Machine Learning
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Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.

Admin: @HusseinSheikho || @Hussein_Sheikho
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Forwarded from Kaggle Data Hub
📊 Data Science Cheat Sheets

📦 596.3 MB | 👍 5.5K | ⬇️ 73.4K

📡 @DATASETS1
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📌 The Map of Meaning: How Embedding Models “Understand” Human Language

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-03-31 | ⏱️ Read time: 12 min read

Learn why embedding models are like a GPS for meaning. Instead of searching for exact…

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📌 How to Make Claude Code Better at One-Shotting Implementations

🗂 Category: LLM

🕒 Date: 2026-03-31 | ⏱️ Read time: 8 min read

Make your coding agent more efficient

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📌 The Inversion Error: Why Safe AGI Requires an Enactive Floor and State-Space Reversibility

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-04-01 | ⏱️ Read time: 29 min read

A systems design diagnosis of hallucination, corrigibility, and the structural gap that scaling cannot close

#DataScience #AI #Python
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📌 How Can A Model 10,000× Smaller Outsmart ChatGPT?

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-04-01 | ⏱️ Read time: 11 min read

Why thinking longer can matter more than being bigger

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📌 What Happens Now That AI is the First Analyst On Your Team?

🗂 Category: DATA ANALYSIS

🕒 Date: 2026-04-01 | ⏱️ Read time: 7 min read

How I am adapting in my career in the age of AI, automation, and when…

#DataScience #AI #Python
📌 How to Handle Classical Data in Quantum Models?

🗂 Category: QUANTUM COMPUTING

🕒 Date: 2026-04-02 | ⏱️ Read time: 11 min read

Workflows and encoding techniques in quantum machine learning

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📌 Quantum Simulations with Python

🗂 Category: QUANTUM COMPUTING

🕒 Date: 2026-04-02 | ⏱️ Read time: 5 min read

Run Quantum Experiments with Qiskit-Aer

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📌 Linear Regression Is Actually a Projection Problem (Part 2: From Projections to Predictions)

🗂 Category: DATA SCIENCE

🕒 Date: 2026-04-02 | ⏱️ Read time: 17 min read

The Vector View of Least Squares.

#DataScience #AI #Python
Forwarded from Learn Python Coding
This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

https://t.me/addlist/8_rRW2scgfRhOTc0

https://t.me/Codeprogrammer
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📌 DenseNet Paper Walkthrough: All Connected

🗂 Category: DEEP LEARNING

🕒 Date: 2026-04-03 | ⏱️ Read time: 20 min read

When we try to train a very deep neural network model, one issue that we…

#DataScience #AI #Python
📌 I Replaced Vector DBs with Google’s Memory Agent Pattern for my notes in Obsidian

🗂 Category: MACHINE LEARNING

🕒 Date: 2026-04-03 | ⏱️ Read time: 13 min read

Persistent AI memory without embeddings, Pinecone, or a PhD in similarity search.

#DataScience #AI #Python
Selection for those who want to become a certified Claude architect

Useful resources for preparation in one place 👇

Registration for certification: https://anthropic.skilljar.com/claude-certified-architect-foundations-access-request

Training (13 free courses):
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Cookbook (examples and practices):
https://github.com/anthropics/anthropic-cookbook

Exam guide:
https://share.google/0eqIbebzRMUt8KTc8

Practice questions:
http://claudecertifications.com

MCP documentation:
http://modelcontextprotocol.io

API documentation:
http://docs.anthropic.com

Useful playbook:
https://drive.google.com/file/d/1luC0rnrET4tDYtS7xe5jUxMDZA-4qNf-/view
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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.
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🔖 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.
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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.
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Your go-to hub for Kaggle datasets – explore, analyze, and leverage data for Machine Learning and Data Science projects.
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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.
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The largest Arabic-speaking group for Python developers to share knowledge and help.
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📌 Building a Python Workflow That Catches Bugs Before Production

🗂 Category: PROGRAMMING

🕒 Date: 2026-04-04 | ⏱️ Read time: 17 min read

Using modern tooling to identify defects earlier in the software lifecycle.

#DataScience #AI #Python
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📌 Building Robust Credit Scoring Models with Python

🗂 Category: DATA SCIENCE

🕒 Date: 2026-04-04 | ⏱️ Read time: 24 min read

A Practical Guide to Measuring Relationships between Variables for Feature Selection in a Credit Scoring.

#DataScience #AI #Python
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