Are you ready to delve into the world of 3D imaging? Our guide walks you through the simple steps to install 3D Slicer, a versatile software tool renowned for its applications in medical imaging and beyond. Whether you’re a researcher, medical professional, or enthusiast, follow along to unleash the power of 3D Slicer and unlock new possibilities in visualization and analysis.
Download and Install 3D Slicer Read More »
In this post, we’ll explore the fundamental concepts of dataset splitting in machine learning. We’ll cover the definitions of train, validation, and test sets, the importance of splitting the dataset, different partitioning strategies, and tips for ensuring proper dataset splitting. Join us as we unravel the keys to effective model development and evaluation.
How To Choose Train Validation and Test Sets For Your Model? Read More »
In this post, we’ll explore how to prevent overfitting in your machine learning models using simple regularization techniques. Dive into controlling model complexity and improving generalization for better performance in real-world situations.
Regularization Techniques to Prevent Model Overfitting Read More »
Overfitting, underfitting, and a model’s capacity are critical concepts in deep learning, particularly in the context of training neural networks.
Overfitting, Underfitting and Model’s Capacity in Deep Learning Read More »
Loss Functions – Training a neural network is an optimization problem. The goal is to find parameters that minimize this
Loss Functions for Regression and Classification in Deep Learning Read More »
