Pinned Repositories
Advanced-Statistics-Hypothesis-Analysis
To perform basic EDA, Statistics and perform Hypothesis Analysis on the given datasets.
Automatic-IT-Ticket-Assignment-NLP
To build an AI-based classifier model to assign the tickets to right functional groups by analyzing the given description
Basic-Statistics-pima-diabetes
To explore the given dataset for all basic statistics such as the distributions, correlations, outliers, missing values, etc.
Classifying-Silhouettes-of-vehicles-Unsupervised-learning
Unsupervised learning (PCA) to classify a given silhouette as one of three types of vehicle, using a set of features extracted from the silhouette
Ensemble-Techniques-Bank
Classification model to predict if the client will subscribe to a term deposit based on the given bank dataset
Featurization-Model-Selection-Tuning
Modeling of strength of high performance concrete using Machine Learning
Product-Recommendation-Systems
To build a recommendation system to recommend products to customers based on the their previous ratings for other products
Sarcasm-Detection-NLP
To build a model to detect whether a sentence is sarcastic or not, using Bidirectional LSTMs
Sentiment-Classification-using-NLP
To generate Word Embeddings and retrieve outputs of each layer with Keras based on the Sentiment Classification task
Supervised-Learning
To build a classification model to predict the likelihood of a liability customer buying personal loans.
Kavitha-Kothandaraman's Repositories
Kavitha-Kothandaraman/Automatic-IT-Ticket-Assignment-NLP
To build an AI-based classifier model to assign the tickets to right functional groups by analyzing the given description
Kavitha-Kothandaraman/Product-Recommendation-Systems
To build a recommendation system to recommend products to customers based on the their previous ratings for other products
Kavitha-Kothandaraman/Sarcasm-Detection-NLP
To build a model to detect whether a sentence is sarcastic or not, using Bidirectional LSTMs
Kavitha-Kothandaraman/Supervised-Learning
To build a classification model to predict the likelihood of a liability customer buying personal loans.
Kavitha-Kothandaraman/Advanced-Statistics-Hypothesis-Analysis
To perform basic EDA, Statistics and perform Hypothesis Analysis on the given datasets.
Kavitha-Kothandaraman/Basic-Statistics-pima-diabetes
To explore the given dataset for all basic statistics such as the distributions, correlations, outliers, missing values, etc.
Kavitha-Kothandaraman/Classifying-Silhouettes-of-vehicles-Unsupervised-learning
Unsupervised learning (PCA) to classify a given silhouette as one of three types of vehicle, using a set of features extracted from the silhouette
Kavitha-Kothandaraman/Ensemble-Techniques-Bank
Classification model to predict if the client will subscribe to a term deposit based on the given bank dataset
Kavitha-Kothandaraman/Featurization-Model-Selection-Tuning
Modeling of strength of high performance concrete using Machine Learning
Kavitha-Kothandaraman/Sentiment-Classification-using-NLP
To generate Word Embeddings and retrieve outputs of each layer with Keras based on the Sentiment Classification task