Jul 18, 2022 · This guide will teach you some key machine learning best practices for solving text classification problems. Here’s what you’ll learn: The high-level, end-to-end workflow for …

Jul 18, 2022 · For text classification datasets, we experimented with one, two, and three-layer MLPs. Models with two layers performed well, and in some cases better than three-layer …

Apr 17, 2025 · Learn how a classification threshold can be set to convert a logistic regression model into a binary classification model, and how to use a confusion matrix to assess the four …

Jun 12, 2024 · We saw how to convert sample text data into numerical vectors. A similar process must be applied to the labels. We can simply convert labels into values in range [0, …

Mar 3, 2025 · Learn how to calculate three key classification metrics—accuracy, precision, recall—and how to choose the appropriate metric to evaluate a given binary classification model.

Apr 16, 2025 · Machine learning (ML) powers some of the most important technologies we use, from translation apps to autonomous vehicles. This course explains the core concepts behind …

Jun 12, 2024 · In this guide, we attempt to significantly simplify the process of selecting a text classification model. For a given dataset, our goal is to find the algorithm that achieves close …

Jun 12, 2024 · Now, it’s time to write our classification algorithm and train it. We will use TensorFlow with the tf.keras API for this. Building machine learning models with Keras is all …

Feb 26, 2025 · Imbalanced datasets sometimes don't contain enough minority class examples to train a model properly. That is, with so few positive labels, the model trains almost exclusively …

Apr 2, 2025 · For example, the following two machine learning models each perform binary classification: A model that determines whether email messages are spam (the positive class) …