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Commitd5a8a37

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added text classification tutorial
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‎README.md

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@@ -31,6 +31,7 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
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-###[Natural Language Processing](https://www.thepythoncode.com/topic/nlp)
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- [How to Build a Spam Classifier using Keras in Python](https://www.thepythoncode.com/article/build-spam-classifier-keras-python). ([code](machine-learning/nlp/spam-classifier))
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- [How to Build a Text Generator using Keras in Python](https://www.thepythoncode.com/article/text-generation-keras-python). ([code](machine-learning/nlp/text-generator))
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- [How to Perform Text Classification in Python using Tensorflow 2 and Keras](https://www.thepythoncode.com/article/text-classification-using-tensorflow-2-and-keras-in-python). ([code](machine-learning/nlp/text-classification))
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-###[Computer Vision](https://www.thepythoncode.com/topic/computer-vision)
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-[How to Detect Human Faces in Python using OpenCV](https://www.thepythoncode.com/article/detect-faces-opencv-python). ([code](machine-learning/face_detection))
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-[How to Make an Image Classifier in Python using Keras](https://www.thepythoncode.com/article/image-classification-keras-python). ([code](machine-learning/image-classifier))
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fromtensorflow.keras.callbacksimportTensorBoard
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importos
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fromparametersimport*
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fromutilsimportcreate_model,load_20_newsgroup_data
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# create these folders if they does not exist
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ifnotos.path.isdir("results"):
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os.mkdir("results")
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ifnotos.path.isdir("logs"):
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os.mkdir("logs")
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ifnotos.path.isdir("data"):
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os.mkdir("data")
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# dataset name, IMDB movie reviews dataset
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dataset_name="20_news_group"
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# get the unique model name based on hyper parameters on parameters.py
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model_name=get_model_name(dataset_name)
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# load the data
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data=load_20_newsgroup_data(N_WORDS,SEQUENCE_LENGTH,TEST_SIZE,oov_token=OOV_TOKEN)
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model=create_model(data["tokenizer"].word_index,units=UNITS,n_layers=N_LAYERS,
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cell=RNN_CELL,bidirectional=IS_BIDIRECTIONAL,embedding_size=EMBEDDING_SIZE,
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sequence_length=SEQUENCE_LENGTH,dropout=DROPOUT,
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loss=LOSS,optimizer=OPTIMIZER,output_length=data["y_train"][0].shape[0])
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model.summary()
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tensorboard=TensorBoard(log_dir=os.path.join("logs",model_name))
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history=model.fit(data["X_train"],data["y_train"],
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batch_size=BATCH_SIZE,
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epochs=EPOCHS,
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validation_data=(data["X_test"],data["y_test"]),
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callbacks=[tensorboard],
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verbose=1)
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model.save(os.path.join("results",model_name)+".h5")
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#[How to Perform Text Classification in Python using Tensorflow 2 and Keras](https://www.thepythoncode.com/article/text-classification-using-tensorflow-2-and-keras-in-python)
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To use this:
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-`pip3 install -r requirements.txt`
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- Please read[this tutorial](https://www.thepythoncode.com/article/text-classification-using-tensorflow-2-and-keras-in-python) before using this.
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- Tweak the hyperparameters in`parameters.py` and train the model.
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- For testing, consider using`test.py`

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