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2024
Understanding Gradient Descent Optimization and Its Variants in TensorFlow.js
Learn the fundamentals of gradient descent optimization, including stochastic gradient descent and other variants, in the context of TensorFlow.js. Explore how these methods impact model training.
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.
Implementing a Feedforward Neural Network (FNN) in TensorFlow.js
Learn how to build a Feedforward Neural Network (FNN) using TensorFlow.js, focusing on defining the model architecture, training it, and making predictions.
Implementing a Basic Linear Regression Model in TensorFlow.js
Learn how to create a simple linear regression model using TensorFlow.js, focusing on core concepts such as defining the model, training, and making predictions.
Understanding the tf.data API in TensorFlow.js
Learn about the purpose of the tf.data API in TensorFlow.js and how it helps in handling input data for machine learning models efficiently.