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 I Streamline My Research and Presentation with LlamaIndex Workflows

🗂 Category: MACHINE LEARNING

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

An example of orchestrating AI workflow with robustness, flexibility and controllability
📌 How to Create a Powerful AI Email Search for Gmail with RAG

🗂 Category:

🕒 Date: 2024-09-10 | ⏱️ Read time: 17 min read

Learn how you can develop an application to search emails using RAG
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📌 To Care, or Not to Care: Using XmR Charts to Differentiate Signals from Noise in Metrics

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-10 | ⏱️ Read time: 12 min read

A Step-by-Step Guide to Creating and Interpreting XmR Charts for Effective Data Analysis
📌 How Tiny Neural Networks Represent Basic Functions

🗂 Category: MACHINE LEARNING

🕒 Date: 2024-09-10 | ⏱️ Read time: 9 min read

A gentle introduction to mechanistic interpretability through simple algorithmic examples
📌 Introducing NumPy, Part 1: Understanding Arrays

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-10 | ⏱️ Read time: 22 min read

Creating, describing, and accessing attributes
📌 Automating Research Workflows with LLMs

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-09-10 | ⏱️ Read time: 14 min read

Augmenting researchers with atomic usage of AI
📌 Linear Programming Optimization: The Simplex Method

🗂 Category: STATISTICS

🕒 Date: 2024-09-10 | ⏱️ Read time: 15 min read

Part 3: The algorithm under the hood
📌 Open-Source Data Observability with Elementary - From Zero to Hero (Part 2)

🗂 Category:

🕒 Date: 2024-09-10 | ⏱️ Read time: 7 min read

The guide to take your dbt tests to the next level for free
📌 Open-Source Data Observability with Elementary – From Zero to Hero (Part 1)

🗂 Category: DATA ENGINEERING

🕒 Date: 2024-09-10 | ⏱️ Read time: 7 min read

A step-by-step hands-on guide I wish I had when I was a beginner
📌 Logistic Regression, Explained: A Visual Guide with Code Examples for Beginners

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-10 | ⏱️ Read time: 9 min read

Finding the perfect weights to fit the data in
📌 Practical Introduction to Polars

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-10 | ⏱️ Read time: 13 min read

Hands-on guide with side-by-side examples in Pandas
📌 The Art of Asking Questions for Engineers

🗂 Category: BUSINESS

🕒 Date: 2024-09-10 | ⏱️ Read time: 6 min read

A Guideline for Asking Impactful Questions
📌 Key Insights for Teaching AI Agents to Remember

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-09-10 | ⏱️ Read time: 20 min read

Recommendations on building robust memory capabilities based on experimentation with Autogen’s “Teachable Agents”
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📌 Introducing NumPy, Part 3: Manipulating Arrays

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-15 | ⏱️ Read time: 7 min read

Shaping, transposing, joining, and splitting arrays
📌 Build a Data Dashboard Using HTML, CSS, and JavaScript

🗂 Category: PROGRAMMING

🕒 Date: 2025-10-03 | ⏱️ Read time: 14 min read

A framework-free guide for Python programmers
📌 MobileNetV2 Paper Walkthrough: The Smarter Tiny Giant

🗂 Category: DEEP LEARNING

🕒 Date: 2025-10-03 | ⏱️ Read time: 28 min read

Understanding and implementing MobileNetV2 with PyTorch  — the next generation of MobileNetV1
📌 Is Multi-Collinearity Destroying Your Causal Inferences In Marketing Mix Modelling?

🗂 Category: DATA SCIENCE

🕒 Date: 2024-09-10 | ⏱️ Read time: 18 min read

Causal AI, exploring the integration of causal reasoning into machine learning
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📌 Does Semi-Supervised Learning Help to Train Better Models?

🗂 Category: MACHINE LEARNING

🕒 Date: 2024-09-09 | ⏱️ Read time: 8 min read

Evaluating how semi-supervised learning can leverage unlabeled data
📌 Benchmarking Hallucination Detection Methods in RAG

🗂 Category: LARGE LANGUAGE MODELS

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

Evaluating methods to enhance reliability in LLM-generated responses.
📌 Automate Video Chaptering with LLMs and TF-IDF

🗂 Category: LARGE LANGUAGE MODELS

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

Transform raw trannoscripts into well-structured documents