- Works on Linux environment only.
- 1.0
- Neural network models
- SETUP
- MINIMUM SYSTEM REQUIREMNETS
- SOFTWARE/PLUG-IN DOWNLOADS
- GUIDELINES
- WARNINGS
- REPO OWNERS AND ADMINS
- Clone the repo at [TEXT ANALYTICS-DEEPLEARNING] (https://github.com/rahulr56/TextAnalytics-DeepLearning)
- Navigate to build directory and run build.sh
- The file ourNeuralNetDigitRecognition.py has to be run with PYTHON3.x
- MINIMUM 4GB RAM
- Intel core i3 or higher
- Download and install Anaconda
- NLTK and TEXTBLOB libraries
- preferred configuration: python 2.7.x with annaconda and nltk libraries
- By default, the application assumes that the test and training datasets are present in the DataSet directory.
- The file path can be adjusted in the loadFile function call.
- How to run:
python filename [amazonAnalysis.py or opticalRecogniser.py]
- Please note that 'python' in the command to run should include anaconda and nltk libraries.
- It is preferred to run the scripts on High Performance Clusters if the data set is huge.
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