DeepLearning

In machine learning, transfer learning is a technique where a pre-trained model, developed for one task, is reused as the starting point for another similar task. This can be a huge timesaver, as it reduces the time and computational resources required to train models from scratch. In this blog post, we will discuss how to use this technique to improve performance in image classification tasks, specifically using TensorFlowJS and the MobileNetV2 model....

Deep learning models have been successful in a wide range of applications, from image classification to natural language processing. However, training these models from scratch can require a large amount of labeled data and computational resources. Fortunately, there are many pre-trained deep learning models available that can be used for a variety of tasks, and the tf.keras.applications module provides an easy way to load these models in TensorFlow. In this blog post, we’ll look at a specific implementation of a function that loads pre-trained deep learning models using the tf....