Next Word Predictor

The next word predictor is an exciting feature that helps you type faster on your mobile phone. It predicts the next word in the context you want to type. It is a very useful tool for people who type often and make mistakes while typing. It can be leveraged for auto-suggestion features in messenger and search engine apps.

The next word predictor makes it easy for readers to understand what exactly you are trying for them to read about.

• Next word predictor is a very useful feature as it increases the readability of your content as well as makes it more understandable for readers.
• Saves time by reducing the number of typos and grammatical errors in your content.
• Modify source code to customize as per your requirements.

Instructions to Run

Follow the below instructions to run the solution.

1. Locate and open the 'Next Word Predictor.ipynb' notebook from the Jupyter Notebook browser window.
2. Execute cells in the notebook by selecting Cell --> Run All from the Menu bar.
3. Once all the cells of the notebook are executed, the last interactive cell (Customisation) will be active, there we can give the input data or we can give the input text in the variable 'text_seq' under the variable section.

Input

text_seq = "I'm gonna make him an offer he can't"

Output

['refuse', 'resist', 'take', 'deny', 'get']

Troubleshooting

1. If you encounter any error related to MS Visual C++, please install MS Visual Build tools
2. While running batch file, if you encounter Windows protection alert, select More info --> Run anyway.
3. During kit installer, if you encounter Windows security alert, click Allow.
4. If you encounter Memory Error, check if the available memory is sufficient and it is proportion to the size of the data being used. For our dataset, the minimum required memory is 8GB.

If your computer doesn't support standard commands from windows 10, you can follow the instructions below to finish the kit installation.

1. Click here to install python
2. Click here to download the repository
3. Extract the zip file and navigate to the directory 'next-word-prediction-main'
4. Open terminal in the extracted directory 'next-word-prediction-main'
5. Install dependencies by executing the command 'pip install -r requirements.txt'
6. Run the command ‘jupyter notebook’ and select the notebook ‘Next Word Predictor.ipynb’ on the browser window.

For a detailed tutorial on installing & executing the solution as well as learning resources including training & certification opportunities, please visit the OpenWeaver Community

Development Environment

VSCode and Jupyter Notebook are used for development and debugging. Jupyter Notebook is a web-based interactive environment often used for experiments, whereas VSCode is used to get a typical experience of IDE for developers. Jupyter Notebook is used for our development.

Exploratory Data Analysis

For extensive analysis and exploration of data, and to deal with arrays, these libraries are used. They are also used for performing scientific computation and data manipulation.

Text Mining

Libraries in this group are used for analysis and processing of unstructured natural language.

Machine Learning

The library offers state-of-the-art pre-trained models for Natural Language Processing (NLP).

Support

If you need help using this kit, you may reach us at the OpenWeaver Community.