Machine Learning – Telegram
Machine Learning
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Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.

Admin: @HusseinSheikho || @Hussein_Sheikho
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📌 How to Do Evals on a Bloated RAG Pipeline

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2025-12-21 | ⏱️ Read time: 71 min read

Comparing metrics across datasets and models

#DataScience #AI #Python
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🚀 Master Data Science & Programming!

Unlock your potential with this curated list of Telegram channels. Whether you need books, datasets, interview prep, or project ideas, we have the perfect resource for you. Join the community today!


🔰 Machine Learning with Python
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
https://news.1rj.ru/str/CodeProgrammer

🔖 Machine Learning
Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.
https://news.1rj.ru/str/DataScienceM

🧠 Code With Python
This channel delivers clear, practical content for developers, covering Python, Django, Data Structures, Algorithms, and DSA – perfect for learning, coding, and mastering key programming skills.
https://news.1rj.ru/str/DataScience4

🎯 PyData Careers | Quiz
Python Data Science jobs, interview tips, and career insights for aspiring professionals.
https://news.1rj.ru/str/DataScienceQ

💾 Kaggle Data Hub
Your go-to hub for Kaggle datasets – explore, analyze, and leverage data for Machine Learning and Data Science projects.
https://news.1rj.ru/str/datasets1

🧑‍🎓 Udemy Coupons | Courses
The first channel in Telegram that offers free Udemy coupons
https://news.1rj.ru/str/DataScienceC

😀 ML Research Hub
Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.
https://news.1rj.ru/str/DataScienceT

💬 Data Science Chat
An active community group for discussing data challenges and networking with peers.
https://news.1rj.ru/str/DataScience9

🐍 Python Arab| بايثون عربي
The largest Arabic-speaking group for Python developers to share knowledge and help.
https://news.1rj.ru/str/PythonArab

🖊 Data Science Jupyter Notebooks
Explore the world of Data Science through Jupyter Notebooks—insights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post.
https://news.1rj.ru/str/DataScienceN

📺 Free Online Courses | Videos
Free online courses covering data science, machine learning, analytics, programming, and essential skills for learners.
https://news.1rj.ru/str/DataScienceV

📈 Data Analytics
Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making.
https://news.1rj.ru/str/DataAnalyticsX

🎧 Learn Python Hub
Master Python with step-by-step courses – from basics to advanced projects and practical applications.
https://news.1rj.ru/str/Python53

⭐️ Research Papers
Professional Academic Writing & Simulation Services
https://news.1rj.ru/str/DataScienceY

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Admin: @HusseinSheikho
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📌 The Geometry of Laziness: What Angles Reveal About AI Hallucinations

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2025-12-22 | ⏱️ Read time: 12 min read

A story about failing forward, spheres you can’t visualize, and why sometimes the math knows…

#DataScience #AI #Python
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📌 Understanding Vibe Proving

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2025-12-22 | ⏱️ Read time: 18 min read

How to make LLMs reason with verifiable, step-by-step logic (Part 1)

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📌 The Machine Learning “Advent Calendar” Day 22: Embeddings in Excel

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-22 | ⏱️ Read time: 8 min read

Understanding text embeddings through simple models and Excel

#DataScience #AI #Python
📌 Synergy in Clicks: Harsanyi Dividends for E-Commerce

🗂 Category: DATA SCIENCE

🕒 Date: 2025-12-23 | ⏱️ Read time: 19 min read

A brief overview of the math behind the Harsanyi Dividend and a real-world application in…

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📌 The Machine Learning “Advent Calendar” Day 21: Gradient Boosted Decision Tree Regressor in Excel

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-22 | ⏱️ Read time: 10 min read

Gradient descent in function space with decision trees

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📌 The Machine Learning “Advent Calendar” Day 20: Gradient Boosted Linear Regression in Excel

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-22 | ⏱️ Read time: 10 min read

From Random Ensembles to Optimization: Gradient Boosting Explained

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📌 ChatLLM Presents a Streamlined Solution to Addressing the Real Bottleneck in AI

🗂 Category: SPONSORED CONTENT

🕒 Date: 2025-12-22 | ⏱️ Read time: 8 min read

For the last couple of years, a lot of the conversation around AI has revolved…

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📌 The Machine Learning “Advent Calendar” Day 23: CNN in Excel

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-23 | ⏱️ Read time: 8 min read

A step-by-step 1D CNN for text, built in Excel, where every filter, weight, and decision…

#DataScience #AI #Python
📌 How Agents Plan Tasks with To-Do Lists

🗂 Category: AGENTIC AI

🕒 Date: 2025-12-23 | ⏱️ Read time: 7 min read

Understanding the process behind agentic planning and task management in LangChain

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📌 Stop Retraining Blindly: Use PSI to Build a Smarter Monitoring Pipeline

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-23 | ⏱️ Read time: 6 min read

A data scientist’s guide to population stability index (PSI)

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📌 The Machine Learning “Advent Calendar” Day 24: Transformers for Text in Excel

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-24 | ⏱️ Read time: 10 min read

An intuitive, step-by-step look at how Transformers use self-attention to turn static word embeddings into…

#DataScience #AI #Python
📌 Is Your Model Time-Blind? The Case for Cyclical Feature Encoding

🗂 Category: DATA SCIENCE

🕒 Date: 2025-12-24 | ⏱️ Read time: 7 min read

How cyclical encoding improves machine learning prediction

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📌 4 Techniques to Optimize AI Coding Efficiency

🗂 Category: PROGRAMMING

🕒 Date: 2025-12-24 | ⏱️ Read time: 8 min read

Learn how to code more effectively using AI

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📌 Bonferroni vs. Benjamini-Hochberg: Choosing Your P-Value Correction

🗂 Category: STATISTICS

🕒 Date: 2025-12-24 | ⏱️ Read time: 11 min read

Multiple hypothesis testing, P-values, and Monte Carlo

#DataScience #AI #Python
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📌 Keeping Probabilities Honest: The Jacobian Adjustment

🗂 Category: DATA SCIENCE

🕒 Date: 2025-12-25 | ⏱️ Read time: 10 min read

An intuitive explanation of transforming random variables correctly.

#DataScience #AI #Python
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📌 Why MAP and MRR Fail for Search Ranking (and What to Use Instead)

🗂 Category: DATA SCIENCE

🕒 Date: 2025-12-25 | ⏱️ Read time: 9 min read

MAP and MRR look intuitive, but they quietly break ranking evaluation. Here’s why these metrics…

#DataScience #AI #Python
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Forwarded from ML Research Hub
ML Engineers: NVIDIA has released a guide for beginners on fine-tuning LLMs using Unsloth.

The guide covers:

- training methods: LoRA, FFT, RL
- when and why to do fine-tuning, real use cases
- how much data and VRAM are required
- how to train locally on DGX Spark, RTX graphics cards, and more

Guide: https://blogs.nvidia.com/blog/rtx-ai-garage-fine-tuning-unsloth-dgx-spark/

👉 https://news.1rj.ru/str/DataScienceT
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