NirmalRajEganathan

Insofe

Data Scientist

June 16, 2026 – Present

Predicting-Genres-From-Movies-Data

April 6, 2020 – April 6, 2020

Use the movies metadata file to predict the genres field.

Rossmann-Store-Sales

March 5, 2020 – March 5, 2020

Forecast sales using store, promotion, and competitor data

Twitter-Sentiment-Analysis

December 12, 2019 – December 12, 2019

The objective of this task is to detect hate speech in tweets. For the sake of simplicity, we say a tweet contains hate speech if it has a racist or sexist sentiment associated with it. So, the task is to classify racist or sexist tweets from other tweets. Formally, given a training sample of tweets and labels, where label '1' denotes the tweet is racist/sexist and label '0' denotes the tweet is not racist/sexist, your objective is to predict the labels on the test data set.

Human-Activity-Recognition-using-sensor-data-through-Deep-learning-Techniques

November 12, 2019 – November 22, 2019

Human activity recognition (HAR) is gaining importance due to wearables and sensors data associated with it. Different from traditional Pattern Recognition methods, deep learning can largely relieve the effort on designing features and can learn much more high-level and meaningful features by training an end-to-end neural network. You need to find the dataset from open resources which can provide you human activity data.

Robust-Model-For-Class-Imbalance

November 12, 2019 – November 12, 2019

There is no particular definition for imbalanced class of data. In general, data that is not balanced is called imbalanced. However, there are infinite possibility of imbalanced class of data. Usually, we do up-sampling or down-sampling of the imbalanced data and make it balanced before applying machine learning models. In both the cases, we lose information about that data set. In this project, we would like to investigate what are the best models through all possible imbalanced situation of a data set.