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Independent Probabilities

A fundamental probability rule is: P(A ∩ B) = P(A | B)P(B) = P(B | A)P(A) If events A and B are independent, meaning …

Peter Washington
1 min read

Neural Network Predictions

Let's say we want to predict the following neural network's output prediction when it has been trained with these weights: We …

Peter Washington
2 min read

Image Filtering

Filtering is one of the conventional image preprocessing steps. Various kinds of filtering can be done on an image during …

Sakar Ghimire
1 min read

Image Thresholding

Thresholding is a basic image operation. During segmentation, we first seperate pixels into two or more categories. Basically, we can classify pixels …

Sakar Ghimire
1 min read

Image Subtraction

Image subtraction is the process where value of pixels of an image is subtracted from another image. This results in …

Sakar Ghimire
1 min read

Hyperparameter Tuning

Hyperparameters control the learning process of a model by determining the network structure and training. Hyperparameter tuning is the process …

Akhil Chaudhary
3 min read

Independent Events in probability

Two events are said to independent if the occurance of one event does not affect the occurence of the other event. …

Sharad Dubey
2 min read

The Convolution Operator

Let's say that you want to detect features of a certain group of objects or class in other words. The features …

Arsalan Wasim
2 min read

Activation Functions

A neural network would essentially be a weighted linear combination of inputs that can capture linear, simpler patterns in the …

Akhil Chaudhary
8 min read

K Nearest Neighbors Algorithm

KNN is one of the simplest supervised learning algorithm that makes predictions for a new data point. The KNN algorithm …

AHMAD SAEED
6 min read

Softmax Function

The softmax function is a special case of the logistic function, where it is applied to a multi-class problem. It …

Akhil Chaudhary
3 min read

ReLU Activation

A neural network is a weighted linear combination of inputs without any activation. An activation function introduces non-linearity in the …

Akhil Chaudhary
3 min read

ROC Curve

The Receiver Operating Characteristics (ROC) curve is a performance metric for classification tasks at various classification thresholds. The ROC curve …

Akhil Chaudhary
2 min read

Image Data Augmentation

A convolutional neural network (CNN) is trained with images from a certain dataset, and the number of images in a …

Arsalan Wasim
3 min read

Convolutional Padding

Convolutional layers have the power to detect and learn various features in input images such as shapes, textures, and horizontal and vertical …

Arsalan Wasim
5 min read

Max Pooling

Convolutional layers are excellent for recording the precise location of features in the input image. A big problem of convolution neural networks is …

Arsalan Wasim
4 min read

Root Mean Squared Error

The Root Mean Squared Error (RMSE) is one of the most commonly used measures for evaluating the quality of a …

Akhil Chaudhary
3 min read

Precision and Recall

The performance of classification models is oftten measured by the accuracy score: the number of correct predictions over the total output …

Akhil Chaudhary
2 min read

Measures of Central Tendency

Introduction:  A measure of central tendency is a single number that attempts to define a dataset by spotting the central …

Sharad Dubey
2 min read

Inclusion-Exclusion Principle

The Inclusion-Exclusion principle states that for two events A and B, \(P(AUB) = P(A) + P(B) - P(A\cap B)\) This can easily …

Sharad Dubey
1 min read

K Nearest Neighbors

The k-nearest neighbors (k-NN) is a non-parametric, supervised learning algorithm that can be used to solve both regression and classification …

Akhil Chaudhary
3 min read

k-Means Clustering

Clustering data points together is one of the most common ways to analyze and understand unlabeled data. It identifies subgroups …

Akhil Chaudhary
6 min read

F1 Score

Several metrics can be used to evaluate the performance of a binary classifier. Accuracy is the simplest of all and …

Akhil Chaudhary
2 min read

Image Translation

The translation of an image is the process of moving or relocating of an image or object from one location …

Sakar Ghimire
1 min read

Measuring your Regression Model's Performance

When you develop any machine learning model, it is crucial to measure the performance of this model. Several differentt methods are …

Sharad Dubey
1 min read

Linear Regression Intuition

Imagine that you have recorded the hours spent studying for an exam and the score on the exam for several …

peterwashington
5 min read

What is a Line of Best Fit?

How does linear regression find this line of best fit given the data points? First, let’s get more formal about …

peterwashington
8 min read

Classification Intuition

The basic structure for classification is this: We take input data, feed it into one of many possible classification methods, …

peterwashington
5 min read

Image Dithering

Image Dithering is a process of adding some noise to an image. This noise can be used to randomize the quantization error. …

Sakar Ghimire
1 min read

Gaussian Distribution

The Gaussian distribution is a bell-shaped curve in which the values are supposed to obey a normal distribution with a corresponding …

Junaid Ahmed
1 min read
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