Analytics

Analytics | News, how-tos, features, reviews, and videos

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How to model time-series anomaly detection for IoT

Machines fail. By creating a time-series prediction model from historical sensor data, you can know when that failure is coming

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How to use anomaly detection in Azure machine learning

Machine learning is about more than vision and speech, as Azure’s latest machine learning service shows

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Review: OmniSci GPU database lifts huge data sets

GPU acceleration of database, rendering, and visualization enables interactive exploration of data sets with billions of rows

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Pub/sub messaging: Apache Kafka vs. Apache Pulsar

Apache Kafka set the bar for large-scale distributed messaging, but Apache Pulsar has some neat tricks of its own

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Tidy eval in R: A simple example

Do you want to use ggplot2, dplyr, or other tidyverse functions in your own functions? This easy example shows how

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The best machine learning and deep learning libraries

Why TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models

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How to use Tableau to analyze agile, devops, and website metrics

Developers often need their own reporting capabilities to better analyze, predict, and manage aspects of their work; tools like Tableau can help

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How to write an R package

R packages are great for organizing your own work, not only sharing with others. See how to create an R package in a few simple steps, thanks to packages like devtools, usethis, and roxygen2

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Review: Google Cloud AutoML is truly automated machine learning

Google’s AutoML lets you create customized deep learning models without any knowledge of data science or programming

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How to validate data, analytics, and data visualizations

Application testing often ignores one crucial set of tests that is critical for any application processing or presenting data, analytics, or data visualizations

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AI, machine learning, and deep learning: Everything you need to know

All about the business benefits, technology frameworks and models, and application of artificial intelligence for better business outcomes

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5 reasons data science belongs in the cloud

Why laptop-hugging data scientists and server-hugging machine learning practitioners should consider letting go

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How to run Python in R

Learn how to run Python code inside an R script using the reticulate R package

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How to choose the right data visualization tools for your apps

Visualization frameworks have their place, but dedicated visualization tools are often a better way to create interactive, visual experiences in your applications

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How to use deep learning to write Shakespeare

LSTM recurrent neural networks can be trained to generate free text. Let’s see how well AI can imitate the Bard

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IBM preps Watson AI services to run on Kubernetes

IBM Watson services arrive in versions that can run on the public cloud or on privately hosted container infrastructure

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IBM Cloud Q&A: Kubernetes takes center stage

As IBM’s Think conference commences, general manager Jim Comfort explains how Kubernetes and container portability are central to IBM’s cloud strategy and Red Hat acquisition

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How to use Azure Data Explorer for large-scale data analysis

Microsoft’s tool for querying terabytes of data finally arrives for everyone to use

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Python tutorial: Get started with Jupyter Notebook

Learn how to combine Python code, freeform text, mathematical formulas, and graphics in an interactive, shareable notebook

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Enterprise architecture: A key driver of digital and analytic transformation

A conversation with Claus Torp Jensen, chief technology officer at CVS Health, on how to build an effective architectural function in the enterprise

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