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Towards Data Science
Your home for data science. A publication sharing concepts, ideas and codes.
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The Most Valuable LLM Dev Skill is Easy to Learn, But Costly to Practice.
The Most Valuable LLM Dev Skill is Easy to Learn, But Costly to Practice.
Here’s how not to waste your budget on evaluating models and systems.
Thuwarakesh Murallie
Oct 9
The Easiest Way to Learn and Use Python Today
The Easiest Way to Learn and Use Python Today
Google Colab and its integrated Generative AI, a powerful combination
Quentin Gallea, PhD
Oct 9
Latest
Mastering Sample Size Calculations
Mastering Sample Size Calculations
A/B Testing, Reject Inference, and How to Get the Right Sample Size for Your Experiments
Lucas Braga
Oct 9
Keep the Gradients Flowing
Keep the Gradients Flowing
Optimizing Sparse Neural Networks: Understanding Gradient Flow for Faster Training, and Better Performance in Deep Learning Models.
Cristian Leo
Oct 9
Mathematics I Look for in Data Scientist Interviews
Mathematics I Look for in Data Scientist Interviews
Let’s rebuild our data science foundation.
Farzad Nobar
Oct 9
5 AI Projects You Can Build This Weekend (with Python)
5 AI Projects You Can Build This Weekend (with Python)
From beginner-friendly to advanced
Shaw Talebi
Oct 8
Embracing Uncertainty: The Power of Fuzzy Logic in Decision-Making
Embracing Uncertainty: The Power of Fuzzy Logic in Decision-Making
Exploring how fuzzy logic enhances AI, systems thinking, and real-world applications
Niklas Lang
Oct 8
ITT vs LATE: Estimating Causal Effects with IV in Experiments with Imperfect Compliance
ITT vs LATE: Estimating Causal Effects with IV in Experiments with Imperfect Compliance
Intuition, step-by-step script, and assumptions needed for the use of IV
Robson Tigre
Oct 8
Evaluating Edge Detection? Don’t Use RMSE, PSNR or SSIM
Evaluating Edge Detection? Don’t Use RMSE, PSNR or SSIM
Empirical and theoretical evidence for why Figure of Merit (FOM) is the best edge-detection evaluation metric
Conor O'Sullivan
Oct 8
From Set Transformer to Perceiver Sampler
From Set Transformer to Perceiver Sampler
On multi-modal LLM Flamingo’s vision encoder
Mengliu Zhao
Oct 8
A Deeper Dive into Odds Ratios Using Logistic Regression
A Deeper Dive into Odds Ratios Using Logistic Regression
A comprehensive guide on how to extract and explore odds ratios from a Logistic Regression model using Python and Statsmodels with examples
Iqbal Rahmadhan
Oct 8
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