gold price detection using data mining I have dataset of gold prices and after modifying and some preprocessing i ended up with dataframe below: 

There is 50,000 record in dataset and all columns expect date are int type and date is datetime object.
i need to predict price per unit in some specific dates. but somehow i baffled with so many methods.

My question is what data mining algorithm/method is results good prediction for this kind of data ?
Recurrent Neural Network (RNN) are quite efficient at dealing with sequential information such as time-series.
LSTM (Long Short Term Memory) is a type of RNN that can learn long-term dependencies and overcome some problems that vanilla RNNs have.
If you want to try it on your problem, I'd suggest this tutorial on LSTM for time-series prediction.