Machine Learning
Machine Learning | News, how-tos, features, reviews, and videos
Machine learning algorithms explained
Machine learning uses algorithms to turn a data set into a model. Which algorithm works best depends on the problem
Review: UiPath aces robotic process automation
UiPath Enterprise RPA Platform is a remarkably complete toolkit for process automation that is also remarkably easy to use
Microsoft smartens up Azure Cognitive Services
Decision services based on reinforcement learning and other machine learning enhancements are coming to the Azure cloud
5 takeaways on scaling machine learning
Twitter and Facebook can teach us a lot about effective artificial intelligence
Review: Kinetica analyzes billions of rows in real time
GPU database is not only hugely scalable, but integrates graph analysis, location intelligence, and machine learning with standard SQL
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
Machine learning and data visualization for clickstream analysis
How to use the KNIME Analytics Platform to understand the behavior of website visitors
TensorFlow unveils MLIR for faster machine learning
Sublanguage project promises faster compilation and easier hardware optimization for high-performance machine learning models
AI systems are biased, and cloud availability makes it worse
IT will have to be on the lookout for hidden biases and take action to minimize the harm
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
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
AI cloudops is coming, whether you like it or not
New cloud monitoring and cloud management tools are becoming self-learning, with both pros and cons today
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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To be, and not to be—is that the answer?
If you believe much of the current reporting on quantum computing, it's around the corner. Here's how quantum computing works and how realistic it is that it will be available any time soon
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
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
5 reasons data science belongs in the cloud
Why laptop-hugging data scientists and server-hugging machine learning practitioners should consider letting go
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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