Generative AI
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โœ… Welcome to Generative AI
๐Ÿ‘จโ€๐Ÿ’ป Join us to understand and use the tech
๐Ÿ‘ฉโ€๐Ÿ’ป Learn how to use Open AI & Chatgpt
๐Ÿค– The REAL No.1 AI Community

Admin: @coderfun
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โค3
Forwarded from Artificial Intelligence
๐Ÿฏ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—ฆ๐—ค๐—Ÿ ๐—ฌ๐—ผ๐˜‚๐—ง๐˜‚๐—ฏ๐—ฒ ๐—ฃ๐—น๐—ฎ๐˜†๐—น๐—ถ๐˜€๐˜๐˜€ ๐—ง๐—ต๐—ฎ๐˜ ๐—ช๐—ถ๐—น๐—น ๐— ๐—ฎ๐—ธ๐—ฒ ๐—ฌ๐—ผ๐˜‚ ๐—ฎ ๐—ค๐˜‚๐—ฒ๐—ฟ๐˜† ๐—ฃ๐—ฟ๐—ผ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ๐Ÿ˜

Still stuck Googling โ€œWhat is SQL?โ€ every time you start a new project?๐Ÿ’ต

Youโ€™re not alone. Many beginners bounce between tutorials without ever feeling confident writing SQL queries on their own.๐Ÿ‘จโ€๐Ÿ’ปโœจ๏ธ

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โค1
Generative AI Mindmap
โค2
๐ŸŽ“๐Ÿฑ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ง๐—ผ ๐—•๐—ผ๐—ผ๐˜€๐˜ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ง๐—ฒ๐—ฐ๐—ต ๐—–๐—ฎ๐—ฟ๐—ฒ๐—ฒ๐—ฟ! ๐Ÿš€

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โค1๐Ÿ‘1
Will LLMs always hallucinate?

As large language models (LLMs) become more powerful and pervasive, it's crucial that we understand their limitations.

A new paper argues that hallucinations - where the model generates false or nonsensical information - are not just occasional mistakes, but an inherent property of these systems.

While the idea of hallucinations as features isn't new, the researchers' explanation is.

They draw on computational theory and Gรถdel's incompleteness theorems to show that hallucinations are baked into the very structure of LLMs.

In essence, they argue that the process of training and using these models involves undecidable problems - meaning there will always be some inputs that cause the model to go off the rails.

This would have big implications. It suggests that no amount of architectural tweaks, data cleaning, or fact-checking can fully eliminate hallucinations.

So what does this mean in practice? For one, it highlights the importance of using LLMs carefully, with an understanding of their limitations.

It also suggests that research into making models more robust and understanding their failure modes is crucial.

No matter how impressive the results, LLMs are not oracles - they're tools with inherent flaws and biases

LLM & Generative AI Resources: https://t.me/generativeai_gpt
โค4
Forwarded from Artificial Intelligence
๐Ÿฒ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐˜๐—ผ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป ๐˜๐—ต๐—ฒ ๐— ๐—ผ๐˜€๐˜ ๐—œ๐—ป-๐——๐—ฒ๐—บ๐—ฎ๐—ป๐—ฑ ๐—ง๐—ฒ๐—ฐ๐—ต ๐—ฆ๐—ธ๐—ถ๐—น๐—น๐˜€๐Ÿ˜

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โค1
Forwarded from Artificial Intelligence
๐Ÿš€๐—ง๐—ผ๐—ฝ ๐Ÿฏ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—š๐—ผ๐—ผ๐—ด๐—น๐—ฒ-๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฒ๐—ฑ ๐—ฃ๐˜†๐˜๐—ต๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ๐Ÿ˜

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Here are some project ideas for a data science and machine learning project focused on generating AI:

1. Natural Language Generation (NLG) Model: Build a model that generates human-like text based on input data. This could be used for creating product descriptions, news articles, or personalized recommendations.

2. Code Generation Model: Develop a model that generates code snippets based on a given task or problem statement. This could help automate software development tasks or assist programmers in writing code more efficiently.

3. Image Captioning Model: Create a model that generates captions for images, describing the content of the image in natural language. This could be useful for visually impaired individuals or for enhancing image search capabilities.

4. Music Generation Model: Build a model that generates music compositions based on input data, such as existing songs or musical patterns. This could be used for creating background music for videos or games.

5. Video Synthesis Model: Develop a model that generates realistic video sequences based on input data, such as a series of images or a textual description. This could be used for generating synthetic training data for computer vision models.

6. Chatbot Generation Model: Create a model that generates conversational agents or chatbots based on input data, such as dialogue datasets or user interactions. This could be used for customer service automation or virtual assistants.

7. Art Generation Model: Build a model that generates artistic images or paintings based on input data, such as art styles, color palettes, or themes. This could be used for creating unique digital artwork or personalized designs.

8. Story Generation Model: Develop a model that generates fictional stories or narratives based on input data, such as plot outlines, character descriptions, or genre preferences. This could be used for creative writing prompts or interactive storytelling applications.

9. Recipe Generation Model: Create a model that generates new recipes based on input data, such as ingredient lists, dietary restrictions, or cuisine preferences. This could be used for meal planning or culinary inspiration.

10. Financial Report Generation Model: Build a model that generates financial reports or summaries based on input data, such as company financial statements, market trends, or investment portfolios. This could be used for automated financial analysis or decision-making support.

Any project which sounds interesting to you?
โค4
Forwarded from Artificial Intelligence
๐—™๐—ฅ๐—˜๐—˜ ๐—ง๐—”๐—ง๐—” ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—ฉ๐—ถ๐—ฟ๐˜๐˜‚๐—ฎ๐—น ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐—ป๐˜€๐—ต๐—ถ๐—ฝ ๐—ณ๐—ผ๐—ฟ ๐—•๐—ฒ๐—ด๐—ถ๐—ป๐—ป๐—ฒ๐—ฟ๐˜€ (๐—ช๐—ถ๐˜๐—ต ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ฒ)๐Ÿ˜

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โค1
Best YouTube Playlists for Data Science

โ–ถ๏ธ Python
๐Ÿ”— Playlist Link

โ–ถ๏ธ SQL
๐Ÿ”— Playlist Link

โ–ถ๏ธ Data Analysis
๐Ÿ”— Playlist Link

โ–ถ๏ธ Data Analyst
๐Ÿ”— Playlist Link

โ–ถ๏ธ Linear Algebra
๐Ÿ”— Playlist Link

โ–ถ๏ธ Calculus
๐Ÿ”— Playlist Link

โ–ถ๏ธ Statistics
๐Ÿ”— Playlist Link

โ–ถ๏ธ Machine Learning
๐Ÿ”— Playlist Link

โ–ถ๏ธ Deep Learning
๐Ÿ”— Playlist Link

โ–ถ๏ธ Excel Power Query
๐Ÿ”— Playlist Link

โ–ถ๏ธ Ruby
๐Ÿ”— Playlist Link

โ–ถ๏ธ Microsoft Excel
๐Ÿ”— Playlist Link
โค7
๐Ÿณ ๐— ๐˜‚๐˜€๐˜-๐—ž๐—ป๐—ผ๐˜„ ๐—ฆ๐—ค๐—Ÿ ๐—–๐—ผ๐—ป๐—ฐ๐—ฒ๐—ฝ๐˜๐˜€ ๐—˜๐˜ƒ๐—ฒ๐—ฟ๐˜† ๐—”๐˜€๐—ฝ๐—ถ๐—ฟ๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜€๐˜ ๐—ฆ๐—ต๐—ผ๐˜‚๐—น๐—ฑ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ๐Ÿ˜

If youโ€™re serious about becoming a data analyst, thereโ€™s no skipping SQL. Itโ€™s not just another technical skill โ€” itโ€™s the core language for data analytics.๐Ÿ“Š

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/44S3Xi5

This guide covers 7 key SQL concepts that every beginner must learnโœ…๏ธ
โค2
๐Ÿ“Š Data Science Project Ideas to Practice & Master Your Skills โœ…

๐ŸŸข Beginner Level
โ€ข Titanic Survival Prediction (Logistic Regression)
โ€ข House Price Prediction (Linear Regression)
โ€ข Exploratory Data Analysis on IPL or Netflix Dataset
โ€ข Customer Segmentation (K-Means Clustering)
โ€ข Weather Data Visualization

๐ŸŸก Intermediate Level
โ€ข Sentiment Analysis on Tweets
โ€ข Credit Card Fraud Detection
โ€ข Time Series Forecasting (Stock or Sales Data)
โ€ข Image Classification using CNN (Fashion MNIST)
โ€ข Recommendation System for Movies/Products

๐Ÿ”ด Advanced Level
โ€ข End-to-End Machine Learning Pipeline with Deployment
โ€ข NLP Chatbot using Transformers
โ€ข Real-Time Dashboard with Streamlit + ML
โ€ข Anomaly Detection in Network Traffic
โ€ข A/B Testing & Business Decision Modeling

๐Ÿ’ฌ Double Tap โค๏ธ for more! ๐Ÿค–๐Ÿ“ˆ
โค5