Introduction Data Science and Machine Learning are furtive, they go un-noticed but are present in all ways possible and everywhere. They contribute significantly in all t...
Building accurate models takes a great deal of time, resources, and technical ability. The biggest challenge? You almost never know what model or feature combination will...
In my previous posts, I compared model evaluation techniques using Statistical Tools & Tests and commonly used Classification and Clustering evaluation techniques In ...
Introduction IoT (Internet of Things) has not quite taken off yet as envisaged – Will the cloud overcome the shortcomings of IoT? I believe that the Cloud is t...
Article was originally published on author’s blog, here. Learning to use data visualization programs Imagine spending countless hours analyzing your data and findin...
Logistic Regression is a statistical approach which is used for the classification problems. In statistics, the logistic model (or logit model) is used to model the proba...
Knowing when and how to choose the right statistical hypothesis test is no mean feat. It can takes years of learning and practice before you get comfortable with it. Fort...
Summary: Python’s open-source and high-level nature, as well as its comprehensive libraries, make it the perfect fit to solve the numerous real-life ML challenges. The ...
Summary: Artificial General Intelligence (AGI) is still a ways off in the future but surprisingly there’s been very little conversation about how to measure if we’r...
Data is the new fuel- it drives businesses towards exponential growths. It has the power to transform operational and add intelligent insights with its immense potential....