Predict equipment failure from data using classical machine learning approach
After several testing of algorithms we found the best one! We are able to predict correctly the target values with the given data.
Using machine learning to address barriers to adoption for solar power
A binary classifier that accounts for class imbalance to predict equipment failures given data from 107 sensors.
A SMS ChatBox/Alexa Integrated Tool with various helpful functionality
Exploratory data analysis, feature engineering, statistical inference, and market analysis for Mexican restaurant data set.
Assisted Restricted Access Intelligence - An AI based age restricted access to multilingual chatroom with personal chatbot assistance called Alfred.
A machine learning model to predict toothpaste prices that helps brands break into emerging markets
The idea of our project is to use stock price datasets from Yahoo Finance and design a program to find correlations between factors that affect stock prices and predict future stock prices using ML.
Binary classification of equipment failure as above- or below-ground based on the sensor data
Unbiased, unsupervised classification and ranking for tacos by treating all restaurants equally, giving small businesses better exposure.
What happens when a bunch of data science master's students are asked to work with a challenging data set? Data Pre-Processing/ EDA/ Model Evaluation/ Biases/ outliers/ Accuracy/ Visualization
We predict equipment failures using a simple model accurately and maintain interpretability of our results
A cross-platform app for data visualization of equipment failure prediction
Matchmaking Movies With the Stars
AirBNB commercial listings- A Novel Tagger and NLP the superhero to Ishwar's Secret model's rescue!
Ye!Pro is an web application that helps you to find out what best fit your taste. Based on Yelp’s data, we created an improved rating system calculated based on those who have similar tastes with you.
To build a model that predicts the toothpaste sale price based on the available data
Using social media data to create alpha signals
Capitalizing on ESG leading companies resilient beyond expectations
Fund management strategy that utilizes various datasets, including supply chains, social media data, news data, stock market time series data and others.
Want an interactive way to find the most cost effective actor or collaboration of them? In this app we provide an interface to build you a team of the best, or you can click right to the top.
Stock directionality using sentiment analysis and social media data
We are building the AI-Based Personal Career Counselor.