DeepGuide for DeepSeek

A Maturity Model for Data Modeling and Design
Best practices for mastering the standardization of data definitions
27079Murphy2025-03-23
The Best Talks from PyCon US 2023
Our thoughts on the largest Python conference in the world
26758Murphy2025-03-23
Forecast Multiple Time Series Like a Master
From local to global algorithms
24726Murphy2025-03-23
Getting Started with LangChain: A Beginner's Guide to Building LLM-Powered Applications
A LangChain tutorial to build anything with large language models in Python
24463Murphy2025-03-23
From Data to Clusters; When is Your Clustering Good Enough?
Sensible clusters and hidden gems can be found using clustering approaches but you need the right cluster evaluation method!
26407Murphy2025-03-23
SynthDiD 101: A Beginner's Guide to Synthetic Difference-in-Differences
On the method's advantages and disadvantages, demonstrated with the synthdid package in R
23325Murphy2025-03-23
Time Series for Climate Change: Forecasting Large Ocean Waves
How to use time series analysis and forecasting to tackle climate change
22553Murphy2025-03-23
How to Use dbt Seeds
What they are and when to use them
27745Murphy2025-03-23
Vector Representations for Machine Learning
How data scientists convert real-world objects in numerical representation for the development of machine learning models
25350Murphy2025-03-23
Multivariate Process Control by Principal Component Analysis Using T² and Q errors
Using and interpreting Hotelling's T² and Squared Prediction Error Q in anomaly detection systems
26276Murphy2025-03-23
A Serverless Query Engine from Spare Parts
An open-source implementation of a Data Lake with DuckDB and AWS Lambdas
26946Murphy2025-03-23
Python Type Hinting: From Type Aliases To Type Variables and New Types
See type aliases, type variables and new types in action
23096Murphy2025-03-23
QQ Plotting Your Way to Data Enlightenment: A Hitchhiker's Guide to the Galaxies of Distributi
Is Your Data Normal? The Ultimate Guide to QQ Plots Using R
23995Murphy2025-03-23
Engineering Features for Contextual Recommendation Engines
Analysis of distinct cases where contextual information dominates
24704Murphy2025-03-23
Get started using LangChain with Python to leverage LLMs
21389Murphy2025-03-23
Unsupervised Learning Meets Emergent pattern
How unsupervised learning can help us detect phase transitions and emergent phenomena?
24096Murphy2025-03-23
OCR-Free Document Data Extraction with Transformers (1/2)
Donut versus Pix2Struct on custom data
26980Murphy2025-03-23
A Framework for Building a Production-Ready Feature Engineering Pipeline
Lesson 1: Batch Serving. Feature Stores. Feature Engineering Pipelines.
21573Murphy2025-03-23
How Data Science Helped Sherlock Holmes Find a Murderer
Inventory management, portfolio optimization, machine scheduling, vehicle routing, and many other real-life problems are excellent examples of how data science and analytical techniques can be employed. It’s no surprise that these are some of the fi
27473Murphy2025-03-23
Easily build an Event Reminder with Cloud Workflows and Cloud Scheduler
Use Case: Identify Birthdays and Send Notification Emails
25939Murphy2025-03-23

< 37 38 39 40 41 >

Genius Cliques: Mapping out the Nobel Network
Combining Network Science, Data Visualization, and Wikipedia to uncover hidden connections between all the Nobel laureates.
Data Science Expertise Comes in Many Shapes and Forms
Our weekly selection of must-read Editors' Picks and original features

Recommend

◦ Expanding Time

◦ Semantically Compress Text to Save On LLM Costs

◦ How bad is being greedy?

◦ The One Mindset Change That Launched Me into Data Science

◦ My commute to work is more than 4 hours. Each way.

◦ Unveiling Metadynamics: A Beginner's Guide to Mastering PLUMED (Part 1 of 3)

◦ Accelerating AI/ML Model Training with Custom Operators

◦ Sketch: A Promising AI Library to Help With Pandas Dataframes Directly in Jupyter

◦ Regulating Generative AI

◦ How to Use SQLAlchemy to Make Database Requests Asynchronously

◦ Information at a Glance: Do Your Charts Suck?

◦ Finding Dark Matter using a Quantum Computer