Autor: Jörn Franke
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Secure Blockchain Analytics
Blockchain analytics has become a trending topic in recent years. This topic is of interest not only for public blockchains, such as Bitcoin or Ethereum and their Altcoins, but also for private/permissive blockchains based on various technologies. Nevertheless, there are many challenges involved, such as the large data volumes, the inefficient format for analytics, state…
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AI Applications and Systems for Deep Logic and Probabilistic Networks
This blog post describes the integration of deep learning, logic and probabilistic reasoning to enable advanced artificial intelligence tasks. The combination of completely different set of AI approaches will be one of the key advances to support AI driven business processes in the coming years. Furthermore, I describe challenges for operating such complex AI systems…
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GPUs, FPGAs, TPUs for Accelerating Intelligent Applications
Intelligent Applications are part of our every day life. One observes constant flow of new algorithms, models and machine learning applications. Some require ingesting a lot of data, some require applying a lot of compute resources and some address real time learning. Dedicated hardware capabilities can thus support some of those, but not all. Many…
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Collaborative Data Science: About Storing, Reusing, Composing and Deploying Machine Learning Models
Why is this important? Machine Learning has re-emerged in recent years as new Big Data platforms provide means to use them with more data, make them more complex as well as allowing combining several models to make an even more intelligent predictive/prescriptive analysis. This requires storing as well as exchaning machine learning models to enable…
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Automated Machine Learning (AutoML) and Big Data Platforms
Although machine learning exists already since decades, the typical data scientist – as you would call it today – would still have to go through a manual labor-intensive process of extracting the data, cleaning, feature extraction, regularization, training, finding the right model, testing, selecting and deploying it. Furthermore, for most machine learning scenarios you do…
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Big Data Analytics on Excel files using Hadoop/Hive/Flink/Spark
Today we have released HadoopOffice v1.1.0 with major enhancements: Based on the latest Apache POI 3.17 Apache Hive: Query Excel files and write tables to Excel files using the Hive Serde Apache Flink support for Flink Table API and Flink DataSource/DataSink Signing and verification of signatures of Excel files Example to use the HadoopOffice library…
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HadoopOffice – A Vision for the coming Years
HadoopOffice is already since more than a year available (first commit: 16.10.2016). Currently it supports Excel formats based on the Apache POI parsers/writers. Meanwhile a lot of functionality has been added, such as: Support for .xlsx and .xls formats – reading and writing Encryption/Decryption Support Support for Hadoop mapred.* and mapreduce.* APIs Support for Spark…
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HadoopCryptoLedger library a vision for the coming Years
The first commit of the HadoopCryptoLedger has been on 26th March of 2016. Since then a lot of new functionality has been added, such as support for major Big Data platforms including Hive / Flink / Spark. Furthermore, besides Bitcoin, Altcoins based on Bitcoin (e.g. Namecoin, Litecoin or Bitcoin Cash) and Ethereum (including Altcoins) have…
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Blockchain Consensus Algorithms – Proof of Anything?
Blockchains have been proven over the last years to be stable distributed ledger technologies. Stable refers to the fact that they can recover from attacks and/or bugs without compromising their assets. They are most commonly known for enabling transaction with virtual cryptocurrencies not issued by a central authority. Popular examples are Bitcoin and Ethereum. However,…