Written by Alexander Raginsky From time to time, you still come across someone with the opinion that Big Data is nothing more than a fad, which will be forgotten about soon enough. You might not expect to hear this from me, but they’re actually right. Well – half right, at least! As I’ve written before, I’m not actually a
Written by Alexander Raginsky These predictions were published by the International Institute for Analytics (IIA). They produced a nice infographics, featured below, and re-tweeted many times by various bloggers, using the hash tag #2015Analytics. Other interesting predictions include those by Tableau, those by Pivotal, as well as my own predictions. Here are IIA’s predictions for 2015, in plain text:
Written by Alexander Raginsky Big Data services offered in the cloud is nothing new. In the past years we have seen many Big Data vendors that have created Big Data solutions that can be accessed via the web to crunch and analyse your data. Recently however, we have seen the rise of a new type of offering: Big Data-as-a-Service
Written by Alexander Raginsky This course provides an introduction to the field of Natural Language Processing. It includes relevant background material in Linguistics, Mathematics, Statistics, and Computer Science. Some of the topics covered in the class are Text Similarity, Part of Speech Tagging, Parsing, Semantics, Question Answering, Sentiment Analysis, and Text Summarization. The course includes quizzes, programming assignments in
Written by Alexander Raginsky A pivot language is a third or intermediate language that can bridge the gap between language pairs. For example, if there are translations between English to French and the same English to Spanish available, through the pivot language English, translations between French and Spanish can be generated. The major drawback and concern of generated translations
Written by Alexander Raginsky Support vector machines (SVMs) use an approach based on constructing decision planes (lines). Such a plain (line) is built for separating objects belonging to different classes. Suppose we have two sets of objects: red and green ones. Sometimes it is possible to draw a line that separates red objects from green ones: See more at:
Written by Alexander Raginsky We’re living in a sea of information, bathing in a firehose of data from across our businesses. We know we need to use it, but the question is how? How can we get value from that information, and at the same time get ready for the faster, bigger, deeper streams that are going to come
Written by Alexander Raginsky Over the past few years, there have been talks about data management and administration of databases. It is indeed important for data to be managed properly for the best results. Businesses get to enjoy lots of benefits if they manage their data properly because data is an asset, and a very important one for that
Written by Alexander Raginsky In the near future, the following major trends are expected in Big Data analysis: Big Data technology will be based on a mixture of cloud and on-premises computing. Many corporations start migrating from in-house database infrastructures to cloud-based data warehouses. Distributed frameworks for data analytics like MapReduce are turning into distributed managers of resources and
Written by Alexander Raginsky Amazon.com is boosting its artificial-intelligence chops. The world’s largest retailer by market capitalization is rolling out its sophisticated big-data-crunching platform for developers in Europe, and is also hiring scientists for its research teams in New York and Berlin who specialize in getting machines to do things like make sales predictions and predict fraud. Machine learning
