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Understanding Dropout and implementing it on MNIST dataset
/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 […]
Interview: Does Business Intelligence benefit from Cloud Data Warehousing?
/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 […]
Attribution Models in Marketing
/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 […]
Introduction to ROC Curve
/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 […]
A Gentle Introduction to Precision and Recall.
/in Data Science, Main Category/by rohitmishraThe idea of this blog is to give an intuitive understanding of Precision and Recall for a binary classification problem. I will shy away from explaining it in a textbook […]
How is automation changing data science and machine learning?
/in Artificial Intelligence, Data Science, Main Category/by Danish WadhwaWe have come a long way since the introduction of data science and machine learning. The recent study has found that the volume of business data doubles in less than […]
A common trap when it comes to sampling from a population that intrinsically includes outliers
/in Business Analytics, Business Intelligence, Data Mining, Data Science, Data Science Hack, Main Category, R Statistics, Statistics/by Moussa El-ZaarahI will discuss a common fallacy concerning the conclusions drawn from calculating a sample mean and a sample standard deviation and more importantly how to avoid it. Suppose you draw […]
Business Intelligence Organizations
/in Carrier, Gerneral, Insights, Projectmanagement/by Benjamin AunkoferI am often asked how the Business Intelligence department should be set up and how it should interact and collaborate with other departments. First and foremost: There is no magic […]
Predictive maintenance in Semiconductor Industry: Part 1
/in Data Mining, Education / Certification, Machine Learning, Python, Use Case/by Aakash ChughThe process in the semiconductor industry is highly complicated and is normally under consistent observation via the monitoring of the signals coming from several sensors. Thus, it is important for […]
Fuzzy Matching mit dem Jaro-Winkler-Score zur Auswertung von Markenbekanntheit und Werbeerinnerung
/in Business Analytics, Data Mining, Data Science, Data Science Hack, Main Category, R Statistics, Text Mining/by Markus LangFür Unternehmen sind Markenbekanntheit und Werbeerinnerung wichtige Zielgrößen, denn anhand dieser lässt sich ableiten, ob Konsumenten ein Produkt einer Marke kaufen werden oder nicht. Zielgrößen wie diese werden von Marktforschungsinstituten […]