Domino Data Lab

AUGUST 12, 2021

We all have heard how data is the new oil. For data, this refinement includes doing some cleaning and manipulations that provide a better understanding of the information that we are dealing with. The purpose of Data Exploration. Data exploration is a very important step before jumping onto the machine learning wagon.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

Domino Data Lab

JULY 1, 2020

Notebooks are increasingly crucial in the data scientist’s toolbox. This form of interactive workflow was introduced to assist data scientists in documenting their work, facilitating reproducibility, and prompting collaboration with their team members. Notebook Structure.

Testing 116

Testing Data Science Machine Learning Data-driven 116

Domino Data Lab

OCTOBER 23, 2019

It covers questions to consider as well as collecting, prepping and plotting data. Collecting and prepping data are core research tasks. While the most ideal situation is to start a project with clean well-labeled data, the reality is that data scientists spend countless hours on obtaining and prepping data.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

APRIL 21, 2021

In this article, we’ll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human eye might not catch. Historically, fraud detection has been performed by analysts who are responsible for identifying and tracing suspicious patterns in the data.

Statistics 69

Statistics Machine Learning Modeling Metrics 69