fuchs article
[00:04:05] High dimensional learning and curse
[00:05:33] Inductive priors
[00:07:55] The proto book
[00:09:37] The domains of geometric deep learning
[00:10:03] Symmetries
[00:12:03] The blueprint
[00:13:30] NNs don't deal with network structure (TedX)
[00:14:26] Penrose - standing edition
[00:15:29] Past decade revolution (ICLR)
[00:16:34] Talking about the blueprint
[00:17:11] Interpolated nature of DL / intelligence
[00:21:29] Going tack to Euclid
[00:22:42] Erlangen program
[00:24:56] “How is geometric deep learning going to have an impact”
[00:26:36] Introduce Michael and Petar
[00:28:35] Petar Intro
[00:32:52] Algorithmic reasoning
[00:36:16] Thinking fast and slow (Petar)
[00:38:12] Taco Intro
[00:46:52] Deep learning is the craze now (Petar)
[00:48:38] On convolutions (Taco)
[00:53:17] Joan Bruna's voyage into geometric deep learning
[00:56:51] What is your most passionately held belief about machine learning? (Bronstein)
[00:57:57] Is the function approximation theorem still useful? (Bruna)
[01:11:52] Could an NN learn a sorting algorithm efficiently (Bruna)
[01:17:08] Curse of dimensionality / manifold hypothesis (Bronstein)
[01:25:17] Will we ever understand approximation of deep neural networks (Bruna)
[01:29:01] Can NNs extrapolate outside of the training data? (Bruna)
[01:31:21] What areas of math are needed for geometric deep learning? (Bruna)
[01:32:18] Graphs are really useful for representing most natural data (Petar)
[01:35:09] What was your biggest aha moment early (Bronstein)
[01:39:04] What gets you most excited? (Bronstein)
[01:39:46] Main show kick off + Conservation laws
[01:49:10] Graphs are king
[01:52:44] Vector spaces vs discrete
[02:00:08] Does language have a geometry? Which domains can geometry not be applied? +Category theory
[02:04:21] Abstract categories in language from graph learning
[02:07:10] Reasoning and extrapolation in knowledge graphs
[02:15:36] Transformers are graph neural networks?
[02:21:31] Tim never liked positional embeddings
[02:24:13] Is the case for invariance overblown? Could they actually be harmful?
[02:31:24] Why is geometry a good prior?
[02:34:28] Augmentations vs architecture and on learning approximate invariance
[02:37:04] Data augmentation vs symmetries (Taco)
[02:40:37] Could symmetries be harmful (Taco)
[02:47:43] Discovering group structure (from Yannic)
[02:49:36] Are fractals a good analogy for physical reality?
[02:52:50] Is physical reality high dimensional or not?
[02:54:30] Heuristics which deal with permutation blowups in GNNs
[02:59:46] Practical blueprint of building a geometric network architecture
[03:01:50] Symmetry discovering procedures
[03:04:05] How could real world data scientists benefit from geometric DL?
[03:07:17] Most important problem to solve in message passing in GNNs
[03:09:09] Better RL sample efficiency as a result of geometric DL (XLVIN paper)
[03:14:02] Geometric DL helping latent graph learning
[03:17:07] On intelligence
[03:23:52] Convolutions on irregular objects (Taco)

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This video on Encapsulation in Java will help beginners to understand the fundamentals of Encapsulation in Java with practical examples for a better understanding. This Java encapsulation tutorial will cover the following critical " encapsulation in java " topics as enlisted below:

00:00 Introduction to Java Encapsulation
00:22 What is Encapsulation in Java?
01:25 Practical Session of java encapsulation

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What is Java?
Java is an object-oriented, class-based, high-level programming language used for software development, mobile application development, website development, desktop application development, and much more. Java is one of the leading and in-demand programming languages in the current IT industry.

Why learn Java?
Java is a very powerful and versatile programming language used for a variety of needs. Java is used for web development, android development, mobile and desktop development, cloud computing and much more. Having a comfortable understanding of Java would prove to be a greater advantage to find yourself a great career.

What is Encapsulation in Java?
Encapsulation in java is one of the fundamental object-oriented programming paradigms. Encapsulation is the process of combining and storing the methods and variables together inside one single class. This makes the method and variables to be bonded together.

If you’re looking to master web application development for virtually any computing platform, this Java Certification Training course is for you.

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚'𝐬 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐚𝐧𝐝 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬 𝐜𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐚𝐧𝐝 𝐜𝐨𝐮𝐫𝐬𝐞𝐬 (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎) : https://www.edureka.co/program....ming-and-frameworks-
This Edureka video on Programming For Beginners will help you to Learn Programming basics with examples. This Programming for beginner video covers all the topics for all the three categories of learners - beginner, intermediate and experienced professionals.

Below are the programming languages covered in this Programming Full course video:

00:00:00 Introduction
00:01:30 Agenda
00:02:44 Pyhton Basics
00:04:27 Why use python?
00:25:09 Comparision Operators
00:43:16 range
00:48:26 Counter
00:55:20 Defaultdict
00:58:47 When to use Sets in python
01:01:23 Python set operations
01:12:35 What is an Array ?
01:14:19 How to create arrays in python
01:31:34 Slicing an array
01:34:09 Looping through an Array
01:37:36 Classes and objects in python
01:42:47 Python Classes
02:04:20 Java
02:10:00 Variables in /java
02:31:56 Operator in java
02:46:36 Loops in Java
02:59:32 Object Oriented Programming (OOPS)
03:03:51 OOPS Concept
03:27:13 OOPS Characteristics
03:34:54 Exception in java
03:46:07Exception Handling Methods
03:54:44 History of C
03:55:36 Features of C Language
04:00:46 Keywords
04:03:22 Strings
04:05:05 Identifiers
04:06:49 Rules for Identifier
04:09:46 Operators
04:14:34 Datatypes
04:16:18 Local Variable
04:21:28 PreProcessor Directives
04:27:31 Control Statement
04:45:37 Loops
04:55:58 Pointers
05:00:17 Functions
05:04:36 Rules for using Functions
05:06:19 How to use Functions
05:08:03 Data Structure
05:10:38 One-Dimensional Array
05:14:05 Lists
05:27:53 I+Undirected Graphs
05:31:20 Files
05:35:39 Strings
05:39:58 Structure
05:41:41 Union
05:43:25 Structure v/s Union
05:44:16 Memory allocations
05:48:35 Sorting algorithm
05:53:45 Insertion Algorithm
05:58:56 SelectionAlgorithm
06:01:31 Selection Algorithm
06:04:06 Features of C++ Language
06:04:58 Installation of C++ in windows
06:07:33 Structure of C++ Program
06:10:09 Identifers
06:11:52 Keywords
06:15:19 Arrays
06:22:13 Lists
06:36:01 Functions
06:42:55 Structure
06:43:47 Enumeration
06:47:14 Variable types
06:52:24 Modifiers
06:53:16 Type of Qualifiers
06:54:00 Types of operators
06:56:00 Control Statement
07:06:12 Loops
07:10:31 Features of OOPS
07:12:15 Encapsulation
07:20:00 Interface
07:21:44 Constructor
07:22:36 Destructor
07:28:38 Deallocation
07:30:21 Multithreading
07:33:48 Interview Questions
09:29:23 What is Javascript
09:33:42 Benefits of Javascript
10:18:31 Loops in Javascript
10:39:14 Javascript Array
10:41:50 Javascript Array Methods
11:03:23 Why Learn coding



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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'𝐬 𝐏𝐲𝐭𝐡𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐏𝐫𝐨𝐠𝐫𝐚𝐦 (𝐔𝐬𝐞 𝐜𝐨𝐝𝐞 '𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎'): https://www.edureka.co/python-....programming-certific
This Edureka "Python for Beginners" session takes you through all the basic concepts that you should learn in Python. Learn to code in Python in under 1 hour. Watch this Python tutorial to get started with Python programming language.

Below are the topics covered in this Python for Beginners tutorial:
00:00 Introduction
00:57 What is Python
01:29 Why use Python
02:47 Getting Started with Python
03:33 Installing Python
06:45 Data Types and Variables in Python
12:35 Receiving Input in Python
15:02 String Operations in Python
19:36 Arithmetic Operators in Python
21:59 Operator Precedence
23:09 Comparison Operators in Python
24:43 Logical Operators in Python
27:01 If Statements in Python
30:40 While Loops in Python
33:40 Python Lists
36:35 List Methods in Python
39:15 For Loops in Python
41:21 Range Function in Python
42:55 Tuples in Python
44:33 Conclusion

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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

🔵 DevOps Online Training: http://bit.ly/3VkBRUT
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🔵 React Online Training: http://bit.ly/3Vc4yDw
🌕 Tableau Online Training: http://bit.ly/3guTe6J
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🌕 Selenium Online Training: http://bit.ly/3EVDtis
🔵 PMP Online Training: http://bit.ly/3XugO44
🌕 Salesforce Online Training: http://bit.ly/3OsAXDH
🔵 Cybersecurity Online Training: http://bit.ly/3tXgw8t
🌕 Java Online Training: http://bit.ly/3tRxghg
🔵 Big Data Online Training: http://bit.ly/3EvUqP5
🌕 RPA Online Training: http://bit.ly/3GFHKYB
🔵 Python Online Training: http://bit.ly/3Oubt8M
🌕 Azure Online Training: http://bit.ly/3i4P85F
🔵 GCP Online Training: http://bit.ly/3VkCzS3
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🔵 Angular Online Training: http://bit.ly/3EYcCTe

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🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
🌕 Cloud Architect Masters Program: http://bit.ly/3OvueZy
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🌕 Professional Certificate 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

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📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

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


Got a question on the topic? Please share it in the comment section below and our experts will answer it for you.

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

About the course :
What is Python?
Python is a widely used programming language that can be used for small and large-scale projects. Python allows you to seamlessly integrate web development with data analysis. Python's wide adoption is due in part to its standard library, accessibility, and support for multiple paradigms, such as procedural, functional and object-oriented programming styles. Python modules can interact with many databases making it an excellent choice to learn data science and machine-learning.

What if I miss any of the Python live classes?
"You will never miss a lecture at Edureka! You can choose either of the two options:
View the recorded session of the Python online class available in your LMS.
You can attend the missed python online training and certification session, in any other live batch."

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In this video on "Best Web Development Courses With Certification," we will discuss top 4 web development certifications. If you are looking to advance your career in web development, Check out our top picks for the best web development certifications to have in 2023. Web development is the process of creating and maintaining websites and web applications using programming languages and other tools. It involves designing, coding, testing, and deploying digital services for the internet or intranet.

00:00 - Best Web Development Courses With Certification
01:36 - What is Web development?
02:13 - Post Graduate Program In Full Stack Web Development
04:02 - Full Stack Developer - MEAN Stack
05:36 - Full Stack Java Developer Certification
07:04 - Caltech Coding Bootcamp

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⏩ Check out the Full Stack tutorial videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULCC3

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#FullStack #FullStackDevelopment #FullStackWebDevelopment #FullStackDeveloper #FullStackDeveloperCourse
#WhatIsFullStack #WhatIsFullStackWebDevelopment #FullStackWebDevelopmentCourse #FullStackTraining #FrontEndDevelopment #WebDevelopment #WebDevelopmentCourse #Simplilearn

✅ About Post Graduate Program In Full Stack Web Development
This program will give you the foundation for building full-stack web apps using the Java programming language. You'll begin with the basics of JavaScript, and then venture into some of the more advanced concepts like Angular, Spring Boot, Hibernate, JSPs, and MVC. Now is the perfect time to get started on your career as a full-stack web developer!

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✅ Skills Covered
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