Sentiment Classification on IMDB dataset. Imdb dataset is a large dataset contains 50,000 movies' reviews and classified into 2 classes, Positive and Negative. So there are 3 phases of this project.
The Internet and technologies have changed the perspective of today's living known as digital world. In which everything is connected and communicating without any hindrance. People are communicating over the internet using social platforms and expressing their thoughts by sharing the blogs and articles, tweeting about any topics and expressing over posts. The technologies are adapting towards optimization over the huge amount of data. As these technologies growing exponentially the problems are arriving alongside. One of the major Problem is text classification for optimizing the search results. To address this problem there are multiple ways (i.e., sentiment analysis) to do that like machine learning and fuzzy rule systems and genetic algorithm.
Various Models have been implemented i.e.,
- LSTM,
- Bidirectional LSTM,
- Convolutional Neural Network
- BERT.
- Classical Machine Learninng Models
You can find the Notebooks, and PDF in the Directory Phase II
You can find the Notebooks, and PDF in the Directory Phase III
There are 2 versions that have been implemented
- V1 is the optimization of ANFIS Using Genetic Algortithm over different parameters i.e., number of Layer, params, optimizers, losses.
- V2 is the optimization of ANFIS Using Genetic Algortithm over different weights of the networks only.
You can find the Notebooks, and PDF in the Directory Phase IV
- 👋 Hi, I’m @musab-r
- 📫 You can reach me at https://www.linkedin.com/in/musabrasheed/