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

Admin: @HusseinSheikho || @Hussein_Sheikho
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πŸ“Œ I Reduced My Pandas Runtime by 95% β€” Here’s What I Was Doing Wrong

πŸ—‚ Category: PROGRAMMING

πŸ•’ Date: 2026-04-26 | ⏱️ Read time: 18 min read

Most slow Pandas code β€œworks”, until it doesn’t. Learn how to spot hidden bottlenecks, avoid…

#DataScience #AI #Python
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πŸ“Œ Comparing Explicit Measures to Calculation Groups in Tabular Models

πŸ—‚ Category: DATA MODELING

πŸ•’ Date: 2026-04-27 | ⏱️ Read time: 6 min read

With the advent of UDFs and their combination with calculation groups, I see a lot…

#DataScience #AI #Python
πŸ“Œ A Career in Data Is Not Always a Straight Line, and That’s Okay

πŸ—‚ Category: AUTHOR SPOTLIGHTS

πŸ•’ Date: 2026-04-27 | ⏱️ Read time: 9 min read

Sabrine Bendimerad on why flexibility is a crucial data science skill, the risks of outsourcing…

#DataScience #AI #Python
πŸ“Œ The Next Frontier of AI in Production Is Chaos Engineering

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2026-04-28 | ⏱️ Read time: 18 min read

Blast-radius control tells you how much to break. Intent tells you what breaking it will…

#DataScience #AI #Python
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πŸ“Œ PyTorch NaNs Are Silent Killers β€” So I Built a 3ms Hook to Catch Them at the Exact Layer

πŸ—‚ Category: DEEP LEARNING

πŸ•’ Date: 2026-04-28 | ⏱️ Read time: 11 min read

NaNs don’t crash your training β€” they quietly destroy it. After losing hours to a…

#DataScience #AI #Python
πŸ“Œ Let the AI Do the Experimenting

πŸ—‚ Category: AGENTIC AI

πŸ•’ Date: 2026-04-28 | ⏱️ Read time: 14 min read

Using autoresearch to optimise marketing campaigns under budget constraints

#DataScience #AI #Python
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πŸ“Œ Correlation Doesn’t Mean Causation! But What Does It Mean?

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2026-04-28 | ⏱️ Read time: 6 min read

What does correlation tells us?

#DataScience #AI #Python
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πŸ“Œ Ensembles of Ensembles of Ensembles: A Guide to Stacking

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2026-04-29 | ⏱️ Read time: 9 min read

The best machine learning model is not one model

#DataScience #AI #Python
πŸ“Œ Agentic AI: How to Save on Tokens

πŸ—‚ Category: AGENTIC AI

πŸ•’ Date: 2026-04-29 | ⏱️ Read time: 26 min read

Caching, lazy-loading, routing, compaction, and more

#DataScience #AI #Python
πŸ“Œ System Design Series: Apache Flink from 10,000 Feet, and Building a Flink-powered Recommendation Engine

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2026-04-29 | ⏱️ Read time: 17 min read

A deep dive into how Apache Flink works, why it exists, and learning it while…

#DataScience #AI #Python
πŸ“Œ 4 YAML Files Instead of PySpark: How We Let Analysts Build Data Pipelines Without Engineers

πŸ—‚ Category: DATA ENGINEERING

πŸ•’ Date: 2026-04-29 | ⏱️ Read time: 10 min read

How we replaced Python pipelines with dlt, dbt, and Trino β€” and cut delivery time…

#DataScience #AI #Python
πŸ“Œ A Gentle Introduction to Stochastic Programming

πŸ—‚ Category: MATHEMATICS

πŸ•’ Date: 2026-04-30 | ⏱️ Read time: 15 min read

How to make decisions when your spreadsheet is lying about the future

#DataScience #AI #Python
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πŸ“Œ Proxy-Pointer RAG: Multimodal Answers Without Multimodal Embeddings

πŸ—‚ Category: LARGE LANGUAGE MODEL

πŸ•’ Date: 2026-04-30 | ⏱️ Read time: 15 min read

Structure is all you need

#DataScience #AI #Python
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πŸ“Œ How to Study the Monotonicity and Stability of Variables in a Scoring Model using Python

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2026-04-30 | ⏱️ Read time: 10 min read

How can you validate that your variables tell a consistent risk?

#DataScience #AI #Python
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πŸ“Œ Why AI Engineers Are Moving Beyond LangChain to Native Agent Architectures

πŸ—‚ Category: AGENTIC AI

πŸ•’ Date: 2026-04-30 | ⏱️ Read time: 8 min read

Frameworks accelerated the first wave of LLM apps, but production demands a different architecture.

#DataScience #AI #Python
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πŸ“Œ How to Get Hired in the AI Era

πŸ—‚ Category: CAREER ADVICE

πŸ•’ Date: 2026-05-01 | ⏱️ Read time: 7 min read

What people actually look for when hiring juniors that stand out.

#DataScience #AI #Python
πŸ“Œ Churn Without Fragmentation: How a Party-Label Bug Reversed My Headline Finding

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2026-05-01 | ⏱️ Read time: 11 min read

A data quality case study from English local elections on categorical normalisation, metric validation, and…

#DataScience #AI #Python
πŸ“Œ Ghost: A Database for Our Times?

πŸ—‚ Category: AGENTIC AI

πŸ•’ Date: 2026-05-01 | ⏱️ Read time: 12 min read

The first database built for AI Agents

#DataScience #AI #Python
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πŸ”– 10 Stanford courses on AI and ML β€” with official pages and all materials

▢️ CS221: Artificial Intelligence
▢️ CS229: Machine Learning
▢️ CS229M: Theory of Machine Learning
▢️ CS230: Deep Learning
▢️ CS234: Reinforcement Learning
▢️ CS224N: Natural Language Processing
▢️ CS231N: Deep Learning for Computer Vision
▢️ CME295: Large Language Models
▢️ CS236: Deep Generative Models
▢️ CS336: Modeling Language from Scratch

They cover the entire spectrum: classic ML, LLM, and generative models β€” with theory and practice.

tags: #python #ML #LLM #AI

➑ https://t.iss.one/MachineLearning9
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