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.

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πŸ“Œ Visualization of Data with Pie Charts in Matplotlib

πŸ—‚ Category:

πŸ•’ Date: 2024-10-16 | ⏱️ Read time: 5 min read

Examples of how to create different types of pie charts using Matplotlib to visualize the…
πŸ“Œ A Novel Approach to Detect Coordinated Attacks Using Clustering

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2024-10-16 | ⏱️ Read time: 18 min read

Unveiling hidden patterns: grouping malicious behavior
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πŸ“Œ Exploring DRESS Kit V2

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2024-10-16 | ⏱️ Read time: 13 min read

Exploring new features and notable changes in the latest version of the DRESS Kit
πŸ“Œ The Science Behind AI’s First Nobel Prize

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2024-10-16 | ⏱️ Read time: 13 min read

How Physics and Machine Learning Joined Forces to Win Physics Nobel 2024
πŸ“Œ Marketing Mix Modeling (MMM): How to Avoid Biased Channel Estimates

πŸ—‚ Category: DATA SCIENCE

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

Learn which variables you should and should not take into account in your model.
πŸ“Œ Beyond Naive RAG: Advanced Techniques for Building Smarter and Reliable AI Systems

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2024-10-16 | ⏱️ Read time: 32 min read

A deep dive into advanced indexing, pre-retrieval, retrieval, and post-retrieval techniques to enhance RAG performance
πŸ“Œ Will Your Vote Decide the Next President?

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-10-15 | ⏱️ Read time: 22 min read

Simulating the probability that your singular vote swings the election in November
πŸ“Œ Normalized Discounted Cumulative Gain (NDCG) – The Ultimate Ranking Metric

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-10-15 | ⏱️ Read time: 10 min read

NDCG – The Rank-Aware Metric for Evaluating Recommendation Systems
πŸ“Œ Continual Learning: A Primer

πŸ—‚ Category: DEEP LEARNING

πŸ•’ Date: 2024-10-15 | ⏱️ Read time: 8 min read

Plus paper recommendations
πŸ“Œ I Fine-Tuned the Tiny Llama 3.2 1B to Replace GPT-4o

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-10-15 | ⏱️ Read time: 8 min read

Is the fine-tuning effort worth more than few-shot prompting?
πŸ“Œ Dataflow architecture

πŸ—‚ Category: DATA ENGINEERING

πŸ•’ Date: 2024-10-15 | ⏱️ Read time: 23 min read

on derived data views and eventual consistency
πŸ“Œ I Built An AI Human-Level Game Player

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2024-10-15 | ⏱️ Read time: 13 min read

Old-school game trees can be incredibly effective.
πŸ“Œ AI Feels Easier Than Ever, But Is It Really?

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2024-10-15 | ⏱️ Read time: 9 min read

The 4 big challenges of building AI products
πŸ“Œ Evaluating synthetic data

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2024-10-14 | ⏱️ Read time: 9 min read

Assessing plausibility and usefulness of data we generated from real data
πŸ“Œ How to Choose the Best ML Deployment Strategy: Cloud vs. Edge

πŸ—‚ Category:

πŸ•’ Date: 2024-10-14 | ⏱️ Read time: 17 min read

The choice between cloud and edge deployment could make or break your project
πŸ“Œ Florence-2: Advancing Multiple Vision Tasks with a Single VLM Model

πŸ—‚ Category:

πŸ•’ Date: 2024-10-14 | ⏱️ Read time: 8 min read

A Guided Exploration of Florence-2’s Zero-Shot Capabilities: Captioning, Object Detection, Segmentation and OCR.
πŸ“Œ PyTorch Optimizers Aren’t Fast Enough. Try These Instead

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-10-14 | ⏱️ Read time: 12 min read

These 4 advanced optimizers will open your mind.
πŸ“Œ How to Set Bid Guardrails in PPC Marketing

πŸ—‚ Category: DATA SCIENCE

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

Without controls, bidding algorithms can be quite volatile. Learn how to protect performance through adding…
πŸ“Œ Product-Oriented ML: A Guide for Data Scientists

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2024-10-14 | ⏱️ Read time: 30 min read

How to build ML products users love
πŸ“Œ lintsampler: a new way to quickly get random samples from any distribution

πŸ—‚ Category: PROBABILITY

πŸ•’ Date: 2024-10-14 | ⏱️ Read time: 5 min read

lintsampler is a pure Python package that can easily and efficiently generate random samples from…