A computer program's capacity to comprehend natural language, or human language as it is spoken and written, is known as natural language processing (NLP). It is a part of machine intelligence (AI). NLP is widely used for applications like NER(Named Entity Recognition), Text Classification, Text Generation, Text Mask Prediction etc. NLP requires a lot of tedious tasks to be done. It requires a lot of effort and time.
Project aims to provide assistance for the developers performing NLP modelling. The idea of creating a web interface that automates the processing of natural languages and performs NLP(Natural Language Processing) tasks.The interface would also perform modelling of the processed data. We will be making use of SOTA(State Of The Art) models.
This system performs the basic exploratory data analysis and text preprocessing required for NLP; in addition, it has the ability to create models through a web-based graphical user interface. It just requires a dataset as input, and our web GUI outputs a dataset based on the user's option of word or phrase analysis.The user does not need any prior coding knowledge.
In this part, we begin with data cleansing, then feature selection, lexical analysis (tokenization, stop word removal, n gram model, stemming, etc), followed by sentence level analysis (semantic, syntactic, pragmatic, and disclosure analysis). After finishing the textual analysis, we perform feature vectorization to convert the text data into a dense vector. The dense vector is then fed into the user-selected model. This section concludes with the creation of a user-friendly web-based interface that generates the desired output.
- Operating System : Windows / Linux / Mac
- IDE : Jupyter Notebook
- Python libraries : Pandas, Numpy, spacy, gensim, NLTK, langdetect and textblob
- Ram 6GB+
- Rom 128GB+
- Intel i3 or higher processor
NLP assist deployed here