Illustrative introductions on dimension reduction
"What is your image on dimensions?"
....That might be a cheesy question to ask to reader of Data Science Blog, but most…Spiky cubes, Pac-Man walking, empty M&M's chocolate: curse of dimensionality
"Curse of dimensionality" means the difficulties of machine learning which arise when the dimension of data is higher. In…
Back propagation of LSTM: just get ready for the most tiresome part
First of all, the summary of this article is "please just download my Power Point slides and be patient, following the equations."…
How to develop digital products and solutions for industrial environments?
In this article, we substantiate why Data Science and Engineering should be introduced as new engineering discipline in the Product Lifecycle Management process.
Understanding LSTM forward propagation in two ways
*This article is only for the sake of understanding the equations in the second page of the paper named "LSTM: A Search Space…
Hypothesis Test for real problems
A statistical hypothesis is a belief made about a population parameter. This belief may or might not be right. In other words, hypothesis testing is a proper technique utilized by scientist to support or reject statistical hypotheses. The foremost ideal approach to decide if a statistical hypothesis is correct is examine the whole population.
Must-have Skills to Master Data Science
The need to process a massive amount of data sets is making Data Science the most-demanded job across diverse industry verticals.…
Process Mining mit Celonis - Artikelserie
Insgesamt stellt Celonis ein unabhängiges und leistungsstarkes Process Mining Tool bereit, wobei der Anwender die Wahl zwischen einer on-Premise-Lösung sowie einer Cloud-Lösung hat. Die „prebuild Process-Connectors“ und die vordefinierten Analysen können ein Process Mining Projekt signifikant beschleunigen und somit die Time-to-Value lukrativ verkürzen. Die Analyse Tools sind leicht bedienbar und schaffen dank integrierter Machine Learning Algorithmen Optimierungspotentiale.
AI Voice Assistants are the Next Revolution: How Prepared are You?
According to Jeff Bezos, Amazon CEO, he says we’re already living in the golden era of artificial intelligence as such where the voice assistant flagship already exists, i.e. Alexa.
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Data Leader Days: Die Spitzenmanager der Datenwirtschaft live und direkt
/0 Comments/in Data Science News, Gerneral, Uncategorized /by eventsAm 13./14. November 2019 finden in Berlin die fünften Data Leader Days statt. Kommen Sie direkt mit den Spitzenkräften der Datenwirtschaft in Kontakt und freuen Sie sich auf die besten Use-Cases, Live-Demos und Panels rund um Data und AI. Die Data Leader Days sind das erste Management-Forum für die Datenwirtschaft im deutschsprachigen Raum und senden […]
A Bird’s Eye View: How Machine Learning Can Help You Charge Your E-Scooters
/0 Comments/in Artificial Intelligence, Big Data, Business Intelligence, Data Mining, Data Science, Data Science Hack, Insights, Machine Learning, Main Category, Python, Tools, Visualization /by Perry JohnsonEver since I started using bike-sharing to get around in Seattle, I have become fascinated with geolocation data and the transportation sharing economy. When I saw this project leveraging the mobility data RESTful API from the Los Angeles Department of Transportation, I was eager to dive in and get my hands dirty building a data product […]
Closing the AI-skills gap with Upskilling
/2 Comments/in Carrier, Gerneral /by Michael LyammClosing the AI-skills gap with Upskilling Artificial Intelligent or as it is fancily referred as AI, has garnered huge popularity worldwide. And given the career prospects it has, it definitely should. Almost everyone interested in technology sector has them rushing towards it, especially young and motivated fresh computer science graduates. Compared to other IT-related jobs […]
Interview – Knowledge Graphs and Semantic Technologies
/0 Comments/in Events, Insights, Interviews /by Editorial Staff“It’s incredibly empowering when data that is clear and understood – what we call ‘beautiful data’ – is available to the data workforce.” Juan F. Sequeda is co-founder of Capsenta, a spin-off from his research, and Senior Director of Capsenta Labs. He is an expert on knowledge graphs, semantic web, semantic & graph data management and […]
Understanding Dropout and implementing it on MNIST dataset
/0 Comments/in Data Science Hack, Python, TensorFlow, Tutorial /by Sarthak BabbarOver-fitting is a major problem in deep learning and a plethora of techniques have been introduced to prevent it. One of the most effective one is called “dropout”. Let’s use the analogy of a person going to gym for understanding this. Let’s say the person going to gym mostly uses his dominant arm, say his […]
Interview: Does Business Intelligence benefit from Cloud Data Warehousing?
/0 Comments/in Big Data, Cloud, Data Engineering, Data Security, Data Warehousing, Database, Insights, Interviews, Sponsoring Partner Posts /by Benjamin AunkoferInterview with Ross Perez, Senior Director, Marketing EMEA at Snowflake Read this article in German: “Profitiert Business Intelligence vom Data Warehouse in der Cloud?” Does Business Intelligence benefit from Cloud Data Warehousing? Ross Perez is the Senior Director, Marketing EMEA at Snowflake. He leads the Snowflake marketing team in EMEA and is charged with starting […]
Allgemeines über Geodaten
/0 Comments/in Big Data, Business Analytics, Business Intelligence, Data Engineering, Data Mining, Data Science, Database, Insights, Main Category, Use Case, Use Cases, Visualization /by Christopher KippDieser Artikel ist der Auftakt in einer Artikelserie zum Thema “Geodatenanalyse”. Von den vielen Arten an Datensätzen, die öffentlich im Internet verfügbar sind, bin ich in letzter Zeit vermehrt über eine besonders interessante Gruppe gestolpert, die sich gleich für mehrere Zwecke nutzen lassen: Geodaten. Gerade in wirtschaftlicher Hinsicht bieten sich eine ganze Reihe von Anwendungsfällen, […]
Attribution Models in Marketing
/0 Comments/in Big Data, Business Analytics, Business Intelligence, Data Mining, Data Science, Insights, Machine Learning, Main Category, Predictive Analytics, Statistics, Use Case, Use Cases /by Barbara StaronAttribution Models A Business and Statistical Case INTRODUCTION A desire to understand the causal effect of campaigns on KPIs Advertising and marketing costs represent a huge and ever more growing part of the budget of companies. Studies have found out this share is as high as 10% and increases with the size of companies (CMO […]
Was der BREXIT für die Cloud-Strategie bedeutet
/0 Comments/in Cloud, Data Science News, Datacenter, Gerneral, Insights, Sponsoring Partner Posts /by Bob MugliaDatensouveränität wird nach dem Brexit eine der größten Herausforderungen für Unternehmen sein. Geschäftsführer sind sich der Bedeutung dessen bewusst und fürchten die Gefahr eines „Data cliff edge“, wenn die Trennung Großbritanniens von der EU endgültig beschlossene Sache sein wird. Ohne ein klares Gespür dafür zu haben, welche Vorschriften und Compliance-Anforderungen bald gelten werden, versuchen britische […]
Introduction to ROC Curve
/0 Comments/in Artificial Intelligence, Data Mining, Data Science, Deep Learning, Machine Learning, Main Category, Predictive Analytics /by rohitmishraThe abbreviation ROC stands for Receiver Operating Characteristic. Its main purpose is to illustrate the diagnostic ability of classifier as the discrimination threshold is varied. It was developed during World War II when Radar operators had to decide if the blip on the screen is an enemy target, a friendly ship or just a noise. […]