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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📌 The Machine Learning Lessons I’ve Learned This Month

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-09-30 | ⏱️ Read time: 7 min read

September 2025: library or self-made, Ditto and Launchbar, reading widely and deeply
📌 Proxy SHAP: Speed Up Explainability with Simpler Models

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-21 | ⏱️ Read time: 7 min read

A Practical Guide to Efficient SHAP Computation
📌 An Intuitive Guide to Integrate SQL and Python for Data Science

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-21 | ⏱️ Read time: 11 min read

Learn to master MySQL connector, a Python library that enables to interact with MYSQL database
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📌 A Basic Introduction to Quantum GANs

🗂 Category: MACHINE LEARNING

🕒 Date: 2024-09-21 | ⏱️ Read time: 11 min read

“Quantum computing just becomes vastly simpler once you take the physics out of it.”
📌 Reinforcement Learning, Part 8: Feature State Construction

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-09-21 | ⏱️ Read time: 17 min read

Enhancing linear methods by smartly incorporating state features into the learning objective
📌 Topic Modelling Your Personal Data

🗂 Category:

🕒 Date: 2024-09-21 | ⏱️ Read time: 29 min read

Using Traditional and Transformer Models to Explore Personal Data Stored by Brokers
📌 TimesFM: The Boom of Foundation Models in Time Series Forecasting

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-09-20 | ⏱️ Read time: 14 min read

Explore How Google’s Latest AI Model Delivers Zero-Shot Forecasting Accuracy Using Over 307 Billion Data…
📌 Paper Walkthrough: U-Net

🗂 Category: DEEP LEARNING

🕒 Date: 2024-09-20 | ⏱️ Read time: 16 min read

A PyTorch implementation on one of the most popular semantic segmentation models.
📌 Choosing Between LLM Agent Frameworks

🗂 Category:

🕒 Date: 2024-09-20 | ⏱️ Read time: 15 min read

Thanks to John Gilhuly for his contributions to this piece. Agents are having a moment.…
📌 Mastering t-SNE: A Comprehensive Guide to Understanding and Implementation in Python

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-20 | ⏱️ Read time: 26 min read

Unlock the power of t-SNE for visualizing high-dimensional data, with a step-by-step Python implementation and…
📌 Through the Uncanny Mirror: Do LLMs Remember Like the Human Mind?

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-09-19 | ⏱️ Read time: 10 min read

Exploring the Eerie Parallels and Profound Differences Between AI and Human Memory
📌 Improving Code Quality with Array and DataFrame Type Hints

🗂 Category:

🕒 Date: 2024-09-19 | ⏱️ Read time: 12 min read

How generic specification permits powerful static and runtime validation
📌 Shared Nearest Neighbors: A More Robust Distance Metric

🗂 Category:

🕒 Date: 2024-09-19 | ⏱️ Read time: 36 min read

A distance metric that can improve prediction, clustering, and outlier detection in datasets with many…
📌 AdEMAMix: A Deep Dive into a New Optimizer for Your Deep Neural Network

🗂 Category: MACHINE LEARNING

🕒 Date: 2024-09-19 | ⏱️ Read time: 15 min read

A better and faster option than the ADAM optimizer, from Apple Research
📌 The Evolution of Text to Video Models

🗂 Category: DEEP LEARNING

🕒 Date: 2024-09-19 | ⏱️ Read time: 10 min read

Simplifying the neural nets behind Generative Video Diffusion
📌 How to Build Your Own Roadmap for a Successful Data Science Career

🗂 Category: CAREER ADVICE

🕒 Date: 2024-09-19 | ⏱️ Read time: 4 min read

Our weekly selection of must-read Editors’ Picks and original features
📌 A Closer Look at Scipy’s Stats Module – Part 2

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-19 | ⏱️ Read time: 6 min read

Let’s learn the main methods from scipy.stats module in Python.
📌 A Closer Look at Scipy’s Stats module – Part 1

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-19 | ⏱️ Read time: 7 min read

Let’s learn the main methods from scipy.stats module in Python.
📌 Emerging Tech Is Nothing Without Methodology

🗂 Category: ANALYTICS

🕒 Date: 2024-09-19 | ⏱️ Read time: 6 min read

Or: a Hundred Ways to Solve a Complex Problem
📌 A Visual Exploration of Semantic Text Chunking

🗂 Category: NATURAL LANGUAGE PROCESSING

🕒 Date: 2024-09-19 | ⏱️ Read time: 22 min read

Use embeddings and visualization tools to split text into meaningful chunks
📌 Principal Component Analysis – Hands-On Tutorial

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-18 | ⏱️ Read time: 13 min read

Dimensionality reduction through Principal Component Analysis (PCA).