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
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πŸ“Œ Bringing Structure to Your Data

πŸ—‚ Category:

πŸ•’ Date: 2024-10-14 | ⏱️ Read time: 13 min read

Testing assumptions with path models
πŸ“Œ How to Perform A/B Testing with Hypothesis Testing in Python: A Comprehensive Guide

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-10-13 | ⏱️ Read time: 11 min read

A Step-by-Step Guide to Making Data-Driven Decisions with Practical Python Examples
πŸ“Œ Recruiting vs. Interviewing for Data Roles in Diverse Markets

πŸ—‚ Category: CAREER ADVICE

πŸ•’ Date: 2024-10-13 | ⏱️ Read time: 12 min read

Factors of success in recruiting and interviewing after applying for 150+ positions and reviewing 500+…
πŸ“Œ Top 5 Principles for Building User-Friendly Data Tables

πŸ—‚ Category: DATA ENGINEERING

πŸ•’ Date: 2024-10-13 | ⏱️ Read time: 9 min read

Designing intuitive and reliable tables that your data team will love
πŸ“Œ Linear Discriminant Analysis (LDA)

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2024-10-12 | ⏱️ Read time: 13 min read

Discover how LDA helps identify critical data features
πŸ“Œ Upgrading to Prefect Push Workers on AWS ECS

πŸ—‚ Category: DATA ENGINEERING

πŸ•’ Date: 2024-10-12 | ⏱️ Read time: 6 min read

Upgrade from Prefect 2.0 to 3.0 and use the new Push Work Pools that greatly…
πŸ“Œ Why the 2024 Nobel Prize in (AI for) Chemistry Matters So Much

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2024-10-12 | ⏱️ Read time: 6 min read

To Demis Hassabis and John Jumper, from DeepMind, and to David Baker, leader of the…
πŸ“Œ Improve Your RAG Context Recall by 95% with an Adapted Embedding Model.

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2024-10-12 | ⏱️ Read time: 11 min read

Step by Step Model Adaptation Code and Results Attached.
πŸ“Œ Gaussian Naive Bayes, Explained: A Visual Guide with Code Examples for Beginners

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-10-12 | ⏱️ Read time: 8 min read

Bell-shaped assumptions for better predictions
πŸ“Œ Bursting the AI Hype Bubble Once and for All

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2024-10-12 | ⏱️ Read time: 11 min read

Misinformation and poor research: a case study
πŸ“Œ Common Misconceptions About Data Science

πŸ—‚ Category: CAREER ADVICE

πŸ•’ Date: 2024-10-11 | ⏱️ Read time: 7 min read

Data science advice that you should question
πŸ“Œ Understanding Automatic Differentiation in JAX: A Deep Dive

πŸ—‚ Category: DEEP LEARNING

πŸ•’ Date: 2024-10-11 | ⏱️ Read time: 12 min read

Unleashing the Gradient: How JAX Makes Automatic Differentiation Feel Like Magic
πŸ“Œ A Mixed-Methods Approach to Offline Evaluation of News Recommender Systems

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2024-10-11 | ⏱️ Read time: 8 min read

Combining reader feedback from surveys with behavioral click data to optimize content personalization.
πŸ“Œ Topic Alignment for NLP Recommender Systems

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2024-10-11 | ⏱️ Read time: 18 min read

Leveraging topic modeling to align user queries with document themes, enhancing the relevance and contextual…
πŸ“Œ Automatic Differentiation (AutoDiff): A Brief Intro with Examples

πŸ—‚ Category: DEEP LEARNING

πŸ•’ Date: 2024-10-11 | ⏱️ Read time: 11 min read

An introduction to the mechanics of AutoDiff, exploring its mathematical principles, implementation strategies, and applications
πŸ“Œ Tracking Hurricanes With AI Weather Models

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2024-10-11 | ⏱️ Read time: 6 min read

Storm chasing for data scientists: A Hurricane Milton case study
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πŸ“Œ Cruel Summer

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-10-11 | ⏱️ Read time: 9 min read

Lessons Learned from the Worst Tech Job Market in 20 Years
πŸ“Œ What Goes Into AI? Exploring the GenAI Technology Stack

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2024-10-11 | ⏱️ Read time: 21 min read

You’ve heard of OpenAI and Nvidia, but do you know who else is involved in…
πŸ“Œ TDS Newsletter: To Better Understand AI, Look Under the Hood

πŸ—‚ Category: THE VARIABLE

πŸ•’ Date: 2025-09-25 | ⏱️ Read time: 3 min read

AI-powered tools tend to generate extreme reactions: on one side we have the β€œIt’s magic!” and…
πŸ“Œ Notes on LLM Evaluation

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2025-09-25 | ⏱️ Read time: 15 min read

A practical, step-by-step guide to building an evaluation pipeline for a real-world AI application