Tags: data

Comprehensive Beginner’s Guide to Jupyter Notebooks for Data Science & Machine Learning

Jupyter Notebooks allow data scientists to create and share their documents, from codes to full blown reports. They help data scientists streamline their work and enable more productivity and easy collaboration. Due to these and several other reasons you will see below, Jupyter Notebooks are one of...
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Removing the Storage Bottleneck for AI

If the history of high performance computing has taught us anything, it is that we cannot focus too much on compute at the expense of storage and networking. Having all of the compute in the world doesn’t mean diddlysquat if the storage can’t get data to the compute elements – whatever they might...
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Here’s Why You Should Secure Your Etcd Deployment

Etcd, a key-value store and a core component of Kubernetes clusters, is used to store highly sensitive configuration data but is also easily left unprotected, as a developer recently found. Puerto Rican software developer Giovanni Collazo was looking into etcd, first developed by CoreOS, and...
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Deep Learning Scaling Is Predictable, Empirically

Deep learning scaling is predictable, empirically Hestness et al., arXiv, Dec.2017 With thanks to Nathan Benaich for highlighting this paper in his excellent summary of the AI world in 1Q18 This is a really wonderful study with far-reaching implications that could even impact company strategies in...
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The Decentralized Internet Is Here, With Some Glitches

Proponents as varied as privacy activists and marquee venture capitalists talk about the decentralized internet as a kind of digital Garden of Eden that can restore the freedom and good will of the internet's early days. The argument goes that big tech companies have locked up our data and minds...
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Understanding Feature Engineering (Part 1) — Continuous Numeric Data

Any intelligent system regardless of complexity needs to be powered by data. At the heart of any intelligent system, we have one or more algorithms based on machine learning, deep learning or statistical methods which consume this data to gather knowledge and provide intelligent insights over a...
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Fuzzing: An Old Testing Technique Comes of Age

Both proprietary and open source development tends to have more developers than testers. As a result, automated testing has become increasingly common. In the last year, fuzzing — testing with dummy or random data — has become particularly widespread, and its popularity seems likely to continue....
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Julia vs. Python: Julia Language Rises for Data Science

Python has turned into a data science and machine learning mainstay, while Julia was built from the ground up to do the job. Of the many use cases Python covers, data analytics has become perhaps the biggest and most significant. The Python ecosystem is loaded with libraries, tools, and...
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HPC Storage Grows Cloudier, Flashier

Organizations running high performance computing (HPC) workloads are increasingly seeking out cloud-based storage solutions and speedy flash-enabled systems to help them cope with growing complexity and the sheer amounts of data they are managing nowadays, according to new research from DataDirect...
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Tech Giants Are Using Open Source Frameworks to Dominate the AI Community

Research plays a crucial role in the AI movement, and tech giants have to do everything in their power to seem viable to the AI community. AI is mostly based on research advances and state-of-the-art technology, which is advancing very quickly. Therefore, there is no business need to make closed...
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