Data Science Machine Learning Data Analysis
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This channel is for Programmers, Coders, Software Engineers.

1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning

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πŸ“Œ Exploratory Data Analysis: Gamma Spectroscopy in Python (Part 2)

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2025-07-18 | ⏱️ Read time: 19 min read

Let’s observe the matter on the atomic level
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πŸ“Œ The Hidden Trap of Fixed and Random Effects

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2025-07-18 | ⏱️ Read time: 6 min read

My lesson of how blindly over-controlling for noise can erase the effects you are measuring
πŸ“Œ Gain a Better Understanding of Computer Vision: Dynamic SOLO (SOLOv2) with TensorFlow

πŸ—‚ Category: COMPUTER VISION

πŸ•’ Date: 2025-07-18 | ⏱️ Read time: 16 min read

A practical approach to instance segmentation using SOLOv2 and TensorFlow
πŸ“Œ From Reactive to Predictive: Forecasting Network Congestion with Machine Learning and INT

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2025-07-18 | ⏱️ Read time: 7 min read

Learn how machine learning can predict network congestion before it happens
πŸ“Œ TDS Authors Can Now Edit Their Published Articles

πŸ—‚ Category: WRITING

πŸ•’ Date: 2025-07-18 | ⏱️ Read time: 3 min read

One of our guiding principles as a publication is that authors’ work remains theirs. This…
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πŸ“Œ The Age of Self-Evolving AI Is Here

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2025-07-17 | ⏱️ Read time: 17 min read

How Meta’s latest breakthrough lets models learn, adapt, and improve β€” all on their own
πŸ“Œ Estimating Disease Rates Without Diagnosis

πŸ—‚ Category: STATISTICS

πŸ•’ Date: 2025-07-17 | ⏱️ Read time: 7 min read

Immune genes as predictors of disease
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πŸ“Œ Don’t Waste Your Labeled Anomalies: 3 Practical Strategies to Boost Anomaly Detection Performance

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2025-07-17 | ⏱️ Read time: 15 min read

A few labels go a long way in anomaly detection
πŸ“Œ Summer Must-Reads: The Data Science Edition

πŸ—‚ Category: THE VARIABLE

πŸ•’ Date: 2025-07-17 | ⏱️ Read time: 4 min read

Cool off with some engaging, enlightening reads.
πŸ“Œ Your 1M+ Context Window LLM Is Less Powerful Than You Think

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2025-07-17 | ⏱️ Read time: 9 min read

Why working memory is a more important bottleneck than raw context window size
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πŸ“Œ Midyear 2025 AI Reflection

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2025-07-16 | ⏱️ Read time: 7 min read

Impressions on agentic AI progress and the AI-2027 Jobocalypse scenario
πŸ“Œ Exploring Prompt Learning: Using English Feedback to Optimize LLM Systems

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2025-07-16 | ⏱️ Read time: 11 min read

Prompt learning presents a compelling approach for continuous improvement of AI applications
πŸ“Œ How to Overlay a Heatmap on a Real Map with Python

πŸ—‚ Category: DATA VISUALIZATION

πŸ•’ Date: 2025-07-16 | ⏱️ Read time: 9 min read

Visualizing historical tornado trends
πŸ“Œ 3 Steps to Context Engineering a Crystal-Clear Project

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2025-07-16 | ⏱️ Read time: 7 min read

Learn three easy steps for gaining an intelligent picture for any project by using the…
πŸ“Œ The Power of Building from Scratch

πŸ—‚ Category: AUTHOR SPOTLIGHTS

πŸ•’ Date: 2025-07-16 | ⏱️ Read time: 5 min read

Mauro Di Pietro discusses building AI agents with open-source tools, bridging theory and practice, and…
πŸ“Œ Do You Really Need a Foundation Model?

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2025-07-16 | ⏱️ Read time: 10 min read

LLM or custom model: how should you choose the right solution?
πŸ“Œ How Metrics (and LLMs) Can Trick You: A Field Guide to Paradoxes

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2025-07-15 | ⏱️ Read time: 8 min read

When numbers lie β€” and your metrics mislead you
πŸ“Œ How to Ensure Reliability in LLM Applications

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2025-07-15 | ⏱️ Read time: 7 min read

Learn how to make your LLM applications more robust
πŸ“Œ Deploy a Streamlit App to AWS

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2025-07-15 | ⏱️ Read time: 16 min read

Using the Elastic Beanstalk service
πŸ“Œ From Equal Weights to Smart Weights: OTPO’s Approach to Better LLM Alignment

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2025-07-15 | ⏱️ Read time: 7 min read

Using optimal transport to weight what matters most In LLM-generated responses
πŸ“Œ Automating Deep Learning: A Gentle Introduction to AutoKeras and Keras Tuner

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2025-07-15 | ⏱️ Read time: 4 min read

How to save time and boost your models with these two approachable AutoML libraries.