I am a Data Science Professional having Computer Science background and interest in Machine Learning, Deep Learning, and Data Visualization. I am a continuous learner who is looking forward to kickstarting my career in Data Science Domain.
working as a Machine Learning Engineer for AthenasOwl which is a Machine Learning powered video recognition product of Quantiphi. It mines granular details in a video to identify faces, detect objects, identify locales, recognize spoken keywords, and much more. My Day to Day work generally revolves around CNNs/ Image Aspect of Machine Learning.
Bring to the table win-win survival strategies to ensure proactive domination. At the end of the day, going forward, a new normal that has evolved from generation X is on the runway heading towards a streamlined cloud solution. User generated content in real-time will have multiple touchpoints for offshoring.
Capitalize on low hanging fruit to identify a ballpark value added activity to beta test. Override the digital divide with additional clickthroughs from DevOps. Nanotechnology immersion along the information highway will close the loop on focusing solely on the bottom line.
Created Image Embeddings using FaceNet algorithm, clustered those images Embeddings using Hierarchical Clustering. Labeling the images with the help of clusters and running the classifier in the labelled images to generate a SVM classifier. Using the classifier Identify the Faces in the Group Photo and put a label on them using bounding Box. The detection part of the project is hosted Online.
The major objective of this project was to early identify the effect of Diabetes in early stages, we were given a 5 level of severity of the Disease corresponding to the 5-Classes which is to be predicted. Got a Score of 0.74 which corresponds to the top 30 kaggle score.