Data Science

How to Overcome the Curse of Dimensionality

Dimensionality reduction is an important technique to overcome the curse of dimensionality in data science and machine learning. As the number of predictors (or dimensions or features) in the dataset increase, it becomes computationally more expensiv...

K-Means Clustering: All You Need to Know

In machine learning, we are often in the realm of “function approximation”. That is, we have a certain ground-truth (y) and associated variables (X) and our aim is to use identify a function to wrap our variables in that does a good job in approx...

Interpreting and Visualizing AutoCorrelation

By Jithin J and Karthik Ravindra, Byte Academy Analyzing a Time Series Data needs special attention. Here, we would like to explore working with time series data and identify the effect of autocorrelation to come up with a more practical approach ...

Data Science vs Machine Learning – Exploring the two paradigms

Data Science is the coveted new career around the block but not many can define the exact role of a data scientist. Being a relatively new field of work with people signing up for the role from different backgrounds, data science as a discipline requ...

Implementing Machine Learning Models in JavaScript – TensorFlow

Web developers, rejoice! If you’ve been looking for a way to make a foray into the world of Machine Learning and Deep Learning, your learning curve has gotten that much more gentle with the introduction of the TensorFlow library in JavaScript. &...