Machine Learning
Machine Learning | News, how-tos, features, reviews, and videos
Google previews site for sharing machine learning experiments
TensorBoard.dev allows you to upload and share TensorBoards and visualize model graphs and metrics
Google Cloud launches TensorFlow Enterprise
Google Cloud service combines the TensorFlow machine learning platform with enterprise support and managed services
Qubole review: Self-service big data analytics
Cloud-native data platform puts Spark, Presto, Hive, and Airflow at your fingertips, while controlling your cloud spending
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Technology that scares us | TECH(talk)
Drones, self-driving vehicles and intrusive tech devices have our otherwise fearless hosts on edge. Watch as IDG TECH(talk) hosts Ken Mingis and Juliet Beauchamp, plus Macworld’s Michael Simon discuss why that tech scares them and...
Google Dex language simplifies array math for machine learning
LLVM-powered experimental language for array processing aims for an important corner of the math library space
What surgery taught me about the cloud
In the process of fixing my shoulder, I discovered some lessons for all enterprises regarding the effective integration of information
A2ML project automates AutoML
Common Python API for cloud-based AutoML services would allow data scientists to train their data sets against multiple AutoML models
The best open source software of 2019
InfoWorld recognizes the leading open source projects for software development, cloud computing, data analytics, and machine learning
AI gets real (sort of) in the enterprise
Turns out AI isn’t magic pixie dust to sprinkle over legacy processes and legacy tech, but a fundamental rethinking of how to do business
Swift for TensorFlow aims for high-performance machine learning
Future plans for the project that brings Swift to machine learning include C++ interoperability, improved automatic differentiation, and support for distributed training
Artificial intelligence today: What’s hype and what’s real?
Two decades into the AI revolution, deep learning is becoming a standard part of the analytics toolkit. Here’s what it means
Inside AI ebook: Artificial intelligence in the enterprise
AI is having a profound effect on enterprises. But where do you begin? A variety of tools and techniques can help you get started on your own implementation. Download our 17-page guide on real-world artificial intelligence.
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
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
IBM Trusted AI toolkits for Python combat AI bias
IBM has released Python toolkits for identifying and mitigating against bias in training data and machine learning models
Deep learning frameworks: PyTorch vs. TensorFlow
If you actually need a deep learning model, PyTorch and TensorFlow are both good choices
Machine learning operations don’t belong with cloudops
Giving systems enabled with machine learning to the cloud operations team to manage is not only a mistake, it’s dangerous
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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