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What is big data analytics? Fast answers from diverse data sets

Analyzing large volumes of data is only part of what makes big data analytics different from traditional data analytics

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Semi-supervised learning explained

Using a machine learning model’s own predictions on unlabeled data to add to the labeled data set sometimes improves accuracy, but not always

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How Qubole addresses Apache Spark challenges

The Qubole Data Platform brings streamlined configuration, auto-scaling, cost management, and performance optimizations to Spark-as-a-service

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Deep learning frameworks: PyTorch vs. TensorFlow

If you actually need a deep learning model, PyTorch and TensorFlow are both good choices

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PyTorch vs. TensorFlow: How to choose

If you actually need a deep learning model, PyTorch and TensorFlow are the two leading options

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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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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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