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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📌 Four AI Minds in Concert: A Deep Dive into Multimodal AI Fusion

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-07-02 | ⏱️ Read time: 36 min read

Introduction: From System Architecture to Algorithmic Execution In my previous article, I explored the architectural…
📌 Why We Should Focus on AI for Women

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-07-02 | ⏱️ Read time: 6 min read

A simulation study on gender disparities entrenched in AI.
📌 How to Maximize Technical Events — NVIDIA GTC Paris 2025

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-07-02 | ⏱️ Read time: 10 min read

Learn about my experience at NVIDIA GTC Paris 25, and how you can get the…
📌 How to Access NASA’s Climate Data — And How It’s Powering the Fight Against Climate Change Pt. 1

🗂 Category: DATA SCIENCE

🕒 Date: 2025-07-01 | ⏱️ Read time: 11 min read

From architectural design to food security.
📌 STOP Building Useless ML Projects – What Actually Works

🗂 Category: DATA SCIENCE

🕒 Date: 2025-07-01 | ⏱️ Read time: 7 min read

How to find machine learning projects that will get you hired.
📌 An Introduction to Remote Model Context Protocol Servers

🗂 Category: DATA SCIENCE

🕒 Date: 2025-07-01 | ⏱️ Read time: 15 min read

Writing, testing and using them.
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📌 Implementing IBCS rules in Power BI

🗂 Category: DATA VISUALIZATION

🕒 Date: 2025-07-01 | ⏱️ Read time: 12 min read

Is there a way to use the out-of-the-box features of Power BI to be IBCS…
📌 Revisiting Benchmarking of Tabular Reinforcement Learning Methods

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-07-01 | ⏱️ Read time: 9 min read

Introducing a modular framework and improving model performance.
📌 From Reporting to Reasoning: How AI Is Rewriting the Rules of Data App Development

🗂 Category: DATA SCIENCE

🕒 Date: 2025-07-01 | ⏱️ Read time: 2 min read

Explore the shift from static reports to intelligent apps with our first ebook.
📌 Prescriptive Modeling Makes Causal Bets – Whether You Know it or Not!

🗂 Category: DATA SCIENCE

🕒 Date: 2025-06-30 | ⏱️ Read time: 16 min read

An explanation of the causal assumption implicit in prescriptive modeling and how to satisfy it.
📌 A Gentle Introduction to Backtracking

🗂 Category: DATA SCIENCE

🕒 Date: 2025-06-30 | ⏱️ Read time: 7 min read

Conceptual overview and hands-on examples
📌 Lessons Learned After 6.5 Years Of Machine Learning

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-06-30 | ⏱️ Read time: 7 min read

Deep work, trends, data, and research
📌 From Pixels to Plots

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-06-30 | ⏱️ Read time: 16 min read

How I built an AI-powered prototype to turn images into insights
📌 Become a Better Data Scientist with These Prompt Engineering Tips and Tricks

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2025-06-30 | ⏱️ Read time: 11 min read

Part 1: prompt engineering for planning, cleaning, and EDA
📌 The End-to-End Data Scientist’s Prompt Playbook

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2025-09-08 | ⏱️ Read time: 10 min read

Part 3: Prompts for docs, DevOps, and stakeholder communication
📌 A Developer’s Guide to Building Scalable AI: Workflows vs Agents

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-06-27 | ⏱️ Read time: 38 min read

A practical guide to choosing between AI agents and workflows for production systems, covering the…
📌 Pipelining AI/ML Training Workloads with CUDA Streams

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-06-26 | ⏱️ Read time: 12 min read

PyTorch Model Performance Analysis and Optimization — Part 9
📌 A Caching Strategy for Identifying Bottlenecks on the Data Input Pipeline

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-06-26 | ⏱️ Read time: 16 min read

PyTorch model performance analysis and optimization — Part 8
📌 Hitchhiker’s Guide to RAG with ChatGPT API and LangChain

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-06-26 | ⏱️ Read time: 7 min read

Build a simple Python RAG pipeline using your local files as context