Every file/directory has three types of owners in Linux. The permissions for each of these 3 owners is represented in Numeric (group of octal representation) or symbolic representation. Symbolic Notation The Linux permissions are symbolically denoted similar to something like -rwxrw-w — or drw-rw-rwx. Here in symbolic notation, the first letter will…

A bird was I, flying out far and wide. As and when I wanted, to and from my eyrie. Dancing in the sunshine was I, as the dark clouds came by. Wary was I, of the looming obstacles. But within minutes, down was I, in the midst of a sandstorm, like a pushed down mind in anomaly. Losing hope minute by minute am I, Waiting for some help. Yearning am I, To fly out far and wide again. Originally published at https://ashwinsharmap.blogspot.com.

Life is a maze, in which all people race. Becoming first, by making someone last. Never caring, never helping, With selfishness and pride. Taking deep roots, in the foundation of their mind. Never trust them, cheaters are they. With the dark shadows of ego and jealousy, in their cold heart and brains. But never lose hope, Facing loses after loses. Ignore the traitors. Never mind the selfish world.

In this post, we will be discussing the basic steps in building a machine learning project. The process of building an ML project includes collecting the dataset, cleaning it, processing the data, training and testing of the model and deploying it. All the steps are explained briefly below. Data collection Data collection…

In this post, we will be looking into any() and all() functions in Python. First, let us discuss the any() function. 👉 any() The any() function takes an iterable as an argument: any(iterable). The iterable can be a list, tuple or dictionary. The any() function returns ‘True’ if any element in the…

As you may be knowing Logistic Regression is a Machine Learning algorithm. It is used for binary classification problems. We also have multiclass logistic regression, where we basically re-run the binary classification multiple times. It is a linear algorithm with a non-linear transform at the output. The input values are…

We have seen the basic operation of convolution in the previous post. Knowing Convolution Basics In this post, we will be discussing padding in Convolutional Neural Networks. Padding is the number of pixels that are added to an input image. …

In this article, we are going to learn about the grayscale image, colour image and the process of convolution. Grayscale image A grayscale image where the image is represented as only the shades of grey. The intensity of the various pixels of the image is denoted using the values from 0 to…

The gradient descent algorithm is an approach to find the minimum point or optimal solution for a given dataset. It follows the steepest descent approach. That is it moves in the negative gradient direction to find the local or global minima, starting out from a random point. …