The state of data analytics and visualization adoption
A survey of usage, access methods, projects, and skills.
Data science
Data science ideas and resources.
“Not hotdog” vs. mission-critical AI applications for the enterprise
Drawing parallels and distinctions around neural networks, data sets, and hardware.
Identifying viral bots and cyborgs in social media
Analyzing tweets and posts around Trump, Russia, and the NFL using information entropy, network analysis, and community detection algorithms.
Automated root cause analysis for Spark application failures
Reduce troubleshooting time from days to seconds.
Amit Vij on GPU-accelerated analytics databases
The convergence of big data, artificial intelligence, and business intelligence
How FINRA benefits from a cloud data lake
Solving challenges of data analytics to make data accessible to all.
Why the IoT revolution needs telcos’ core skills
Fast data and virtualization are shifting the way telcos approach the IoT.
Key considerations for building an AI platform
The right AI solution is the one that fits the skill set of the users and solves the highest-priority problems for the business.
Building data lifecycles for IoT projects with edge analytics
The O'Reilly Podcast: Han Yang on the importance of investment, innovation, and improvisation.
Apache Kafka and the four challenges of production machine learning systems
Untangling data pipelines with a streaming platform.
Enabling data science for the majority
How human-in-the-loop data analytics is accelerating the discovery of insights.
Damon Feldman on combining a data hub and data lake
The O’Reilly Podcast: Achieving greater reliability and security when integrating data.
Artificial intelligence and advances in data warehousing
The O'Reilly Podcast: Gary Orenstein on developing a data infrastructure that enables the latest applications in machine learning and AI.
Converging big data, AI, and business intelligence
Utilizing GPU power to improve performance and agility.
Load, search, and secure data in multiple formats
The O'Reilly Podcast: Dave Cassel on building a unified enterprise database to store and query any type of data.
Fast track Apache Spark
6 lessons learned to get a quick start on productivity.
The APIs for neural networks in TensorFlow
A look at the Layer API, TFLearn, and Keras.
Integrating convolutional neural networks into enterprise applications
Building a production-grade real-time image classification system.
Hot data meets big data to make real-time, real-world decisions
Why machine learning needs real-time data infrastructure.
Big data’s biggest secret: Hyperparameter tuning
The toughest part of machine learning with Spark isn't what you think it is.
Three enablers for machine learning in data unification: Trust, legacy, and scale
Human-guided ML pipelines for data unification and cleaning might be the only way to provide complete and trustworthy data sets for effective analytics.
A multi-cloud strategy is the foundation for digital transformation
Using a single cloud provider is a thing of the past.
Integrating data with AI
Tamr’s Eliot Knudsen on algorithms that work alongside human experts.
A DevOps approach to data management
A multi-model approach to transforming data from a liability to an asset.