Supercharging your image: Machine learning for photography applications
Advanced capabilities for image retrieval and processing are relatively new and powered to a large extent by advances in machine learning technology. We present a brief history of this space, and share the story of how Shutterstock has embraced this technology and what it does for them.
Read More →Will the real Elon Musk please stand up? Autonomous bots and synthesized speech in the public domain
The ability to create virtual clones that appear to think and talk like the real thing is very much real, as it has been done for Elon Musk and Barack Obama. We discuss techniques and potential with the people behind them.
Read More →CatBoost Machine Learning framework from Yandex boosts the range of AI
This is the year artificial intelligence (AI) was made great again. AI is all about machine learning, and machine learning is all about deep learning (DL), according to the hype. For connaisseurs like Yandex, there's more to AI than deep learning. CatBoost, the open source framework Yandex just released, aims to expand the range of what is possible in AI and what Yandex can do.
Read More →How machine learning is taking on online retail fraud
Fraud is one of the biggest causes of lost revenue for online retailers. Fraugster and Riskified, two startups that operate in this space, share their insights and methods for safeguarding online retail.
Read More →Alibaba: Building a retail ecosystem on data science, machine learning, and cloud
What does it take to compete in a global arena in which retail and cloud are increasingly intertwined? Domain-specific data science and machine learning for the masses, according to Alibaba.
Read More →Automating automation: a framework for developing and marketing deep learning models
Are you sold on the benefits of adding automation to your stack, but put off by the high entry barrier to this game? The NeoPulse Framework promises to ease the burden of developing Deep Learning models by introducing a number of interesting concepts.
Read More →Spark gets automation: Analyzing code and tuning clusters in production
Spark is the hottest big data tool around, and most Hadoop users are moving towards using it in production. Problem is, programming and tuning Spark is hard. But Pepperdata and Alpine Data bring solutions to lighten the load.
Read More →Artificial intelligence on Hadoop: Does it make sense?
MapR just announced QSS, a new offering that enables the training of complex deep learning algorithms. We take a look at what QSS can offer, and examine AI on the Hadoop landscape.
Read More →Caffe2: Deep learning with flexibility and scalability
As the AI landscape continues to evolve, a new version of the popular Caffe open source deep learning framework has been released. Caffe2 is backed by Facebook and features a wide array of partnerships to make it as flexible and scalable as possible. But is that enough to make Caffe2 a winner?
Read More →Language agnostic document processing: Finding relations using statistics, machine learning, and graphs
Would you like to be able to find related work regardless of domain or language, more efficiently than you ever thought possible? Omnity is out to help achieve this, using a mix of techniques.
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