When our team's project scored first in the text subtask of this year's CALL Shared Task challenge, one of the key components of our success was careful preparation and cleaning of data. Data cleaning and preparation is the most critical first step in any AI project. As evidence shows, most data scientists spend most of their time Š ” Šup to 70% Š ” Šon cleaning data. In this … [Read more...] about Data Cleaning and Preprocessing for Beginners
Big Data
Guerrilla Analytics how to deliver analytics in the cut & thrust of business
Despite the plethora of good books on topics like Data Visualisation, very few cover how to deliver Guerrilla Analytics. By that, I mean beyond the theoretical ideals of Data Science textbooks. Beyond just the coding challenges of how to use R or Python to encode a question. Books that engage with real-world challenges for analysts. So, I am delighted to share one that I have … [Read more...] about Guerrilla Analytics how to deliver analytics in the cut & thrust of business
How to Build a Big Data Solution on Azure
Azure has made a point of prioritizing AI and analytics services, making it an appealing option for many looking to combine big data analysis and the benefits of cloud computing. With Azure, you can easily process massive amounts of data, both structured and unstructured, with real-time analytics and faster performance than you are likely to get with on-premise … [Read more...] about How to Build a Big Data Solution on Azure
Artificial Versus Human Intelligence: Learning Solutions In The Global Digital Economy
The digital economy has risen to prominence in discourse amongst think tanks, researchers and corporations, and has climbed to the top of government and business agenda. Increasingly and collectively, the world is recognising the digital economy as the chief driver of growth and development and is directing investment accordingly. Behind this digital push exists new … [Read more...] about Artificial Versus Human Intelligence: Learning Solutions In The Global Digital Economy
Data Mining and Engineering in Finance
This'marcus'evans'conference will drive initiatives to build an ecosystem of quality data for trade and risk, through embedding data quality efforts within the use of a central data repository, the application of synthetic and legacy data, the role and limitations of machine learning, and use of appropriate data visualisation techniques. As the volumes of data held by … [Read more...] about Data Mining and Engineering in Finance
