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10 Splunk alternatives for log analysis

Splunk may be the most famous way to make sense of mass quantities of log data, but it is far from the only player around

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Automated machine learning or AutoML explained

AutoML frameworks and services eliminate the need for skilled data scientists to build machine learning and deep learning models

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How to do real-time analytics across historical and live data

5 in-memory computing platform capabilities that support analytical processing of both data lake data and operational streams

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HPE plus MapR: Too much Hadoop, not enough cloud

MapR gives HPE superior big data analytics technology and expertise, but not what HPE needs most

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The best machine learning and deep learning libraries

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

A human profile containing digital wireframe of technology connections.

The best machine learning and deep learning libraries

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

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TensorFlow 2 review: Easier machine learning

Now more platform than toolkit, TensorFlow has made strides in everything from ease of use to distributed training and deployment

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The data lake is becoming the new data warehouse

Platforms like AWS Lake Formation and Delta Lake point toward a central hub for decision support and AI-driven decision automation

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Time series analysis with KNIME and Spark

Train and evaluate a simple time series model using a random forest of regression trees and the NYC Yellow taxi data set

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Supervised learning explained

Supervised learning turns labeled training data into a tuned predictive model

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What is TensorFlow? The machine learning library explained

TensorFlow is a Python-friendly open source library for numerical computation that makes machine learning faster and easier

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Hadoop runs out of gas

As big data customers flee complexity and embrace the cloud, Hadoop vendors are sputtering

broken down red mustang in trouble roadside hopeless

Hadoop runs out of gas

As big data customers flee complexity and embrace the cloud, the Hadoop vendors are sputtering

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What is natural language processing? AI for speech and text

Deep learning has improved machine translation and other natural language processing tasks by leaps and bounds

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What is deep learning? Algorithms that mimic the human brain

Deep neural networks can solve the most challenging problems, but require abundant computing power and massive amounts of data

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4 reasons big data projects fail—and 4 ways to succeed

Nearly all big data projects end up in failure, despite all the mature technology available. Here's how to make big data efforts actually succeed

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What is machine learning? Intelligence derived from data

Machine learning algorithms learn from data to solve problems that are too complex to solve with conventional programming

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Machine learning algorithms explained

Machine learning uses algorithms to turn a data set into a model. Which algorithm works best depends on the problem

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Delta Lake gives Apache Spark data sets new powers

A new open source project from Databricks adds ACID transactions, versioning, and schema enforcement to Spark data sources that don't have them

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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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