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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Change the World Through Data

#datascience #ai #ml #artificialintelligence #bigdata #dataanalytics #gpt3

Ms. Coffee Bean explains how a huge collaboration of researchers managed to extract training data from large language models like GPT-2. Why is this even possible and what does this mean for even larger models like GPT-3?
Discussed paper:
" Extracting Training Data from Large Language Models" explained by Carlini et al. 2020.

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📺 GPT-3 – what you need to know: https://youtu.be/5fqxPOaaqi0

Outline:
* 00:00 Large Language Models
* 01:55 GPT-2
* 02:33 Why is it possible?
* 03:38 k-eidetic memorization
* 04:21 How does the attack work?
* 05:49 How bad is it?
* 08:12 What to do?

📄 Paper explained: Carlini, N., Tramer, F., Wallace, E., Jagielski, M., Herbert-Voss, A., Lee, K., ... & Oprea, A. (2020). Extracting Training Data from Large Language Models. arXiv preprint arXiv:2012.07805. https://arxiv.org/pdf/2012.07805.pdf

-------------------------------------------------------------
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#AICoffeeBreak #MsCoffeeBean #GPT #MachineLearning #AI #research

Learn about 10 security vulnerabilities every JavaScript developer should know. First try to find the vulnerabilities in the different code examples. Then learn how to fix the issues.

✏️ Brandon from Semgrep developed this course.

🔗 Learn more about Semgrep: https://go.semgrep.dev/scan-in-1-minute-for-free
🏗 Semgrep provided a grant to make this course possible.



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Data analytics has been rapidly growing, with companies looking to generate insights and drive their business with the help of data. In this Data Analytics Full Course video, you will learn what data analytics is, why data analytics is necessary, the types of data analytics, and the various data analytics applications. You will then understand a case study and perform analysis of data using Python and R. In addition to that; we will see the top 10 data analysis tools and understand the difference between a data scientist and a data analyst. Finally, we’ll see the top interview questions that will help you crack a data analyst interview.

Dataset Link - https://drive.google.com/drive..../folders/1U8CF0Xx3Ni

00:02:09 Data Analytics for Beginners
00:03:01 What is Data Analytics
00:04:30 Steps involved in Data Analytics
00:06:25 Tools used in Data Analytics
00:10:00 Data analytics applications
00:16:35 companies using data analytics
00:17:15 case study
00:21:15 Who is a data analyst
00:21:53 Top 10 skills to become a Data analyst in 2022
00:28:54 Top 10 Analysis Tools
00:47:10 Data Analytics Using Phyton
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09:27:32 Data Analyst Interview Questions

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LangChain became immensely popular when it was launched in 2022, but how can it impact your development and application of AI models, Large Language Models (LLM) in particular. In this video Martin Keen shares an overview of the features and uses of LangChain.

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
This 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐓𝐮𝐭𝐨𝐫𝐢𝐚𝐥 is intended as a Crash Course on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 for Beginners. 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 has been growing in popularity exponentially. But, 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 is still not known to many people. In this video, I aim to show you the different ways in which you can use 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 for yourself.

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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.

n8n Tutorial for Beginners 2026: How to Build AI Agents
✅ self-host n8n and save tons of money with Hostinger: http://hostinger.com/youri10

In this video, I show you how to build your own AI agent in n8n from scratch, self-host it on Hostinger for unlimited executions, and automate tasks that normally waste hours every week. You’ll learn how to set up a VPS with one-click n8n installation, connect OpenAI models and memory, add real-world tools like Google Search, and turn the output into clean newsletters automatically sent to your inbox.

for inquiries: youri (at) mediaflow.group

📌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

00:00:00 Introduction
00:02:00 What is Generative AI?
00:15:29 Generative AI Examples
00:34:09 Generative AI Tools
00:55:33 What Is Artificial Intelligence?
01:06:15 Types Of Artificial Intelligence
01:16:30 What is Deep Learning
01:27:43 TensorFlow Explained
01:52:29 Convolutional Neural Network
02:13:05 Artificial Neural Network
02:44:56 Recurrent Neural Networks
03:13:50 Keras
03:38:59 What is LLM?
03:58:43 What Are GANs?
04:11:04 Transformers in Gen AI
04:18:43 Prompt Engineering Explained
04:32:28 Prompt Engineering for Code Generation
04:41:47 How to Become a Prompt Engineer?
04:46:51 Building a Chatbot with Prompt Engineering
05:03:01 GitHub Copilot
05:20:26 What is LangChain?
05:37:42 What is RAG?
06:00:34 Generate Images Using DC-GAN
06:25:08 Midjourney
06:43:30 OpenAI API using Python
06:51:44 Generative AI in Marketing
07:02:14 The Future of Generative AI and Job Opportunities
07:07:58 Nvidia's Latest Breakthrough in Generative AI
07:14:36 DeepSeek vs OpenAI: Who Wins the AI Race?
07:27:09 Alibaba’s Qwen 2.5-Max Just Beat GPT-4 & DeepSeek?
07:31:32 DeepSeek Training Cost
07:37:01 Exploring the Ethics of Generative AI
07:44:31 What is Agentic AI?
07:54:30 Agentic AI vs Generative AI
08:12:31 Dangers of AI
08:35:17 Artificial Intelligence Project Ideas
08:48:54 Top 10 Benefits Of Artificial Intelligence
09:00:42 GenAI Roadmap
09:09:27 Top 5 Generative AI Career Opportunities
09:25:40 Generative AI Interview Questions

📌 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.

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📝Feel free to share your comments below.📝

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In this Python tutorial, We'll see how to create an AI Text Generation Solution with GPT-Neo from Eleuther AI.
We'll learn
1. About GPT-Neo
2. How to install the latest Hugging Face Transformers Package
3. Load Text Generation pipeline and Download Pre-trained GPT-Neo Models
4. Text Generation

Eleuther AI - https://www.eleuther.ai/
GPT-Neo on Hugging Face Model Hub - https://huggingface.co/EleutherAI/gpt-neo-1.3B
GPT-Neo - https://github.com/EleutherAI/gpt-neo
GPU Focused GPT-NeoX - https://github.com/EleutherAI/gpt-neox/
Colab Code - https://colab.research.google.....com/drive/1UByjdT5l_

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Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

An introduction to support vector machines (SVMs) that requires very little math (no calculus or linear algebra), only a visual mind.
This is the third of a series of three videos.
- Linear Regression: https://www.youtube.com/watch?v=wYPUhge9w5c
- Logistic Regression: https://www.youtube.com/watch?v=jbluHIgBmBo

0:00 Introduction
1:42 Classification goal: split data
3:14 Perceptron algorithm
6:00 Split data - separate lines
7:05 How to separate lines?
12:01 Expanding rate
18:19 Perceptron Error
19:26 SVM Classification Error
20:34 Margin Error
25:13 Challenge - Gradient Descent
27:25 Which line is better?
28:24 The C parameter
30:16 Series of 3 videos
30:30 Thank you!