## Mathematical explanation for Linear Regression working

Suppose we are given a dataset Given is a Work vs Experience dataset of a company and the task is to predict the salary of… Read More »

Suppose we are given a dataset Given is a Work vs Experience dataset of a company and the task is to predict the salary of… Read More »

In linear regression, the model targets to get the best-fit regression line to predict the value of y based on the given input value (x).… Read More »

CNN is basically a model known to be Convolutional Neural Network and in the recent time it has gained a lot of popularity because of… Read More »

Linear Regression is a machine learning algorithm based on supervised learning. It performs a regression task. Regression models a target prediction value based on independent… Read More »

In machine learning, while working with scikit learn library, we need to save the trained models in a file and restore them in order to… Read More »

Binary image is a digital image that has only two possible value for each pixel – either 1 or 0, where 0 represents white and… Read More »

Thresholding is the simplest method of image segmentation and the most common way to convert a grayscale image to a binary image. In thresholding, we… Read More »

In MATLAB, an RGB image is basically a 3-D Image array ( M*N*3 ) of color pixel, where each color pixel is associated with three… Read More »

Many web applications allows users to submit files in a compressed format (usually zip file format) to reduce the size of the file that is… Read More »

Natural language processing (NLP) is an area of computer science and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular… Read More »

Prerequisites We will briefly summarize Linear Regression before implementing it using Tensorflow. Since we will not get into the details of either Linear Regression or… Read More »

Prerequisite – Frequent Item set in Data set (Association Rule Mining) Apriori algorithm is given by R. Agrawal and R. Srikant in 1994 for finding… Read More »

In machine learning, Support vector machine(SVM) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis. It is… Read More »

Suppose there are set of data points that needs to be grouped into several parts or clusters based on their similarity. In machine learning, this… Read More »

tf-idf stands for Term frequency-inverse document frequency. The tf-idf weight is a weight often used in information retrieval and text mining. Variations of the tf-idf… Read More »