Data Visualization: Going Beyond Charts

For most data scientists, the path from raw, messy data to clear narratives and actionable insights passes through visualization. Giving concrete shape to your data makes it more approachable for…

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The goldmine of Customer Reviews — Quantifying Customer Experience

With the proliferation of social media, online shopping, and related activities, customers are leaning toward providing more and more reviews about products and services they consume. Reviews have…

Concepts and practices to ensure data quality

Poor data quality can fragment your team’s time, balloon complexity of data infrastructure, and erode trust in data. But it doesn’t stop there. On the organizational level, problems with data quality…

Exploring AI by Dropping Pikachus into Art Movements

On July the 13th the company that developed the generative AI art tool Midjourney opened its closed beta. To access it, you just need to enter the discord channel. Playing with this model immediately…

Process On-Demand Data without Idle Databricks Clusters

Databricks is a Platform-as-a-Service offering that lets Data Engineers perform ingestion, exploration, and transformation of data. Recently, they included the ability to create data pipelines into…

5-Minute Paper Explanations: Food AI Part II

5 Minute Paper Explanations: Food AI Part II. Intuitive deep dive of im2recipe related paper “Dividing and Conquering Cross-Modal Recipe Retrieval: from Nearest Neighbours Baselines to….

This AI newsletter is all you need #8

This week’s highlight is surely Meta’s new chatbot: BlenderBot 3. BlenderBot 3 is accessible to everyone in the U.S. to chat with in order to collect feedback on its capabilities. It seems like…

Outliers, Leverage, Residuals, and Influential Observations

In data science, a common task is anomaly detection, i.e. understanding whether an observation is “unusual”. First of all, what does it mean to be unusual? In this article we are going to inspect…

How to create a sampling plan for your data project

Imagine that you’re a data scientist who has been hired to estimate the average height of pine trees in the forest pictured below and describe the distribution. You’re responsible for the planning…

Simple random sampling: is it actually simple?

No matter how hard you may try to forget your STAT101 course, you’ll likely tend to default to simple random sampling (SRS) as your knee jerk approach. It was, after all, an assumption you were told…