datascience

Depiction of survey questions with symbols to show good and bad questions

Unlock Actionable Insights: 5 Tips for Designing Impactful Market Research Surveys

Unlock Actionable Insights: 5 Tips for Designing Impactful Market Research Surveys Author: Sean Hughes The most effective and lucrative business decisions are data driven. Sometimes the information needed to make a business decision can come from internal polling or even conversations with team members but many require customer input. Market research survey data can be …

Unlock Actionable Insights: 5 Tips for Designing Impactful Market Research Surveys Read More »

Kubernetes X JupyterHub

Deploying JupyterHub with Kubernetes: A Step-by-Step Guide

Deploying JupyterHub with Kubernetes: A Step-by-Step Guide Author: Harsh Patel JupyterHub is a powerful tool for deploying and managing Jupyter Notebooks at scale. With JupyterHub, you can provide multiple users with access to a shared Jupyter Notebook server. This can be useful in a variety of settings, such as classrooms, research groups, or companies that …

Deploying JupyterHub with Kubernetes: A Step-by-Step Guide Read More »

Segmentation Models Compared

Segmentation Models Compared:  What’s best suited to your needs? Author: Yifei Zheng Customer segmentation is a means of organizing and managing a company’s relationship with its customers and can improve things like personalized marketing communications, customer service and support efforts, customer loyalty, identifying the most valuable customers, and identifying new product or upsell opportunities. This …

Segmentation Models Compared Read More »

MLOps: Building Machine Learning Systems

MLOps: Building Machine Learning Systems Author: Ani Madurkar The importance of thinking larger when designing effective and ethical machine learning systems MLOps is taking the data science and machine learning landscape by storm as organizations struggle to realize the value promised by their data. This is partly due to the difficulty in productionizing machine learning …

MLOps: Building Machine Learning Systems Read More »

Incorporating Decision Science into Data Science

Author: Igor Pshenychny Machine Learning and mathematical rigor are tools at data scientists’ disposal. But we all know that having a better calculator won’t exactly result in better test scores, and having a more powerful computer won’t necessarily make you a better programmer. To develop a strategy that doesn’t underperform, a data scientist will need …

Incorporating Decision Science into Data Science Read More »

How to Get the Most Out of Jupyter Notebook

Author: Igor Pshenychny Jupyter Notebook has become the de facto standard for data analysis. An acronym of the three main coding languages it supports: Julia, Python, and R, Jupyter Notebook provides a user-friendly integrated development environment (IDE) and has been evolving over time to become a go-to tool for data scientists. Jupyter Notebook facilitates a …

How to Get the Most Out of Jupyter Notebook Read More »