Data Science Machine Learning Data Analysis
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ads: @HusseinSheikho

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 Emerging Tech Is Nothing Without Methodology

πŸ—‚ Category: ANALYTICS

πŸ•’ Date: 2024-09-19 | ⏱️ Read time: 6 min read

Or: a Hundred Ways to Solve a Complex Problem
πŸ“Œ A Visual Exploration of Semantic Text Chunking

πŸ—‚ Category: NATURAL LANGUAGE PROCESSING

πŸ•’ Date: 2024-09-19 | ⏱️ Read time: 22 min read

Use embeddings and visualization tools to split text into meaningful chunks
πŸ“Œ Principal Component Analysis – Hands-On Tutorial

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-09-18 | ⏱️ Read time: 13 min read

Dimensionality reduction through Principal Component Analysis (PCA).
πŸ“Œ Uncertainty in Markov Decisions Processes: a Robust Linear Programming approach

πŸ—‚ Category: MATH

πŸ•’ Date: 2024-09-18 | ⏱️ Read time: 8 min read

Theoretical derivation of the Robust Counterpart of Markov Decision Processes (MDPs) as a Linear Program…
Today I am 3️⃣0️⃣ years old, I am excited to make more successes and achievements

My previous year was full of exciting events and economic, political and programmatic noise, but I kept moving forward

Best regards
Eng. @HusseinSheikho πŸ”€
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πŸ“Œ GPU Accelerated Polars – Intuitively and Exhaustively Explained

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2024-09-17 | ⏱️ Read time: 16 min read

Fast Dataframes for Big Problems
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πŸ“Œ Polars + NVIDIA GPU Tutorial

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-09-17 | ⏱️ Read time: 4 min read

Using Polars with NVIDIA GPU can speed up your data pipelines
πŸ“Œ The Math Behind Kernel Density Estimation

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-09-17 | ⏱️ Read time: 13 min read

Exploring the foundations, concepts, and math of kernel density estimation
πŸ“Œ Model Management with MLflow, Azure, and Docker

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2024-09-17 | ⏱️ Read time: 11 min read

A guide to tracking experiments and managing models
πŸ“Œ Football and Geometry – Passing Networks

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-09-16 | ⏱️ Read time: 12 min read

Analyzing Bayer Leverkusen’s Passing Networks from Last Season
πŸ“Œ PySpark Explained: The InferSchema Problem

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-09-16 | ⏱️ Read time: 10 min read

Think before using this common option when reading large CSV’s
πŸ“Œ Introducing NumPy, Part 4: Doing Math with Arrays

πŸ—‚ Category:

πŸ•’ Date: 2024-09-16 | ⏱️ Read time: 12 min read

Plus reading and writing array data!
πŸ“Œ Disability, Accessibility, and AI

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2024-09-16 | ⏱️ Read time: 11 min read

A discussion of how AI can help and harm people with disabilities
πŸ“Œ Teaching Your Model to Learn from Itself

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-09-16 | ⏱️ Read time: 6 min read

In machine learning, more data leads to better results. But labeling data can be expensive…
πŸ“Œ Vision Mamba: Like a Vision Transformer but Better

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-09-16 | ⏱️ Read time: 26 min read

Part 4 – Towards Mamba State Space Models for Images, Videos and Time Series
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πŸ“Œ Unit Disk Uniform Sampling

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-09-16 | ⏱️ Read time: 15 min read

Discover the optimal transformations to apply on the standard 0,1 uniform random generator for uniformly…
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πŸ“Œ How to Implement State-of-the-Art Masked AutoEncoders (MAE)

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-09-16 | ⏱️ Read time: 8 min read

A Step-by-Step Guide to Building MAE with Vision Transformers
πŸ“Œ The Data Strategy Choice Cascade

πŸ—‚ Category:

πŸ•’ Date: 2024-09-16 | ⏱️ Read time: 23 min read

What your data strategy should look like
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πŸ“Œ Are Foundation Models Ready for Your Production Tabular Data?

πŸ—‚ Category: LARGE DATA MODELS

πŸ•’ Date: 2025-10-01 | ⏱️ Read time: 15 min read

A complete review of architectures to make zero-shot predictions in the most common types of…
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πŸ“Œ How to Improve the Efficiency of Your PyTorch Training Loop

πŸ—‚ Category: DEEP LEARNING

πŸ•’ Date: 2025-10-01 | ⏱️ Read time: 14 min read

Learn how to diagnose and resolve bottlenecks in PyTorch using the numworkers, pinmemory, and profiler…