Data Science Professional who works on Object Recognition, Recommender systems and Classification and other fields...
Cleaning, transforming, merging and reshaping data frames inorder to use it for the desired purpose.
Visualizing the data using matplotlib, ggplot, seaborn and excel.
Develops various models according to the data and the objective - Prediction, Classification, Recommendation- using different algorithms - KNearest, Random Forest, Ensemble , SVM, Gradient Boosting, etc.
Architecting, training, and analyzing Neural Networks for applications ranging from Object detection (2D/3D), Image segmentation and other fields.
The Projects that I have worked on
Implemented a research paper on MaxMin Convolution to increase the accuracy to 92% along with Winograd architecture and Transfer learning on the CIFAR-10 dataset.
Using Singular Value Decomposition (SVD) in Python, created a system for recommending the movies for the users according to their preferences.
Created a machine learning model for predicting success rate of cold calls related to car insurance by selecting the best algorithm.