Name: Arti Singh
Type: User
Company: Oracle America Inc.
Bio: 9+ years of experience as a Full Stack Software Engineer with expertise in Machine Learning, GenAI, and DevOps, adept at architecting, designing, implementing.
Location: DMV Area
Blog: https://www.linkedin.com/in/artisingh0913
Arti Singh's Projects
Data Preprocessing and visualization. Establishing relationship among variable if any.
Web Dev workshop
Reinforcement learning resources curated
Machine Learning Project - Implemented a machine learning recommender model, which maps a career question from some seeker to appropriate corps.
Curated list of Python resources for data science.
Exploratory Data analysis over NYC Recycling data provided by Booz Allen Hamilton for the challenge and build a predictive model to target zone in need of attention to increase recycling diversion rate.
Interactive tutorial on the Forward-Backward Expectation Maximization algorithm
Minimalistic gridworld package for OpenAI Gym
WIP.. My quick reference notes for software engineering interviews- data structures, and algorithms
Source code accompanying O'Reilly book: Machine Learning Design Patterns
This project aims to implement a model to detect toxicity in an online conversation. The model solves some of the significant challenges related to the field. We implemented the model in three phases: preprocessing of data, creation of feature vectors like TFIDF, Word2Vec and Doc2Vec, algorithms and evaluation metrics. Further, we optimized our output by working and experimenting with various features and models like SVM, Logistic Regression, Naive Bayes and Neural Network . We created a baseline model using SVM for our binary classification task to use it as a standard to compare our future models implementation. By making a comparison over these predictive models for the macro-average precision, recall and F1 score, we achieved a higher F1 score for CNN model over bigram computation. Our word-level CNN model out-performed all the other models including the Logistic Regression using TFIDF, Gensim Doc2Vec and other Neural network models.
RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code