Skip to content

    About Domino

    Choosing the right Machine Learning Framework

    Machine learning (ML) frameworks are interfaces that allow data scientists and developers to build and deploy machine learning models faster and...

    Analyzing Large P Small N Data - Examples from Microbiome

    Guest Post by Bill Shannon, Co-Founder and Managing Partner of BioRankings Introduction High throughput screening technologies have been developed to...

    The Curse of Dimensionality

    Guest Post by Bill Shannon, Founder and Managing Partner of BioRankings Danger of Big Data Big data is the rage. This could be lots of rows (samples)...

    Evaluating Generative Adversarial Networks (GANs)

    This article provides concise insights into GANs to help data scientists and researchers assess whether to investigate GANs further. If you are...

    Techniques for Collecting, Prepping, and Plotting Data: Predicting Social Media-Influence in the NBA

    This article provides insight on the mindset, approach, and tools to consider when solving a real-world ML problem. It covers questions to consider...

    Clustering in R

    This article covers clustering including K-means and hierarchical clustering. A complementary Domino project is available. Introduction Clustering is...

    Understanding Causal Inference

    This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data...

    Time Series with R

    This article delves into methods for analyzing multivariate and univariate time series data. A complementary Domino project is available. Introduction

    Announcing Domino 3.4: Furthering Collaboration with Activity Feed

    Our last release, Domino 3.3 saw the addition of two major capabilities: Datasets and Experiment Manager. “Datasets”, a high-performance, revisioned...

    Comparing the Functionality of Open Source Natural Language Processing Libraries

    In this guest post, Maziyar Panahi and David Talby provide a cheat sheet for choosing open source NLP libraries. What do natural language processing...

    Manipulating Data with dplyr

    Special thanks to Addison-Wesley Professional for permission to excerpt the following "Manipulating data with dplyr" chapter from the book, ...

    Announcing Domino 3.3: Datasets and Experiment Manager

    Our mission at Domino is to enable organizations to put models at the heart of their business. Models are so different from software — e.g., they...

    Highlights from the Maryland Data Science Conference: Deep Learning on Imagery and Text

    Niels Kasch, cofounder of Miner & Kasch, an AI and Data Science consulting firm, provides insight from a deep learning session that occurred at the ...