5 AI Tricks to Grow Your Online Sales
The way people shop is currently changing. This only means that online stores need optimization to stay competitive and answer…
Process Mining mit MEHRWERK – Artikelserie
Dieser Artikel der Artikelserie Process Mining Tools beschäftigt sich mit dem Anbieter MEHRWERK. Das im Jahr 2008 gegründete…
Bag of Words: Convert text into vectors
In this blog, we will study about the model that represents and converts text to numbers i.e. the Bag of Words (BOW). The…
Multi-head attention mechanism: "queries", "keys", and "values," over and over again
This is the third article of my article series named "Instructions on Transformer for people outside NLP field, but with…
7 Ways To Advance Your Data Science Knowledge and Expertise
Image Source: Pexels
As a data scientist, your knowledge and expertise are what powers industries. Businesses of all sectors…
Five ways Data Science is used in Fintech
Data science experts process and act upon data that digital resources produce. In the fintech world, data comes from mobile…
Why Is Physical Security Vital for Data Security?
Modern businesses hold on to an increasing amount of sensitive and sometimes confidential data. As a result, they’ve had…
Hand Written Alphabet recognition Using Support Vector Machine
We have used image classification as an task in many cases, more often this has been done using an module like openCV in…
Data Security for Data Scientists & Co. - Infographic
Data becomes information and information becomes knowledge. For this reason, companies are nowadays also evaluated with regard…
In-memory Caching in Finance
/0 Comments/in InMemory, Insights, Main Category /by Edward HuskinBig data has been gradually creeping into a number of industries through the years, and it seems there are no exceptions when it comes to what type of business it plans to affect. Businesses, understandably, are scrambling to catch up to new technological developments and innovations in the areas of data processing, storage, and analytics. […]
Die Notwendigkeit von DevOps in Data Science
/0 Comments/in Data Engineering /by Lea KrauseDatenwissenschaft und maschinelles Lernen werden häufig mit Mathematik, Statistik, Algorithmen und Datenstreitigkeiten in Verbindung gebracht. Während diese Fähigkeiten für den Erfolg der Implementierung von maschinellem Lernen in einem Unternehmen von zentraler Bedeutung sind, gewinnt eine Funktion zunehmend an Bedeutung – DevOps for Data Science. DevOps umfasst die Bereitstellung der Infrastruktur, das Konfigurationsmanagement, die kontinuierliche Integration und […]
Positional encoding, residual connections, padding masks: covering the rest of Transformer components
/0 Comments/in Artificial Intelligence, Data Science, Data Science Hack, Deep Learning, Machine Learning, Main Category, Python, TensorFlow /by Yasuto TamuraThis is the fourth article of my article series named “Instructions on Transformer for people outside NLP field, but with examples of NLP.” 1 Wrapping points up so far This article series has already covered a great deal of the Transformer mechanism. Whether you have read my former articles or not, I bet you are […]
How Data Science Is Helping to Detect Child Abuse
/0 Comments/in Insights /by Luke SmithImage Source: pixabay.com There is no good way to begin a conversation about child abuse or neglect. It is a sad and oftentimes sickening topic. But the fact of the matter is it exists in our world today and frequently goes unnoticed or unreported, leaving many children and young adults to suffer. Of the nearly […]
Seq2seq models and simple attention mechanism: backbones of NLP tasks
/0 Comments/in Uncategorized /by Yasuto TamuraThis is the second article of my article series “Instructions on Transformer for people outside NLP field, but with examples of NLP.” 1 Machine translation and seq2seq models I think machine translation is one of the most iconic and commercialized tasks of NLP. With modern machine translation you can translate relatively complicated sentences, if you […]
How to Efficiently Manage Big Data
/1 Comment/in Big Data, Main Category /by Edward HuskinThe benefits of big data today can’t be ignored, especially since these benefits encompass industries. Despite the misconceptions around big data, it has shown potential in helping organizations move forward and adapt to an ever-changing market, where those that can’t respond appropriately or quickly enough are left behind. Data analytics is the name of the […]
Data Mining Process flow – Easy Understanding
/0 Comments/in Artificial Intelligence, Data Mining, Data Science, Deep Learning, Machine Learning, Main Category, Predictive Analytics, Statistics /by Ahamed Al Farabi1 Overview Development of computer processing power, network and automated software completely change and give new concept of each business. And data mining play the vital part to solve, finding the hidden patterns and relationship from large dataset with business by using sophisticated data analysis tools like methodology, method, process flow etc. On this paper, […]
Digital Data Taxes in China: How Would Big Tech Be Affected?
/1 Comment/in Data Science News /by Shannon FlynnAs 2020 came to a close, Chinese officials hinted at new data regulations on the horizon. Yao Qian, a Chinese securities official, stated that China should impose a digital data tax on some tech companies. Considering big tech’s prominent presence in the country, these taxes, if enacted, could have considerable impacts on the industry. The […]
On the difficulty of language: prerequisites for NLP with deep learning
/2 Comments/in Artificial Intelligence, Big Data, Data Mining, Data Science, Data Science Hack, Deep Learning, Machine Learning, Main Category, Natural Language Processing, Python, TensorFlow, Text Mining /by Yasuto TamuraThis is the first article of my article series “Instructions on Transformer for people outside NLP field, but with examples of NLP.” 1 Preface This section is virtually just my essay on language. You can skip this if you want to get down on more technical topic. As I do not study in natural language […]
Operational Data Store vs. Data Warehouse
/0 Comments/in Data Engineering, Data Warehousing /by Edward HuskinOne of the main problems with large amounts of data, especially in this age of data-driven tools and near-instant results, is how to store the data. With proper storage also comes the challenge of keeping the data updated, and this is the reason why organizations focus on solutions that will help make data processing faster […]