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Predicting Bitcoin prices using a multi-dimensional LSTM and sentiment analysis.
AI Hack
We built models using different technologies
For AIhack2021
Predicting crop yield in the state of Illinois
Corn crop yields show monotonically increasing trend with disaster-related dips and evident geographical clustering. We develop an Attention-based DNN that can effectively predict negative events.
Regression and Classification on the Dataset to produce some unique insights
Cryptocurency price forecasting using random forests and LSTM NN.Using a simple random forest we are able to select the best features that will be taken into account for an advanced model.
High accuracy predictions with easy-to-gather data.
It's time to predict housing prices in Boston. Look through our project for fancy interactive maps!
Using longitude and latitude data with the Boston 1978 housing data set to predict various other values using a set of nested neural networks.
utilize the LSTM model to predict corp yield
Challlenging dataset!
Crop yield modeling is becoming a crucial tool for farmers and governments to make better decisions and stabilize the food supply.
How do we adress overpopulation and food shortages? We used satellite and corn yield data to make predictions that can help address these issues!
Data Analysis and machine learning with Boston Housing Market Data
We made a highly efficient triangular arbitrage strategy to generate profits and analysed it against the crypto-currency datasets
Random forest AI to predict the housing prices in Boston, MA
Need to predict yields? We got you covered
Forecast Volatility of Cryptocurrency Prices
Predicting price changes based on order book data and spot data
Crop yields are not exempt of suffering from the manifold damaging effects climate change. Extreme weather is more common now than ages ago, reason for which it is required to model such behaviour.
Predicts crop yield for county given temperature and EVI values in the current year
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