An exploratory analysis project on the various machine learning algorithms that can be used for NLP tasks. The task was sentiment analysis of IMDB reviews; categorising the sentiment into either negative or positive. Various machine learning algorithms were implemented to check their accuracy on the dataset provided. Some of them are:
- Naive Bayes
- Neural Networks
- K Nearest Neighbours
- etc.
Furthermore, prior to the application of these machine learning algorithms NLP techniques were applied on the dataset to help with the training. Some of them are:
- TF-IDF
- Word Embeddings
- etc.
However, these algorithms were also tested without any NLP techniques to then compare the usefulness of the techniques. Consequently, this did lead to an improvement in the results provided by the algorithms.