Text Classification with Natural Language Processing

Advanced Modeling for Text Classification

Explore advanced text classification techniques, including ensemble methods and deep learning, to enhance model performance using Python and TensorFlow.

Lessons and practices

Exploring the Last Documents and Categories

Finding Documents with Specific Category Count

Implement Bagging Classifier and Evaluate Model Performance

Bagging Classifier with Different Parameters Evaluation

Text Classification Using Bagging Classifier

Switch to Soft Voting in Classifier Ensemble

Implementing and Training a Voting Classifier

Incorporating Soft Voting in Ensemble Classifier Model

Creating the Voting Classifier Model

Building a Soft Voting Classifier from Scratch

Tuning Learning Rate for Gradient Boosting Classifier

Implementing and Training a Gradient Boosting Classifier

Setting Learning Rate and Making Predictions with GradientBoostingClassifier

Building a Gradient Boosting Classifier Model

Implementation of Gradient Boosting Classifier

Adjusting Tokenizer Parameters

Tokenizer Text Processing Practice

Filling the Gaps in Text Preprocessing Code

Initiating the Tokenizer Process

Tokenizing Text Data with TensorFlow

Improve Neural Network Performance with Additional Layer

Inserting the Missing Model Layer

Preparing the Tokenizer, Data, and Model

Extend the Neural Network Model

Creating and Training a Neural Network Model

Changing Activation Function in Dense Layer

Configuring SimpleRNN and Dense Layers in Model

Fill in the blanks: Building a Simple RNN with TensorFlow

Adding Layers to the RNN Model

Implement Simple RNN for Text Classification

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