I am a machine learning engineer passionate about cutting-edge technology and solving real-world problems. I am seeking an opportunity with a high growth-oriented organization to put in my best endeavors to translate innovative ideas into feasible projects by applying my technical skills improving the current scenario.
Implementing deep learning models like CNN, RNN, LSTM, and Spacy for NLP by mining large text data. Creating a software plugin for the test, report, and further investigations.
The objective of this project is to systemize NASA's patent and software management, by a set of automated machine learning tool. The Patent and software contain 15 categories each which further need to be divided into sub-categories for efficient classification. The useful features have been extracted from the documents and data provided by NASA as well as from some other data sources.
A balanced predictor, StackCBPred, which utilizes features, extracted from evolution-driven sequence profile, called the position-specific scoring matrix (PSSM) and several predicted structural properties of amino acids to effectively train a Stacking-based machine learning method for the accurate prediction of protein-carbohydrate binding sites.
To develop a predictor which utilizes sequential and structural properties of a protein sequence to effectively train a machine learning model. To pick the best combination of features, genetic algorithm was used.
An application to record the attendance automatically in a class. We used android-studio to host and react-native framework to control the application.
We performed detection of phishing websites through machine learning. We used the WEKA tool to clean the dataset and attribute selection.
To model a 4DOF mechanical arm to replicate human movements. Used a Kinect camera to resolve the video into skeletal form. Solved inverse kinematic problems for a model of arm with 4 directions of freedom. Passed these calculated angles to the model for replication.
GPA: 3.75
Percentage: 68%
Apart from being a machine-learning engineer, I enjoy most of my time being outdoors. I enjoy hiking and exploring new places.
When forced indoors, I follow a number of sci-fi and fantasy genre movies and television shows, and I spend a large amount of my free time exploring the latest technology advancements in the machine learning world.