Subject archive for "data-analysis"

Product Updates

Take a look at Domino Code Assist

A picture is worth 1000 words, so let's get right into exploring Domino Code Assist (DCA). As I mentioned in my prior blog, with DCA you can import a dataset, make a few data visualizations, and deploy those data visualizations as a Python data app - all through a point-and-click interface. At the end of this, you have a perfectly executable Python or R script that follows the steps that you took in the UI.

By Jack Parmer3 min read

Data Science

Python is the New Excel

It's becoming clear that the traditional “citizen data scientist” approach, focusing on no-code tools, has become an evolutionary dead end. Organizations who have pursued this route have little to show beyond PoCs and one-off successes despite years of investment in training and underutilized, proprietary tools. The best that can be said is that these efforts have been a costly way of democratizing data prep and business intelligence. In reality, they have been a step in the wrong direction for analytics and data science maturity.

By Kjell Carlsson7 min read

Machine Learning

7 Important Machine Learning Techniques and Algorithms

At the core of every machine learning model are the algorithms that power them, consuming the data and providing you with the answers you need. In machine learning (ML) today, there are countless algorithms being used, each designed to find solutions to different problems. Before you can determine which algorithm, or algorithms, are going to do the job, it’s important to understand what your options are.

By David Weedmark8 min read

Data Science

Faster data exploration in Jupyter through Lux

Jupyter Notebook has become one of the key primary tools for many data scientists. It offers a clear way to collaborate with others throughout the process of data exploration, feature engineering and model fitting and through utilizing some clear best practices, can also become living documents of how that code operates.

By David Bloch5 min read

Data Science

The Curse of Dimensionality

Danger of Big Data

By Bill Shannon14 min read

Data Science

0.05 is an Arbitrary Cut Off: "Turning Fails into Wins”

Grace Tang, Data Scientist at Uber, presented insights, common pitfalls, and “best practices to ensure all experiments are useful” in her Strata Singapore session, “Turning Fails into Wins”. Tang holds a Ph.D. in Neuroscience from Stanford University.

By Domino5 min read

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