What's included

• Project Documentation

  Comprehensive documentation outlining the project scope, objectives, and methodology used in the NLP analysis. This can include details on algorithms chosen, models implemented, and any specific techniques applied.

• Data Preprocessing Report

  A report detailing the steps taken to preprocess and clean the raw data for analysis. This may involve tasks such as tokenization, stemming, and handling missing data.

• Exploratory Data Analysis (EDA)

  Description: Summary and visualizations from exploratory data analysis, providing insights into the characteristics of the textual data before NLP processing.

• NLP Model(s) Implementation

  Details on the development and implementation of NLP models, including the architecture, parameters, and training process.

• Sentiment Analysis Results

  If sentiment analysis is part of the project, deliver a report summarizing sentiment trends within the text data. This may include visualizations or sentiment scores.

• Codebase and Implementation Details

  Share the codebase used for the NLP analysis along with detailed instructions for reproducing the results. This may include code snippets, scripts, or links to relevant repositories.

• User Guides and Manuals

  If applicable, provide user guides or manuals for any tools, dashboards, or applications developed as part of the NLP project.