Why Are Artificial Neural Networks Important
Why are Artificial Neural Networks important in data science? Artificial Neural networks are an extremely complicated piece of research/technology being developed for decades. They use man-made computing power to try and replicate the way the human brain calculates, and
Here’s Why Machine Learning Data Catalogs are Becoming Popular
Why Machine Learning Data Catalogs (MLDCs) are becoming popular In part one of this blog post we had discussed what data catalogs are, and why there is an increase in their use by enterprises over the last two years. In this second and final part of that post, we look at
AI For Data Cleaning: How AI can Clean Your Data and Save Your Man Hours and Money
AI for Data Cleaning: How AI can Clean Your Data and Save Your Man Hours and Money Dirty data is the bane of the analytics industry. Almost every organization that deals with data have had to deal with some degree of unreliability in its numbers. Table of Contents What Is
Machine Learning In Data Analytics: How It Works For Your Business?
Machine Learning in Data Analytics: How It Works for Your Business? In this post, we will try and answer the question – how does machine learning in data analytics work for your business? In part one of this blog post, we looked at how artificial intelligence (AI) can hel
How Artificial Intelligence Turns Data into Useful Information
How Artificial Intelligence turns data into useful information? We are often asked – explain AI from the viewpoint of a data lifecycle, or just how does artificial intelligence (AI) convert data into output that`s beneficial to a business? Machine learning (ML), which ca
How Natural Language Processing is Helping Democratize Business Intelligence
A minuscule percentage of those in the business of providing BI solutions have adopted NLP and adapted it to generate results for Enterprise clients. While the figure may be small today, advancements in the field are bound to push the number up.
The State Of Natural Language Processing Today
Readers of this blog may have realized that Natural Language Processing (NLP) was missing from our ‘5 Data Analytical Trends To Watch For in 2018’ post. Our in-house team of predictive data analysts say it lost out to the other trends by a narrow margin. But that in no way takes away from the importance of NLP and its growing influence in the world of big data analytics. The loser by a whisker surely deserves an honorable mention, hence this 2-part post.
Human Behavior Prediction using Machine Learning Techniques
Customers leave behind an incomprehensible amount of data while they go about shopping. Making sense of that data and reacting in real time are the two things that will keep companies one-step ahead of their customers (and competition) in the present-day customer-centric world.
Building an effective What-If Analysis Model
Data analytics need not stop at just looking in the rear-view mirror. 'What-If' analysis offers organizations a way of forecasting the future, with historical facts as the base. But your scenario modeling must be made efficient for best results.