InfoQ Homepage Deep Learning Content on InfoQ
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Face-api.js: JavaScript Face Recognition Leveraging TensorFlow.js
Face-api.js is a JavaScript API for face detection and face recognition in the browser implemented on top of the tensorflow.js core API, which implements a series of convolutional neural networks (CNNs), optimized for the web and for mobile devices.
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Electric Cloud Launches Predictive Analytics for DevOps
ElectricFlow DevOps Foresight uses deep learning to identify patterns in release pipelines, gauge the likelihood of software release success and make recommendations in order to incrementally improve pipeline performance and application quality.
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Apple Has Released Core ML 2
At WWDC Apple released Core ML 2: a new version of their machine learning SDK for iOS devices. The new release of Core ML should create an inference time speedup of 30% for apps developed using Core ML 2. An important new feature of the Core ML SDK is Create ML. Developers can create and train custom machine learning models on their mac.
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Q&A on IBM's Fabric for Deep Learning with Chief Architect of Watson
InfoQ caught up with Ruchir Puri, chief architect of Watson, regarding the Fabric for Deep Learning (FfDL).
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Tensorflow with Javascript Brings Deep Learning to the Browser
Google launched Tensorflow.js, a Javascript implementation of its open-source Tensorflow deep-learning framework during the recent TensorFlow Dev Summit 2018. Tensorflow.js enables training models directly in the browser by leveraging the WebGL JavaScript API for faster computations.
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Dataiku's Latest Release Integrates Deep-Learning for Computer Vision
Collaborative data science platform Dataiku's latest release of its Data Science Studio includes pre-trained deep learning models for image processing. The DSS platform implements each step of a data-science project from data-sourcing and visualization to production deployment. Its machine-learning module supports standard libraries and it integrates with Hadoop and multiple Spark engines.
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How Booking.com Uses Kubernetes for Machine Learning
Sahil Dua explained how Booking.com was able to scale machine learning (ML) models for recommending destinations and accommodation to their customers using Kubernetes, at the QCon London conference. In particular, he stressed how Kubernetes elasticity and resource starvation avoidance on containers helps them run computationally (and data) intensive, hard to parallelize, machine learning models.
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Microsoft Embeds Artificial Intelligence Platform in Windows 10 Update
The next Windows 10 update opens the way for the integration of artificial intelligence functionalities within Windows applications. Developers will be able to integrate pre-trained deep-learning models converted to the ONNX framework in their Windows applications.
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Facebook Releases Open Source "Detectron" Deep-Learning Library for Object Detection
Recent releases from Facebook and Google implement the most current deep-learning algorithms to take a crack at the challenging problem of machine object detection.
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Autonomous Vehicles Became Better at Predicting Lane-Changes
Researchers created an algorithm that allows self-driving cars to predict lane-changes of the surrounding cars. The system works by using a deep-learning technique called Long Short-Term Memories (LSTMs). Although the most likely scenario on the highway is that every car stays in its own lane, their algorithm was able to slightly improve on this baseline prediction.
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Q&A on Machine Learning and Kubernetes with David Aronchick of Google from Kubecon 2017
InfoQ caught up with David Aronchick, product manager at Google and contributor to Kubeflow about the synergy between Kubernetes and Machine Learning at Kubecon 2017.
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Machine Learning and Artificial Intelligence - Two Conferences to Attend in 2018
The IEEE publishes an annual list of the Top 10 Technology Trends for each upcoming year. Making the list for 2018 are multiple topics surrounding artificial intelligence and machine learning. Deep learning comes in as the IEEE hottest trend for 2018.
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Modern Big Data Pipelines over Kubernetes
Container management technologies like Kubernetes make it possible to implement modern big data pipelines. Eliran Bivas, senior big data architect at Iguazio, spoke at the recent KubeCon + CloudNativeCon North America 2017 Conference about big data pipelines and how Kubernetes can help develop them.
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Building GPU Accelerated Workflows with TensorFlow and Kubernetes
Daniel Whitenack spoke at the recent KubeCon + CloudNativeCon North America 2017 Conference about GPU based deep learning workflows using TensorFlow and Kubernetes technologies. He discussed the open source data pipeline framework Pachyderm.
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How Apple Does Realtime Recognition of Handwritten Chinese Characters
Apple details building on-device handwritten Chinese character recognition with convolutional-neural networks and image recognition.