Sharanya
Manohar

NLP model pipeline for English-French, English-Dutch and English-German language translation using 't5' and 'marianMT' transformers

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Predicting spending of customers based on features like time spent on website, average time of sessions with personal stylist from the store etc.,Hence helping business to make improvements in gaining more loyal customers. The code is written using Scala.

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Preprocessing a traffic crashes dataset to analyze and deduce meaningful relations and visualizations that help in better understanding of the data.

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A website that aims at connecting people, local communities and restaurants who are willing to donate the excess food, with the needy and provide them food. The data is stored in a MySql database.

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A discord bot called 'Encourage bot' will perform certain tasks in discord when added to a discord server.Flask webserver service is used to keep the bot running in the background. UptimeRobot.com is used to ping the http address of the bot code every 5 mins.

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Using Logistic regression model with gradient descent from scratch to recognize hand written digits. The dataset used is the Optical Recognition of Handwritten Digits dataset.

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Building a prediction model for the Iris flower dataset, the Bank notes authentication dataset and the MNSIT handwritten digits dataset using K nearest neighbors classification.

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Scraping a specific page of Wikipedia to answer some questions regarding data collected. The data contains information on different countries and their respective past and future population estimates.

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Using Support vector machines(SVM) and Clustering on the wine quality dataset to learn the data and make accurate predictions.

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Machine learning model to classify the Fashion MNIST dataset. The Model is implemented using Convolutional Neural Networks and the Keras deep learning API.

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Coming soon.....

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Coming soon.....

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