Aug 2020 - Present
Fennix Commerce
Data Science Intern
I am currently pursuing a Master's degree in Information Technology and Management, with focus in data science. I have prior experience of more than 3 years as Data Analyst with Cognizant Technology Solutions and an experience of Co-Founding a startup. I have worked on a variety of academic and competitive machine learning and deep learning projects, I will showcase some of my projects here, and link them to their GitHub repositories. During my free time, I like to play online competitive games and code. I enjoy working on HackerRank and leetcode challenges, which help sharpen my mind and improve on my problem solving skills.
Ashish Bisht
7740 mccallum blvd 337
Dallas, Texas 75252 US
(682)234-5288
newbieeashish.github.io
Fennix Commerce
Data Science Intern
The University of Texas at Dallas
Master in Information Technology and Management
Cognizant Technology Solutions
Data Analyst
ELC
Co-Founder
Uttarakhand Technical University
B.Tech Electronics and Communication Engineering
This project is end to end implementation to predict different Architectural Heritage Elements using transfer learning and streamlit.
Machine LearningBuilt a predictive model using Ensembling Methods that helps E-commerce company set up a lowest-pricing model for products.
Machine LearningImplemented Deep Learning Model for predicting various Indian Dance Form, this was the part of the HackerEarth Competition
Deep Learning, Machine Learning/span>Created the Neural Network that generates a new, fake" TV script, based on patterns it recognizes.
Machine Learning, Deep LearningObjectives of ‘Plant Pathology Challenge’ are to train a model using images of training dataset to 1) Accurately classify a given image from testing dataset into different diseased category or a healthy leaf 2) Accurately distinguish between many diseases, sometimes more than one on a single leaf.
Machine Learning, Deep LearningA leading pet adoption agency is planing to create a virtual tour experience for their customers showcasing all animals that are available in their shelter. To enable this tour experience, you are required to build a machine learning model that determines type and breed of the animal based on it's physical attributes and other factors
Machine LearningLeet Code algorithms solutions written in Python
Data Structures, AlgorithmsThe aim of this notebook is to provide an example of how to train an NLP model to detect fake news. Fake news is becoming a bigger and bigger issue in society, with disinformation becoming more widely shared on social media. So, a model to detect and filter out such stories would help to regain a lot of trust in the news we consume. The dataset used is approx. 20,000 examples of both real and fake news stories respectively, consisting of a title, text, subject and date. This notebook will preprocess the text, use GloVe word embeddings to map each word to a numeric vector, then pass the text through an LSTM network. The network will then classify each example as real or fake.
Machine Learning, Deep Learning