What the heck is time-series data (and why do I need a time-series database)?

@tachyeonz : Here’s a riddle: what do self-driving Teslas, autonomous Wall Street trading algorithms, smart homes, transportation networks that fulfill lightning-fast same-day deliveries, and an open-data-publishing NYPD have in common?

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Streaming databases in realtime with MySQL, Debezium, and Kafka

@tachyeonz : Change data capture has been around for a while, but some recent developments in technology have given it new life. Notably, using Kafka as a backbone to stream your database data in realtime has become increasingly common.

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Timescale

@tachyeonz : How we scaled SQL Time-series workloads are different. TimescaleDB introduces special partitioning and distributed query optimizations to unlock new possibilities for SQL. Learn more Ease of use Query with standard SQL. Connect to tools that speak standard database connections.

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Overview of ‘online’ algorithm using Standard Deviation example

@tachyeonz : Here at Logentries we are constantly adding to the options for analysing log generated data. The query language ‘LEQL’ has a number of statistical functions and a recent addition has been the new Standard Deviation calculation.

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5 EBooks to Read Before Getting into A Machine Learning Career

@tachyeonz : Note that, while there are numerous machine learning ebooks available for free online, including many which are very well-known, I have opted to move past these “regulars” and seek out lesser-known and more niche options for readers.

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How to build and run your first deep learning network

@tachyeonz : Experiment with deep learning neural networks with Getting Started with Deep Learning using Keras and Python, an Oriole Online Tutorial by Mike Williams. When I first became interested in using deep learning for computer vision I found it hard to get started.

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Stanford Earth launches new Big Data course | The Dish

@tachyeonz : From west to east, this data visualization moves from true color to false color infrared to show healthier vegetation appearing in deeper hues of red than lighter or less vigorous vegetation.

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Visually Linking AI, Machine Learning, Deep Learning, Big Data and Data Science

@tachyeonz : What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning? Over the past few years AI has exploded, and especially since 2015. Much of that has to do with the wide availability of GPUs that make parallel processing ever faster, cheaper, and more powerful.

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Google teaches “AIs” to invent their own crypto and avoid eavesdropping

@tachyeonz : Google Brain has created two artificial intelligences that evolved their own cryptographic algorithm to protect their messages from a third AI, which was trying to evolve its own method to crack the AI-generated crypto.

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Tags : analytics, artificial intelligence, data science, deep learning, gans, generative adversarial, machine learning, neural networks, z

Published On:January 04, 2017 at 03:59PM

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How physicists analyze massive data: LHC + brain + ROOT = Higgs (33c3)

@tachyeonz : http://bit.ly/2i1HRQ3 are not computer scientists. But at CERN and worldwide, they need to analyze petabytes of data, efficiently. Since more than 20 years now, ROOT helps them with interactive development of analysis algorithms (in the context of the experiments’ multi-

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Tags : analytics, big data, ccc, cern lhc, chaos computer club, data pipeline, data science, data visualisation, data visualization, demo, stream processing, videos, z

Published On:January 02, 2017 at 04:43PM

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Wetwear for Wires

@tachyeonz : The Mr. Robot television series has some real world imitators18 Sep What would Dave and Bill do? Probably not this15 Sep

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Tags : analytics, artificial intelligence, cyber security, data science, ics, iiot, infosec, iot, machine learning, z

Published On:January 01, 2017 at 10:07AM

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Variance, Clustering, and Density Estimation Revisited

@tachyeonz : We propose here a simple, robust and scalable technique to perform supervised clustering on numerical data. It can also be used for density estimation, and even to define a concept of variance that is scale-invariant. This is part of our general statistical framework for data science.

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Tags : algorithms, analytics, clustering, error, machine learning, noise, statistics, variance, z

Published On:July 05, 2016 at 10:22AM

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