Machine Learning

January 12, 2017
Introduction The best way to learn a new skill is by doing it! This article is meant to help R users enhance their set of skills and learn Python for data science (from scratch). After all, R and Python are the most important programming languages a data scientist must know. Python is a supremely powerful and a […]
January 5, 2017
Introduction Recruiters in the analytics/data science industry expect you to know at least two algorithms: Linear Regression and Logistic Regression. I believe you should have in-depth understanding of these algorithms. Let me tell you why. Due to their ease of interpretation, consultancy firms use these algorithms extensively. Startups are also catching up fast. As a result, in an […]
January 2, 2017
Introduction There exists a world for Machine Learning beyond R and Python! Machine Learning is a product of statistics, mathematics, and computer science. As a practice, it has grown phenomenally in the last few years. It has empowered companies to build products like recommendation engines, self driving cars etc. which were beyond imagination until a few years […]
December 28, 2016
Introduction Many people are pursuing data science as a career (to become a data scientist) choice these days. With the recent data deluge, companies are voraciously headhunting people who can handle, understand, analyze, and model data. Be it college graduates or experienced professionals, everyone is busy searching for the best courses or training material to become […]
December 22, 2016
Integrated Development Environment (IDE) An integrated development environment is an application which provides programmers and developers with basic tools to write and test software. In general, an IDE consists of an editor, a compiler (or interpreter), and a debugger which can be accessed through a graphic user interface(GUI). According to Wikipedia, “Python is a widely used […]
December 21, 2016
A 2-day experience at Societe Generale, Bengaluru Societe Generale, one of the largest banks in France, in collaboration with HackerEarth, organized Brainwaves, the annual hackathon at Bengaluru on November 12–13, 2016. The theme of the hackathon this year was “Machine Learning”. The hackathon had an online qualifier from where 85 top teams out of 2200 […]
December 20, 2016
Introduction Last week, we learned about Random Forest Algorithm. Now we know it helps us reduce a model's variance by building models on resampled data and thereby increases its generalization capability. Good! Now, you might be wondering, what to do next for increasing a model's prediction accuracy ? After all, an ideal model is one […]
December 19, 2016
Is it gonna rain today? Should I take my umbrella to the office or not? To know the answer to such questions we will just take out our phone and check the weather forecast. How is this done? There are computer models which use statistics to compare weather conditions from the past with the current […]
December 16, 2016
Times are changing and have been for a while now. In the world of STEM, women are no longer considered a “bad fit,” which is easily proved by the amazing number of brilliant women in the field today. Women are just as interested in finding out how things work, extracting insight from data, problem-solving, and […]
December 14, 2016
Introduction Treat "forests" well. Not for the sake of nature, but for solving problems too! Random Forest is one of the most versatile machine learning algorithms available today. With its built-in ensembling capacity, the task of building a decent generalized model (on any dataset) gets much easier. However, I've seen people using random forest as a […]