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Sentiment Analyse

Sentiment Analyse Neural Network Model

Can classificate given text as bad or good review.

Based on Spacy - for text embedding. Spacy contain big multilanguage dataset, and can build 300 dimensions vector on text entityes. Model build on Tensorflow - easy for build network model fraemwork, but possible for production requires additional tuning.

Requirements

Can be run in docker enviroment, or if you on linux:

  • Python - version 3.*
  • Spacy - version 2.*
  • Tensorflow - version 2.2 or bigger
  • Make - optional, all commands can be run manually
  • DVC - Git for machine learning

Development

If you on Windows, build and run in-Docker development enviroment

# Build image
make docker-build
# Start docker container, map volume on current folder and attach current console
make docker-console

If you not in docker you need load Spacy model

# Will load meduim size model, good for developement, but for production better load lardger
make spacy-load-md

Training

For train model just run

make train

It will load dataset and start training

Five main steps for build Neural Network

  1. Load dataset - split into train and test, and validation - which need for check training progress
  2. Normalise data - need normalise text to vector with constant size, for put it into first layer of network
  3. Build network model - stack layers for build model of network
  4. Train - put train data with correct hyperparameters
  5. Test - for insure correctness