FAIL AND LEARN

Introduction: In the world of Linux, the power of customization is at your fingertips. One of the most powerful tools available to Linux users is the ability to create custom bash scripts. These scripts enable you to automate tasks, improve efficiency, and enhance your overall Linux experience. In this guide, we will explore the process of creating a custom bash script step by step, empowering you to harness the full potential of your Linux system. Here we are going to excute a command in script file on current directory. Understanding Bash: Bash, short for "Bourne Again SHell," is a command language interpreter that is widely used in Linux and Unix systems. It provides a command-line interface for users to interact with the operating system and execute commands. Bash scripts are simply text files containing a series of commands that can be executed as a single unit. Example :  Choosing a Text Editor: Before we dive into creating a bash script, it's essential to choose a

In this post we are gonna learn about the loss function in machine learning..The loss functions are essential in machine learning cause they are one who tells the algorithm if it makes mistake in prediction as wrong. so The Loss function/Cost Function are integral part of gradient descent and entropy calculations. Here we are gonna learn a bit about the different cost functions for different types of problems in machine learning. Mathematical Formula for Entropy : Consider a data set having a total number of N classes, then the entropy (E) can be determined with the formula below: Where: P i  = Probability of randomly selecting an example in class I; Entropy always lies between 0 and 1, however depending on the number of classes in the dataset, it can be greater than 1. But the high value of Let's understand it with an example where we have a dataset having three colors of fruits as red, green, and yellow. Suppose we have 2 red, 2 green, and 4 yellow observations throughout the dat

An image as simple as 200x200 is too much information for a Nueral network or a computer to understand. The machine learning algorithm like logic regression cannot process the 200x200 information of image, even if it does, the results may not be favourable at all. The accuracy of Nueral Network totally depend upon the input we've given it. So in machine learning the NN's preprocess the input and extract necessary information from the input. Something advance such as CONVOLUTION NUERAL NETWORK(CNN) perform feature extraction. In order to extract feature from an image we need convolution in image processing. Convolution is process in signal processing which is used to combine 2 signals. More about convolution in here . Here the convolution in computer vision is for feature extraction . We extract important details from image like Edges,noise removal,etc... The extraction of important data can be achieved by using a KERNAL .  The kernal method is used for sharping,embrose,smoo

In this post we are gonna learn about fourier transformation and implementation of Discrete fourier transformation in python. Why we need to use fourier transformation anyway...a normal periodic wave like sine wave has 3 characterstics like Phase,amplitude,frequency that tell us about the wave..it's easy and understandable but what if a wave is unperiodic like this ex. in this example it is not a periodic sinewave..so but an multiple frequencies of waves added together. Hence to analyse these kind of waves we need fourier transformation in signal processing. The fourier transforamation is applied in both Continous and Discrete waves . .In this we are gonna concentrate in DFT(Discrete fourier transformation)..and to visulalize the wave we are gonna use python(cause it's easy to use). we need the following python library to do this : 1.numpy    2.seaborn    3.mathplotlib     DFT(DISCRETE FOURIER TRANSFORMATION) It is applied to specifically discete signals. It is used to break th

  demorgan's Law                                                       

In this tutorials i'm gonna tell you all about the adc present in arduino famous boards like UNO,NANO,MINI....the atmega328p chips consist of the " 10-bit resolution adc " inside the uC. The type of adc is used in is  Successive approximation ADC . these are kind are slow but gives good resolution though. let's dig in registers of adc in atmega328p. To read analog input we need The reg " ADMUX ". T he adc reg have a Pin called AREF (adc reference voltage). The gives 10-bit number i.e 0-1023, 0-0V & 1023-5V. it measures using this formula       Vin = (Analog Ref * analogRead() ) / 1024 we need stable AREF voltage we can use internal 1.1V reference or we need to provide a stable voltage anywhere between 0.3V-5V externally. [NOTE: if ur are planning to provide external voltage to aref pin present on arduino uno,nano,mini, the recommended value is less than 5v to be safe on safe side cause the voltage of external 5v source may not be 5v exactly so if it i