Words are the easiest way to express our feelings toward something and their proper analysis allows us to understand the sentiment that they are trying to convey. This paper presents a comprehensive approach toward sentiment analysis on movie reviews using deep learning techniques. The proposed methodology makes use of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks to automatically classify movie reviews into two categories: Positive sentiment and Negative Sentiment. The effectiveness of this approach is evaluated using the IMDB dataset, demonstrating high accuracy in sentiment classification. We have also made use of the Global Vectors for Word Representation (GloVe) for word embedding. Additionally, the paper discusses the preprocessing steps, methodology, model architecture, and performance evaluation metrics. The end result has also been compared with the results attained by our predecessors.