In this paper, we focus on the unidirectional translation of Kannada text to English text using Neural Machine Translation (NMT). From studies, we found that using Recurrent Neural Network (RNN) has been the most efficient way to perform machine translation.In this process we have used Sequence to Sequence (Seq2Seq) modelled dataset with the help of Encoder-Decoder Mechanism considering Long Short Term Memory (LSTM) as RNN unit. We have compared our result concerning to Statistical Machine Translation (SMT) and obtained a better Bi-Lingual Evaluation Study (BLEU) value, with an accuracy of 86.32%.