In this paper, Artificial Neural Network (ANN) is used to predict trading signals like Strong Buy, Buy, Neutral, Strong Sell and Sell a total of 5 signals. The ANN outputs one of the trading signals based on the market data of cryptocurrencies. The ANN makes use of the candle-stick data along with additional data like Volume, Number of Trades, etc and technical indicators to predict the signals. The ANN is trained on multiple intervals of the market, i.e. 1 minute, 3 minutes, 5 minutes and so on up to 3 days in the intervals. Along with the market data, the paper also makes use of the news articles to better predict the trading signals, this is only used when the ANN predicts the Buy or Sell, and by using the news articles those Buy and Sell signals are converted to Strong Buy and Strong Sell respectively. The ANN was trained on 3 years of data, and Google’s BERT [1] model was trained on almost 1000 news article’s titles on topics related to cryptocurrencies and the model outputs whether it’s a positive or negative title. The accuracy of the ANN models for all the markets is in the range of 85 - 90% and the same accuracy is observed with the BERT model which is trained on the news article’s title.