Data Vault 2.0 - Flexible Datenmodellierung
Data Vault 2.0 ist ein Modellierungsansatz für Data Warehouse Systeme, der vor allem für Organisationen mit vielen Quellsystemen und sich häufig ändernden Daten sinnvoll ist.
CCNA vs. CCNP vs. CCIE Security Certification
Learn more about Cisco certifications and learn the difference between CCNA, CCNP and CCIE certifications to help you choose which path is right for you.
Big Data mit Hadoop und Map Reduce!
Hadoop ist ein Softwareframework, mit dem sich große Datenmengen auf verteilten Systemen schnell verarbeiten lassen. Es verfügt über Mechanismen, welche eine stabile und fehlertolerante Funktionalität sicherstellen, sodass das Tool für die Datenverarbeitung im Big Data Umfeld bestens geeignet ist. In diesen Fällen ist eine normale relationale Datenbank oft nicht ausreichend, um die unstrukturierten Datenmengen kostengünstig und effizient abzuspeichern.
How to maintain product quality with deep learning
Deep Learning helps companies to automate operative processes in many areas. Industrial companies in particular also benefit from product quality assurance. Computer Vision enables automation to identify scratches and cracks on product item surfaces.
Understanding Linear Regression with all Statistical Terms
Linear Regression Model - This article is about understanding the linear regression with all the statistical terms.
What…
Top 5 Email Verification and Validation APIs for your Product
If you have spent some time running a website or online business, you would be aware of the importance of emails.
What many…Variational Autoencoders
ariational autoencoders (VAEs) are a deep learning method to produce synthetic data (images, texts) by learning the latent representations of the training data. AGMs are sequential models and generate data based on previous data points by defining tractable conditionals.
How to choose the best pre-trained model for your Convolutional Neural Network?
Transfer Learning refers to the set of methods that allow the transfer of knowledge acquired from solving a given problem to another problem.
Transfer Learning has been very successful with the rise of Deep Learning.
Key Points on AI's Role In The Future Of Data Protection
Because AI can do a lot more than just collect and analyze data — it can also protect it. In this article, we’ll explain what the role of Artificial Intelligence is in the future of data protection.
Ein KI Projekt richtig umsetzen : So geht’s
Wir von DATANOMIQ und pixolution teilen unsere Erfahrungen aus Deep Learning Projekten, wo es vor allem um die Optimierung und Automatisierung von Unternehmensprozessen rund um visuelle Daten geht, etwa Bilder oder Videos.
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Data Vault 2.0 – Flexible Datenmodellierung
/0 Comments/in Big Data, Business Analytics, Business Intelligence, Data Engineering, Data Warehousing, Main Category /by Paula SellengData Vault 2.0 ist ein Modellierungsansatz für Data Warehouse Systeme, der vor allem für Organisationen mit vielen Quellsystemen und sich häufig ändernden Daten sinnvoll ist.
CCNA vs. CCNP vs. CCIE Security Certification
/0 Comments/in Certification / Training, Data Security, Education / Certification /by Shannon FlynnLearn more about Cisco certifications and learn the difference between CCNA, CCNP and CCIE certifications to help you choose which path is right for you.
Big Data mit Hadoop und Map Reduce!
/0 Comments/in Big Data, Data Engineering, Data Mining, Data Science, Main Category, Tool Introduction /by Niklas LangHadoop ist ein Softwareframework, mit dem sich große Datenmengen auf verteilten Systemen schnell verarbeiten lassen. Es verfügt über Mechanismen, welche eine stabile und fehlertolerante Funktionalität sicherstellen, sodass das Tool für die Datenverarbeitung im Big Data Umfeld bestens geeignet ist. In diesen Fällen ist eine normale relationale Datenbank oft nicht ausreichend, um die unstrukturierten Datenmengen kostengünstig und effizient abzuspeichern.
How to maintain product quality with deep learning
/0 Comments/in Artificial Intelligence, Data Science, Deep Learning, Machine Learning, Main Category, Use Case, Use Cases /by Benjamin AunkoferDeep Learning helps companies to automate operative processes in many areas. Industrial companies in particular also benefit from product quality assurance. Computer Vision enables automation to identify scratches and cracks on product item surfaces.
Understanding Linear Regression with all Statistical Terms
/0 Comments/in Data Science, Main Category /by M.Nithya LakshmiLinear Regression Model – This article is about understanding the linear regression with all the statistical terms. What is Regression Analysis? regression is an attempt to determine the relationship between one dependent and a series of other independent variables. Regression analysis is a form of predictive modelling technique which investigates the relationship between a dependent […]
Top 5 Email Verification and Validation APIs for your Product
/0 Comments/in Uncategorized /by Atreyee ChowdhuryIf you have spent some time running a website or online business, you would be aware of the importance of emails. What many see as a decadent communication medium still holds immense value for digital marketers. More than 330 billion emails are sent every day, even in 2022. While email marketing is very effective, it […]
Variational Autoencoders
/0 Comments/in Artificial Intelligence, Data Science, Deep Learning, Machine Learning, Main Category, Use Cases /by Sunil Yadavariational autoencoders (VAEs) are a deep learning method to produce synthetic data (images, texts) by learning the latent representations of the training data. AGMs are sequential models and generate data based on previous data points by defining tractable conditionals.
How to choose the best pre-trained model for your Convolutional Neural Network?
/0 Comments/in Uncategorized /by Mickael KomendyakTransfer Learning refers to the set of methods that allow the transfer of knowledge acquired from solving a given problem to another problem.
Transfer Learning has been very successful with the rise of Deep Learning.
Key Points on AI’s Role In The Future Of Data Protection
/0 Comments/in Artificial Intelligence, Data Security /by Lydia IsehBecause AI can do a lot more than just collect and analyze data — it can also protect it. In this article, we’ll explain what the role of Artificial Intelligence is in the future of data protection.
Ein KI Projekt richtig umsetzen : So geht’s
/0 Comments/in Artificial Intelligence, Data Science, Deep Learning, Machine Learning, Main Category /by Benjamin AunkoferWir von DATANOMIQ und pixolution teilen unsere Erfahrungen aus Deep Learning Projekten, wo es vor allem um die Optimierung und Automatisierung von Unternehmensprozessen rund um visuelle Daten geht, etwa Bilder oder Videos.