Cryptocurrencies have gained immense popularity in recent years as an emerging asset class, and their prices are known to be highly volatile. Predicting cryptocurrency is a difficult task due complex nature the absence of central authority. In this paper, our proposal employ Long Short-Term Memory (LSTM) networks, type deep learning technique forecast cryptocurrencies. We use historical price d...

The price of a new car in the industry is fixed by manufacturer with some additional costs incurred Government form taxes. So, customers buying can be assured money they invest to worthy. But, due increased prices cars and financial incapability buy them, used sales are on global increase. Therefore, there an urgent need for prediction system which effectively determines worthiness based multip...

Family farms play a role in economic development. Limited terms of land, water and capital resources, family farming is essentially characterized by its use labour. must choose which agricultural products to produce; however, they do not have the necessary tools for optimizing their decisions. Knowing will best prices at harvest important farmers. At this point, machine learning technology has ...

Accurate stock price prediction has an important role in investment. Because data are characterized by high frequency, nonlinearity, and long memory, predicting prices precisely is challenging. Various forecasting methods have been proposed, from classical time series to machine-learning-based methods, such as random forest (RF), recurrent neural network (RNN), convolutional (CNN), Long Short-T...