In this section, we explore the power of visualization tools and techniques to gain meaningful insights into the characteristics and patterns of image data. Using Python libraries such as Matplotlib …
Visualizing image data using Matplotlib in Python – Exploring Image Data Read MoreIn this chapter, we will learn how to explore image data using various packages and libraries in Python. We will also see how to visualize images using Matplotlib and analyze …
Technical requirements – Exploring Image Data Read MoreIn summary, the line cluster_mask = (kmeans_model.labels_ == cluster_idx) creates a mask that helps you filter and select the data points in a specific cluster based on their assigned cluster …
Using k-means clustering to label regression data – Labeling Data for Regression-2 Read MoreIn this section, we are going to use the unsupervised K-means clustering method to label the regression data. We use K-means to cluster data points into groups or clusters based …
Using k-means clustering to label regression data – Labeling Data for Regression-1 Read MoreIn this code snippet, we’re building and training a linear regression model using the labeled data. First, we import the LinearRegression class from the sklearn.linear_model library. Then, we create an …
Pseudo-labeling – Labeling Data for Regression-2 Read MoreIn this section, we are going to generate house price labels using summary statistics of a small set of available labeled housing price data. This is useful in real-world projects …
Using summary statistics to generate housing price labels – Labeling Data for Regression Read MoreHere, pairwise_distances from scikit-learn is used to calculate the distances between cluster centers (inter-cluster distances). The result is a matrix where the element at position (i, j) represents the distance …
What is unsupervised learning? – Labeling Data for Classification-2 Read MoreUnsupervised learning is a category of machine learning where the algorithm is tasked with discovering patterns, structures, or relationships within a dataset without explicit guidance or labeled outputs. In other …
What is unsupervised learning? – Labeling Data for Classification-1 Read MoreL_train is passed to the label model to predict the labels, as follows:X[‘Labels’] = label_model.predict(L=L_train) We get the following result: Figure 2.4 – Probabilistic labels As we have seen, we …
Predicting labels – Labeling Data for Classification Read MoreHours per week rule function The hours per week rule function is used to check whether the working hours per week of the person is greater than 40; if so, …
Creating a label model – Labeling Data for Classification Read More