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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πŸ“Œ The Great Data Closure: Why Databricks and Snowflake Are Hitting Their Ceiling

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2026-01-16 | ⏱️ Read time: 13 min read

Acquisitions, venture, and an increasingly competitive landscape all point to a market ceiling

#DataScience #AI #Python
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πŸ€– Machine Learning Tutorials Repository

1. Python
2
. Computer Vision: Techniques, algorithms
3
. NLP
4.
Matplotlib
5. NumPy
6. Pandas
7.
MLOps
8. LLMs
9.
PyTorch/TensorFlow

git clone https://github.com/patchy631/machine-learning

πŸ”— GitHub: https://github.com/patchy631/machine-learning/tree/main

⭐️ https://t.iss.one/DataScienceT
πŸ“Œ Data Poisoning in Machine Learning: Why and How People Manipulate Training Data

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2026-01-17 | ⏱️ Read time: 14 min read

Do you know where your data has been?

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πŸ“Œ A Geometric Method to Spot Hallucinations Without an LLM Judge

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2026-01-17 | ⏱️ Read time: 7 min read

Imagine a flock of birds in flight. There’s no leader. No central command. Each bird…

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Best GitHub repositories to learn AI from scratch in 2026:


1. Andrej Karpathy
https://github.com/karpathy/nn-zero-to-hero

2. Hugging Face Transformers
https://github.com/huggingface/transformers

3. FastAI/fastbook
https://github.com/fastai/fastbook

4. Made-With-ML
https://github.com/GokuMohandas/Made-With-ML

5. ML System Design
https://github.com/chiphuyen/machine-learning-systems-design

6. Awesome Generative AI guide
https://github.com/aishwaryanr/awesome-generative-ai-guide

7. Dive into Deep Learning
https://github.com/d2l-ai/d2l-en

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πŸ“Œ The Hidden Opportunity in AI Workflow Automation with n8n for Low-Tech Companies

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2026-01-18 | ⏱️ Read time: 14 min read

How to use n8n with multimodal AI and optimisation tools to help companies with low…

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πŸ“Œ Why Healthcare Leads in Knowledge Graphs

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2026-01-18 | ⏱️ Read time: 9 min read

How science, regulation, collaboration, and public funding shaped the world’s most mature semantic infrastructure

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πŸ“Œ Bridging the Gap Between Research and Readability with Marco Hening Tallarico

πŸ—‚ Category: AUTHOR SPOTLIGHTS

πŸ•’ Date: 2026-01-19 | ⏱️ Read time: 6 min read

Diluting complex research, spotting silent data leaks, and why the best way to learn is…

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πŸ“Œ Using Local LLMs to Discover High-Performance Algorithms

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2026-01-19 | ⏱️ Read time: 10 min read

How I used open-source models to explore new frontiers in efficient code generation, using my…

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πŸ“Œ Time Series Isn’t Enough: How Graph Neural Networks Change Demand Forecasting

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2026-01-19 | ⏱️ Read time: 11 min read

Why modeling SKUs as a network reveals what traditional forecasts miss

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πŸ“Œ You Probably Don’t Need a Vector Database for Your RAG β€” Yet

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2026-01-20 | ⏱️ Read time: 14 min read

Numpy or SciKit-Learn might meet all your retrieval needs

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πŸ“Œ Why Package Installs Are Slow (And How to Fix It)

πŸ—‚ Category: DATA ENGINEERING

πŸ•’ Date: 2026-01-20 | ⏱️ Read time: 7 min read

How sharded indexing patterns solve a scaling problem in package management

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