We now have a mountain of data due to the constant flow of information from various social media sites. It is crucial to digest data and extract emotions or important elements from it. An approach that may help with this is sentiment analysis. There has to be an English-like system that can decipher regional languages like Hindi for sentiment analysis. Machine translation is one of various emotion identification methods; nonetheless, it incurs the cost of translating across languages. This research presents a Deep Belief Network–based method for sentiment analysis of Hindi data. When it comes to Hindi data, this neural network model outperforms the machine translation method. An improvement in performance may be achieved by combining sentiment analysis with deep learning [4]. This sentiment categorization is best handled by a deep belief network, one of many deep learning neural network models [5]. To categorise Hindi reviews as either favourable, bad, or neutral, this s