Semi-supervised learning is a type of machine learning where we use a combination of a large amount of unlabelled data and a small amount of labelled data to train the model. It is a hybrid approach between supervised learning and unsupervised learning. The basic difference between the two is that...
In today’s tutorial, we are going to learn to do file transfer using a TCP socket in the python3 programming language. This is the most basic file transfer program that we can do using a client-server architecture. Here, we are going to do the build a client and a server...
Convolutional Neural Network (CNN) has been most widely used in the field of computer vision and visual perception to solve multiple tasks such as image classification, semantic segmentation and many more. However, there is a need for approaches that can further improve its performance. One such approach is to add...
Deep neural networks have become popular due to their high performance in real-world applications, such as image classification, speech recognition, machine translation and many more. Over time deep neural networks are becoming deeper and deeper to solve more complex tasks. Adding more layers to a deep neural network can improve...
In this article, we are going to explore the two machine learning approaches – supervised and unsupervised learning. It is one of the most basic questions for data science beginners. Without a basic understanding of supervised and unsupervised learning, you cannot make any progress in the field of data science....
In this tutorial, you will learn to implement a TCP client-server program in the C programming language. Here, the client and server would exchange messages and communicate with each other in an interactive way. In addition, you will also learn about the client-server architecture and other related concepts. Table of...
Transfer Learning is a technique in machine learning where we reuse a pre-trained model to solve a different but related problem. It is one of the popular methods to train the deep neural network. It is generally used for image classification tasks where the amount of the dataset is small. ...
In this article, you will learn to perform person segmentation with DeepLabV3+ architecture on human images. Here, we will cover the entire process of image segmentation starting from data processing to evaluation. The entire code is written in Python programming language using TensorFlow 2.5 framework. Table of Content What is...
In our previous tutorials – cv2.imread() – Read Image using OpenCV Python and cv2.resize() – Resizing Image using OpenCV Python, we have learned to read and resize an image. We will now learn to save the array into an image file. For this, we are going to use cv2.imwrite() function...
In this tutorial, we will learn to resize an image using OpenCV in the Python programming language. For this, we are using the cv2.resize() function. OpenCV refers to Open Source Computer Vision library aimed at computer vision and machine learning. Image resizing refers to the process of changing the dimensions...
Hi Nikhil, Thanks for your dedications and explored very well. it is great helps to me. by Palani
ImportError: cannot import name 'load_data' from 'data' (C:\Users\Aravinda\anaconda3\lib\site-packages\data\__init__.py)
sir can you share a code of using squeeze and excitation network on custom CNN for a classification
Hey Nikhil, Very nice, to-the-point article on transfer learning. For a small size of dataset, an image augmentation along with…
Truly good blog short article and also valuable.