How to Calculate Precision, Recall, F1, and More for Deep Learning Models
Precision Precision in machine learning is a metric used to evaluate the quality of a classification model. It measures the […]
Difference Between Classification and Regression in Machine Learning
Classification and regression are two common types of machine learning tasks. The main difference between classification and regression is the […]
VGG19 Pros and cons
VGG19 is a convolutional neural network (CNN) model that was developed by the Visual Geometry Group (VGG) at the University […]
Loss Functions in PyTorch Models
What are PyTorch Models? PyTorch is a popular open source machine learning framework that provides a number of tools and […]
Transfer Learning For Binary-Class Image Classification Using Pre-trained VGG-16
Problem: Transfer learning train a model on less data (<1000 images) and still getting good results (>80% accuracy) to demonstrate […]
Image Classification with Single Class dataset using VGG-16 Transfer Learning
Transfer learning generally refers to a process where a model trained on one problem is used in some way on […]
How to implement CapsuleNet on TensorFlow using Google Colab?
So now we all know that Capsule Networks (by Geoffrey Hinton) is shaking up the AI space and literature state […]
Classification of Objects in Photographs using Pre-trained VGG-16 Model
Convolutional neural networks are now capable of outperforming humans on some computer vision tasks, such as classifying images. That is, […]
How to fine-tune VGG-16 net using Keras on Google Colaboratory?
Training deep neural networks on CPUs is difficult. This tutorial will guide you on how to fine-tune VGG-16 net using […]
VGG-19 Convolutional Neural Network
VGG19 is a variant of the VGG model which in short consists of 19 layers (16 convolution layers, 3 Fully […]