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CodeSignal

Advanced Modeling for Text Classification

via CodeSignal

Overview

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

Syllabus

  • Lesson 1: Ensemble Methods in NLP: Mastering Bagging for Text Classification
    • 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
  • Lesson 2: Ensemble Methods in NLP: Mastering the Voting 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
  • Lesson 3: Boosting Text Classification Power with Gradient Boosting Classifier
    • 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
  • Lesson 4: Text Preprocessing for Deep Learning with TensorFlow
    • Adjusting Tokenizer Parameters
    • Tokenizer Text Processing Practice
    • Filling the Gaps in Text Preprocessing Code
    • Initiating the Tokenizer Process
    • Tokenizing Text Data with TensorFlow
  • Lesson 5: Understanding and Building Neural Networks for Text Classification
    • 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
  • Lesson 6: Mastering Text Classification with Simple RNNs in TensorFlow
    • 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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