Net Promoter Score (NPS) is a customer loyalty metric used to determine the likelihood that a customer will return to a company's website or use their service again. Airbnb uses NPS extensively in measuring the customer loyalty, as a more effective measurement to determine the likelihood that a customer will return to book again or recommend the company to their friends.
Riley Newman, head of data science at Airbnb, recently published an article describing how the Californian startup defines and uses data science. He explains that data can be seen as the voice of the customers, and data science as an act of interpretation. He also details several initiatives that have been particularly important for scaling data science.
Facebook recently announced open sourcing hardware design for its custom designed Open Rack compatible hardware. Attributing advances in Machine Learning and Artificial Intelligence to richer data sets and more powerful GPU-based systems, Facebook is unveiling its next generation systems code-named “Big Sur”, after the synonymous location in California.
About the same time Google announced open sourcing TensorFlow, Microsoft has pushed to GitHub DMTK, a Distributed Machine Learning Toolkit. While Google has released a one-machine version of TensorFlow, DMTK runs on a cluster of machines.
TensorFlow is a machine learning library created by the Brain Team researchers at Google and now open sourced under the Apache License 2.0. TensorFlow is detailed in the whitepaper TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. The source code can be found on Google Git.
In theory the operations team determines what the thresholds for warnings and alerts should be. But in practice, the operations team often have no idea what these values should be. Using machine learning techniques such as adaptive thresholds, Splunk ITSI solves this problem.
Splunk opened their big data conference with an emphasis on “making machine data accessible, usable, and valuable to everyone”. This is a shift from their original focus: indexing arbitrary big data sources. Reasonably happy with their ability to process data, they want to ensure that developers, IT staff, and normal people have a way to actually use all of the data their company is collecting.
Any cloud provider that believes in data gravity is trying to make it easier to collect and store data in its facilities. To make data movement between cloud and on-premises endpoints easier, Microsoft recently announced the general availability of Azure Data Factory (ADF).
Flipboard recently reported on an in-house application of deep learning to scale up low-resolution images that illustrates the power and flexibility of this class of learning algorithms.
Under the name of Project Oxford, Microsoft has made available a set of RESTful APIs that aim to make it possible for developers to build apps that feature face recognition, speech processing, and other machine learning algorithms. Part of the Azure portfolio, the new APIs are currently in beta and free to use up to 5,000 call per month.
Facebook has open sourced a number of modules for faster training of neural networks on Torch.
A number of Google researchers and engineers presented their view on the technical debt of using machine learning at a NIPS workshop. They identified different aspects of technical debt and came to the conclusion that without proper care, using machine learning or complex data analysis in your company can induce new kinds of technical debt different from classical software engineering.
Google has announced a new CAPTCHA API which provides a No CAPTHA experience for most users.
Web Summit, one of the largest technology conferences in Europe opened up today. Famous people from the technology and business world are expected to talk, like Peter Thiel, Drew Houston and Anna Patterson.
Microsoft recently announced new machine learning capabilities for Microsoft Azure platform. Developers can also create their own web services and publish them to Azure Marketplace. Microsoft also announced availability of Apache Storm for Azure. Azure Stream Analytics, Data Factory and Event Hubs for Azure were all announced in the past few weeks by Microsoft. In this article we explore moreabout