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This repository collects everything you need to use AI and LLM in your projects.
120+ libraries, organized by development stages:
โ Model training, fine-tuning, and evaluation
โ Deploying applications with LLM and RAG
โ Fast and scalable model launch
โ Data extraction, crawlers, and scrapers
โ Creating autonomous LLM agents
โ Prompt optimization and security
Repo: https://github.com/KalyanKS-NLP/llm-engineer-toolkit
๐ฅบ https://t.me/DataAnalyticsX
120+ libraries, organized by development stages:
โ Model training, fine-tuning, and evaluation
โ Deploying applications with LLM and RAG
โ Fast and scalable model launch
โ Data extraction, crawlers, and scrapers
โ Creating autonomous LLM agents
โ Prompt optimization and security
Repo: https://github.com/KalyanKS-NLP/llm-engineer-toolkit
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This channels is for Programmers, Coders, Software Engineers.
0๏ธโฃ Python
1๏ธโฃ Data Science
2๏ธโฃ Machine Learning
3๏ธโฃ Data Visualization
4๏ธโฃ Artificial Intelligence
5๏ธโฃ Data Analysis
6๏ธโฃ Statistics
7๏ธโฃ Deep Learning
8๏ธโฃ programming Languages
โ
https://t.me/addlist/8_rRW2scgfRhOTc0
โ
https://t.me/Codeprogrammer
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Forwarded from Machine Learning with Python
These Google Colab-notebooks help to implement all machine learning algorithms from scratch ๐คฏ
Repo: https://udlbook.github.io/udlbook/
๐ @codeprogrammer
Repo: https://udlbook.github.io/udlbook/
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Ant AI Automated Sales Robot is an intelligent robot focused on automating lead generation and sales conversion. Its core function simulates human conversation, achieving end-to-end business conversion and easily generating revenue without requiring significant time investment.
I. Core Functions: Fully Automated "Lead Generation - Interaction - Conversion"
Precise Lead Generation and Human-like Communication: Ant AI is trained on over 20 million real social chat records, enabling it to autonomously identify target customers and build trust through natural conversation, requiring no human intervention.
High Conversion Rate Across Multiple Scenarios: Ant AI intelligently recommends high-conversion-rate products based on chat content, guiding customers to complete purchases through platforms such as iFood, Shopee, and Amazon. It also supports other transaction scenarios such as movie ticket purchases and utility bill payments.
24/7 Operation: Ant AI continuously searches for customers and recommends products. You only need to monitor progress via your mobile phone, requiring no additional management time.
II. Your Profit Guarantee: Low Risk, High Transparency, Zero Inventory Pressure, Stable Commission Sharing
We have established partnerships with platforms such as Shopee and Amazon, which directly provide abundant product sourcing. You don't need to worry about inventory or logistics. After each successful order, the company will charge the merchant a commission and share all profits with you. Earnings are predictable and withdrawals are convenient. Member data shows that each bot can generate $30 to $100 in profit per day. Commission income can be withdrawn to your account at any time, and the settlement process is transparent and open.
Low Initial Investment Risk. Bot development and testing incur significant costs. While rental fees are required, in the early stages of the project, the company prioritizes market expansion and brand awareness over short-term profits.
If you are interested, please join my Telegram group for more information and leave a message: https://t.me/+lVKtdaI5vcQ1ZDA1
I. Core Functions: Fully Automated "Lead Generation - Interaction - Conversion"
Precise Lead Generation and Human-like Communication: Ant AI is trained on over 20 million real social chat records, enabling it to autonomously identify target customers and build trust through natural conversation, requiring no human intervention.
High Conversion Rate Across Multiple Scenarios: Ant AI intelligently recommends high-conversion-rate products based on chat content, guiding customers to complete purchases through platforms such as iFood, Shopee, and Amazon. It also supports other transaction scenarios such as movie ticket purchases and utility bill payments.
24/7 Operation: Ant AI continuously searches for customers and recommends products. You only need to monitor progress via your mobile phone, requiring no additional management time.
II. Your Profit Guarantee: Low Risk, High Transparency, Zero Inventory Pressure, Stable Commission Sharing
We have established partnerships with platforms such as Shopee and Amazon, which directly provide abundant product sourcing. You don't need to worry about inventory or logistics. After each successful order, the company will charge the merchant a commission and share all profits with you. Earnings are predictable and withdrawals are convenient. Member data shows that each bot can generate $30 to $100 in profit per day. Commission income can be withdrawn to your account at any time, and the settlement process is transparent and open.
Low Initial Investment Risk. Bot development and testing incur significant costs. While rental fees are required, in the early stages of the project, the company prioritizes market expansion and brand awareness over short-term profits.
If you are interested, please join my Telegram group for more information and leave a message: https://t.me/+lVKtdaI5vcQ1ZDA1
โค7
Forwarded from Machine Learning with Python
Do you see yourself as a programmer, researcher, or engineer?
Anonymous Poll
44%
Programmer
23%
Researcher
33%
Engineer
Forwarded from Machine Learning with Python
by [@codeprogrammer]
---
๐๏ธ MIT OpenCourseWare โ Machine Learning
---
#MachineLearning #LearnML #DataScience #AI
https://t.me/CodeProgrammer
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Google for Developers
Machine Learning | Google for Developers
โค4๐ฅ1
Basic Machine Learning Algorithms
1. Linear Regression (linear regression)
Predicts a number based on a linear relationship (example: apartment price).
2. Logistic Regression (logistic regression)
Classification, usually 0/1 (spam/not spam), outputs a probability.
3. Decision Tree (decision tree)
"If-then" rules, easy to explain but prone to overfitting.
4. SVM (support vector machine)
Seeks the boundary between classes with the maximum margin; works well on medium-sized data.
5. KNN (k-nearest neighbors)
Looks at the nearest points and votes; simple but slows down on large datasets.
6. Dimensionality Reduction (dimensionality reduction, often PCA/UMAP/t-SNE)
Compresses features to simplify data/visualization/remove noise.
7. Random Forest (random forest)
Many trees + averaging/voting; often a strong out-of-the-box solution.
8. K-means
Unsupervised clustering: divides points into k groups.
9. Naive Bayes (naive Bayes)
A fast probabilistic classifier, often good for text.
๐ @DataAnalyticsX
1. Linear Regression (linear regression)
Predicts a number based on a linear relationship (example: apartment price).
2. Logistic Regression (logistic regression)
Classification, usually 0/1 (spam/not spam), outputs a probability.
3. Decision Tree (decision tree)
"If-then" rules, easy to explain but prone to overfitting.
4. SVM (support vector machine)
Seeks the boundary between classes with the maximum margin; works well on medium-sized data.
5. KNN (k-nearest neighbors)
Looks at the nearest points and votes; simple but slows down on large datasets.
6. Dimensionality Reduction (dimensionality reduction, often PCA/UMAP/t-SNE)
Compresses features to simplify data/visualization/remove noise.
7. Random Forest (random forest)
Many trees + averaging/voting; often a strong out-of-the-box solution.
8. K-means
Unsupervised clustering: divides points into k groups.
9. Naive Bayes (naive Bayes)
A fast probabilistic classifier, often good for text.
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๐ฆ๐ค๐ ๐๐ฟ๐ผ๐บ ๐๐ฎ๐๐ถ๐ฐ๐ ๐๐ผ ๐๐ฑ๐๐ฎ๐ป๐ฐ๐ฒ๐ฑ: This PDF-file contains SQL from beginner to advanced level.
You will need this 101-page PDF file to prepare and review SQL before any data-related interview.
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๐ @DataAnalyticsX
You will need this 101-page PDF file to prepare and review SQL before any data-related interview.
https://drive.google.com/file/d/1N2uPi4hkdCLYPgBa5UfjFT4koqMbGUHz/view
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This channels is for Programmers, Coders, Software Engineers.
0๏ธโฃ Python
1๏ธโฃ Data Science
2๏ธโฃ Machine Learning
3๏ธโฃ Data Visualization
4๏ธโฃ Artificial Intelligence
5๏ธโฃ Data Analysis
6๏ธโฃ Statistics
7๏ธโฃ Deep Learning
8๏ธโฃ programming Languages
โ
https://t.me/addlist/8_rRW2scgfRhOTc0
โ
https://t.me/Codeprogrammer
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โค3
Forwarded from Data Science Jupyter Notebooks
Here: GitHub repository to learn AI Engineering.
It contains some of the best free courses, articles, tutorials, and videos on the following topics:
Mathematical foundation
Basics of AI and #ML
Deep Learning and specializations
Generative #AI
Large language models (#LLM)
Guides on #promptengineering
#RAG, #agents, and #MCP
See here: https://github.com/ashishps1/learn-ai-engineering
๐ @CODEPROGRAMMER
It contains some of the best free courses, articles, tutorials, and videos on the following topics:
Mathematical foundation
Basics of AI and #ML
Deep Learning and specializations
Generative #AI
Large language models (#LLM)
Guides on #promptengineering
#RAG, #agents, and #MCP
See here: https://github.com/ashishps1/learn-ai-engineering
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GitHub
GitHub - ashishps1/learn-ai-engineering: Learn AI and LLMs from scratch using free resources
Learn AI and LLMs from scratch using free resources - ashishps1/learn-ai-engineering
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Numpy_Cheat_Sheet.pdf
4.8 MB
NumPy Cheat Sheet: Data Analysis in Python
This #Python cheat sheet is a quick reference for #NumPy beginners.
Learn more:
https://www.datacamp.com/cheat-sheet/numpy-cheat-sheet-data-analysis-in-python
https://t.me/DataAnalyticsX
This #Python cheat sheet is a quick reference for #NumPy beginners.
Learn more:
https://www.datacamp.com/cheat-sheet/numpy-cheat-sheet-data-analysis-in-python
https://t.me/DataAnalyticsX
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