Please Use Streaming Workload to Benchmark Vector Databases
Why static workload is insufficient and what I learned by comparing HNSWLIB and DiskANN using streaming workload- 26054Murphy ≡ DeepGuide
Temporal Graph Benchmark
Challenging and realistic datasets for temporal graph learning- 21654Murphy ≡ DeepGuide
MLX vs MPS vs CUDA: a Benchmark
A first benchmark of Apple's new ML framework MLX- 28420Murphy ≡ DeepGuide
Benchmarking Rust Compiler Settings with Criterion
Controlling Criterion with Scripts and Environment Variables- 28366Murphy ≡ DeepGuide
Benchmarking Pytest with CICD Using GitHub Action
Making Pytest benchmark automated, actionable, and intuitive- 26633Murphy ≡ DeepGuide
Optimizing Pandas Code: The Impact of Operation Sequence
Learn how to rearrange your code to achieve significant speed improvements.- 21276Murphy ≡ DeepGuide
A Benchmark and Taxonomy of Categorical Encoders
New. Comprehensive. Extendable.- 22991Murphy ≡ DeepGuide
Python One Billion Row Challenge – From 10 Minutes to 4 Seconds
The one billion row challenge is exploding in popularity. How well does Python stack up?- 23146Murphy ≡ DeepGuide
The One Billion Row Challenge in Julia
What can data scientists learn should they choose to accept this mission?- 26490Murphy ≡ DeepGuide
Statistically Confirm Your -Comparing Pandas and Polars with 1 Million Rows of Data
Using the Independent samples t-test and Welch's t-test to compare scores in benchmarking.- 27512Murphy ≡ DeepGuide
Dummy Regressor, Explained: A Visual Guide with Code Examples for Beginners
Naively choosing the best number for all of your prediction- 27263Murphy ≡ DeepGuide
Rethinking LLM Benchmarks: Measuring True Reasoning Beyond Training Data
Apple's New LLM Benchmark, GSM-Symbolic- 26345Murphy ≡ DeepGuide
We look at an implementation of the HyperLogLog cardinality estimati
Using clustering algorithms such as K-means is one of the most popul
Level up Your Data Game by Mastering These 4 Skills
Learn how to create an object-oriented approach to compare and evalu
When I was a beginner using Kubernetes, my main concern was getting
Tutorial and theory on how to carry out forecasts with moving averag