├── README.md
└── TensorFlowTweetTextClassificationV1.ipynb


/README.md:
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 1 | # TextClassificationTensorFlowCNN
 2 | Let us look at how we can implement text classification with Tensorflow https://www.tensorflow.org/ TensorFlow is an end-to-end open source platform for machine learning. The dataset is from the Tweet Sentiment Extraction challenge from Kaggle(https://www.kaggle.com/c/tweet-sentiment-extraction/overview) We would implement text classification using a simple convolutional network developed using Tensorflow on tweet data to classify tweets as "positive","negative" or "neutral"
 3 | 
 4 | 
 5 | Pre-requisites
 6 | 
 7 | Python 3.5 or above
 8 | 
 9 | Jupyter
10 | 
11 | scikit-learn (https://github.com/scikit-learn/scikit-learn)
12 | 
13 | Pandas (https://pandas.pydata.org/)
14 | 
15 | Tensorflow GPU 2.1
16 | 
17 | Pydot
18 | 


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