A Data Scientist's Guide to Python Typing: Boosting Code Clarity
Photo by Pankaj Patel on Unsplash What is ‘Typing’? By typing we are not referring to physically touching our keyboard, but rather the datatypes our variables (and functions) take on in our Python code! Python inherently is a dynamic language,- 24873Murphy2025-03-23
Enhancing CSV File Query Performance in ChatGPT
with LangChain's Self-Querying based on a customized CSV Loader- 28990Murphy2025-03-23
Keep Track of your Experiments with Hydra
Configure hyperparameters using YAML files and speed up your research!- 23514Murphy2025-03-23
Linguistic Fingerprinting with Python
Attributing authorship with punctuation heatmaps- 26219Murphy2025-03-23
Fourier-transform for time-series : plotting complex numbers
Plot the Fourier-transform algorithm to understand it.- 24574Murphy2025-03-23
How Random Are Goals in Soccer?
Sports Analytics Football (or soccer for the USA readers) is an amazing sport. It can’t be the world’s most popular sport by coincidence. Football gathers people together, it’s an excuse to disconnect from our busy lives because game tim- 20993Murphy2025-03-23
Jazz Chords Parsing with Transformers
A Data-Driven Approach to Tree-Based Music Analysis- 24140Murphy2025-03-23
Double Machine Learning, Simplified: Part 2 – Extensions & the CATE
Learn how to utilize DML for estimating individual level treatment effects to enable data-driven targeting- 28172Murphy2025-03-23
Experiment Orchestration From Scratch
In this post we will explore why experiment orchestration is important, existing orchestration solutions, how to build your own orchestrator with MongoDB, and why that might be beneficial in some use cases. Who is this useful for? Anyone trying to fit mod- 20822Murphy2025-03-23
Statistical Experiments With Resampling
Bootstrapping and permutation tests- 29392Murphy2025-03-23
Leveraging Machine Learning for Effective Marketing Strategy Development
Tips and tricks for successful building of a marketing strategy using ML- 30053Murphy2025-03-23
Building an AI to Recognize my Handwriting – Part I
Part 1 is about the theoretical and practical foundation: how to approach? would do you need? What are CNNs? Can it be automated?- 29611Murphy2025-03-23
AI's Sentence Embeddings, Demystified
Bridging the gap between computers and language: How AI Sentence Embeddings Revolutionize NLP- 29666Murphy2025-03-23
Comprehensive Guide to Ranking Evaluation Metrics
Explore an abundant choice of metrics and find the best one for your problem- 25164Murphy2025-03-23
August Edition: Summer Reads for Data Scientists
Looking for some enlightening, engaging, and thought-provoking articles? You've come to the right place- 26082Murphy2025-03-23
The Ultimate Guide to nnU-Net for State of the Art Image Segmentation
A theoretical and practical guide on how to use nnU-Net for Computer Vision and Semantic Image Segmentation and deliver SOTA performance.- 21059Murphy2025-03-23
Distributed Llama 2 on CPUs
A toy example of bulk inference on commodity hardware using Python.- 22526Murphy2025-03-23
Is Decision Science Quietly Becoming the New Data Science?
Many of the world's top companies have started hiring Decision Scientists. Is this the quiet beginning of a new era?- 20744Murphy2025-03-23
User feedback – the missing piece of your ML monitoring stack
A complete guide to building user-centric AI.- 28995Murphy2025-03-23
GPT and Beyond: The Technical Foundations of LLMs
Our weekly selection of must-read Editors' Picks and original features- 29418Murphy2025-03-23
The current state of continual learning in AI
Why is ChatGPT only trained up until 2021?Optimizing Pandas Code: The Impact of Operation Sequence
Learn how to rearrange your code to achieve significant speed improvements.