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2024
Understanding Dropout Regularization in TensorFlow.js
Learn about dropout regularization in TensorFlow.js and how it prevents overfitting during model training. Explore its implementation and impact on deep learning models.
Using Pre-Trained Models for Transfer Learning in TensorFlow.js
Learn how to leverage pre-trained models in TensorFlow.js for transfer learning on tabular data. This guide walks you through using a pre-trained model to improve performance on a structured dataset.
Implementing a Convolutional Neural Network (CNN) in TensorFlow.js Using Tabular Data
Learn how to implement a convolutional neural network (CNN) in TensorFlow.js using a tabular dataset. This step-by-step guide covers data preprocessing, model architecture, training, and evaluation for binary classification tasks.
Using TensorFlow.js for Time Series Analysis
Learn how to use TensorFlow.js for time series analysis, including data preprocessing, model architecture design, training, and forecasting. Explore advanced techniques for sequential data.
Evaluating the Performance of a TensorFlow.js Model Using Metrics
Understand how to evaluate the performance of a TensorFlow.js model using metrics like accuracy, precision, recall, and loss. Learn practical examples for different tasks.
Understanding Activation Functions in TensorFlow
Learn about activation functions in TensorFlow, their role in neural networks, and why they are crucial for enabling non-linear decision-making capabilities.