Machine Learning – Telegram
Machine Learning
39.2K subscribers
3.85K photos
32 videos
42 files
1.31K links
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
Download Telegram
📌 Climate Change in the Countryside

🗂 Category: CLIMATE CHANGE

🕒 Date: 2024-08-28 | ⏱️ Read time: 13 min read

A Python project for climate warriors
📌 Enforcing JSON outputs in commercial LLMs

🗂 Category:

🕒 Date: 2024-08-28 | ⏱️ Read time: 11 min read

A comprehensive guide
1
📌 How AI Could Soon Take Human-Computer Interaction to New Levels

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-08-28 | ⏱️ Read time: 22 min read

As AI models reach excellence in speech recognition and synthesis, text processing, and multimodalism, the…
1
📌 Beating Connect Four with AI

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-08-28 | ⏱️ Read time: 9 min read

A Simple Approach Using Monte Carlo Simulations
1
📌 Analytics Frameworks Every Data Scientist Should Know

🗂 Category: DATA SCIENCE

🕒 Date: 2024-08-28 | ⏱️ Read time: 12 min read

Why I believe my experience at McKinsey made me a better data scientist
📌 Need for Speed: Streamlit vs Functool Caching

🗂 Category: DATA SCIENCE

🕒 Date: 2024-08-28 | ⏱️ Read time: 14 min read

Comparing the performance of streamlit and functools caching for pandas and polars. The results will…
2
📌 Boosting LLM Inference Speed Using Speculative Decoding

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-08-27 | ⏱️ Read time: 7 min read

A practical guide on using cutting-edge optimization techniques to speed up inference
📌 Building a Robust Data Observability Framework to Ensure Data Quality and Integrity

🗂 Category:

🕒 Date: 2024-08-27 | ⏱️ Read time: 9 min read

How can we improve observability with open-source tools?
📌 The MMD-Critic Method, Explained

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-08-27 | ⏱️ Read time: 12 min read

A powerful yet under-the-radar method for data summarization and explainable AI
📌 Building a Command-Line Quiz Application in R

🗂 Category: DATA SCIENCE

🕒 Date: 2025-10-05 | ⏱️ Read time: 6 min read

Practice control flow, input handling, and functions in R by creating an interactive quiz game.
2
📌 Missing Value Imputation, Explained: A Visual Guide with Code Examples for Beginners

🗂 Category: MACHINE LEARNING

🕒 Date: 2024-08-27 | ⏱️ Read time: 13 min read

One (tiny) dataset, six imputation methods?
📌 When AI Artists Compete:

🗂 Category: ART

🕒 Date: 2024-08-27 | ⏱️ Read time: 10 min read

Insights from My Generative Art Experiment
📌 A Machine Learning Mobius: Can Models Learn from Each Other?

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-08-27 | ⏱️ Read time: 18 min read

Novel twists in synthetic data and learning paradigms
📌 How to Effectively Detect Objects with Meta’s Image Segmentation Model: SAM 2

🗂 Category: MACHINE LEARNING

🕒 Date: 2024-08-27 | ⏱️ Read time: 12 min read

Learn how to utilize Meta’s new SAM 2 model to segment anything
📌 How to Color Polars DataFrame

🗂 Category: DATA SCIENCE

🕒 Date: 2024-08-27 | ⏱️ Read time: 6 min read

Continue working with the Polars library while being able to color and style the table
📌 Exploring the Strategic Capabilities of LLMs in a Risk Game Setting

🗂 Category: DATA SCIENCE

🕒 Date: 2024-08-27 | ⏱️ Read time: 39 min read

In a simulated Risk environment, large language models from Anthropic, OpenAI, and Meta showcase distinct…
📌 AWS DeepRacer : A Practical Guide to Reducing The Sim2Real Gap – Part 2 || Training Guide

🗂 Category: ROBOTICS

🕒 Date: 2024-08-26 | ⏱️ Read time: 13 min read

This article describes how to train the AWS DeepRacer to drive safely around a track…
📌 No Baseline? No Benchmarks? No Biggie! An Experimental Approach to Agile Chatbot Development

🗂 Category: INNOVATION

🕒 Date: 2024-08-26 | ⏱️ Read time: 15 min read

Lessons learned bringing LLM-based products to production
📌 How to Achieve Near Human-Level Performance in Chunking for RAGs

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-08-26 | ⏱️ Read time: 10 min read

The costly yet powerful splitting technique for superior RAG retrieval
📌 How Can We Continually Adapt Vision-Language Models?

🗂 Category:

🕒 Date: 2024-08-26 | ⏱️ Read time: 9 min read

Exploring Continual Learning Strategies for CLIP.
📌 Introducing Markov Decision Processes, Setting up Gymnasium Environments and Solving them via Dynamic Programming Methods

🗂 Category: MACHINE LEARNING

🕒 Date: 2024-08-26 | ⏱️ Read time: 12 min read

Dissecting “Reinforcement Learning” by Richard S. Sutton with custom Python implementations, Episode II