Features and labels are crucial in machine learning. To ensure algorithms can process data, categories must be converted into numerical formats using techniques like one-hot encoding and ordinal encoding. This post provides an overview of both methods, explaining their workings and applications
Two fundamental building blocks of machine learning are features (input) and labels (output). This article explains what features and labels are, their different types, and how they are applied in various machine learning models.
Welcome to the first post of our series on understanding Convolution Neural Networks. In this series we'll explore the inner workings of CNNs, starting from the basics and gradually delving into advanced concepts.
Artificial intelligence (AI) has evolved from a theoretical concept to a transformative technology impacting various industries. This article guides you through the origins of AI, its initial interpretations, and its progression into machine learning (ML) and deep learning (DL). By understanding these foundational concepts, you'll be well-prepared to embark on practical projects and delve deeper into the dynamic world of AI and ML. Join me as we unravel the basics and set the stage for hands-on exploration in the fascinating field of artificial intelligence.
Discover the evolving world of machine learning methods in this article! From supervised to weakly supervised, weakly semi-supervised, and semi-supervised learning, uncover the unique benefits and applications of each approach. Whether you're just starting out or seeking to deepen your understanding, explore how these methods work and when to apply them. Let's dive in and unlock the potential of machine learning together!
Learn how machines understand images like us and explore different image tasks, from recognizing objects to understanding scenes.
Explore the essentials of manual image coregistration in our latest tutorial. From loading 3D MRI scans and highlighting misalignment with the checkerboard filter to performing precise manual adjustments and saving the final aligned images, we've got you covered every step of the way.
Ready to dive into image segmentation? In this tutorial, we'll guide you through manual, semi-automatic, and automatic techniques using 3D Slicer. Let's get started!
In the fourth tutorial of this series, delve into the art of overlaying images, essential for medical imaging practitioners to assess patient progress and treatment efficacy. Discover step-by-step guidance and explore diverse applications in this comprehensive walkthrough.
In our third tutorial, we read and analyze various image formats with 3D Slicer. Discover how to navigate NRRD, NIfTI, and DICOM files effortlessly, empowering yourself to advance in medical imaging with confidence.