Complete guide from scratch It is better if you first read about Linear Regression and Logistic Regression. If not please go and explore them (You can refer to following links for help). Linear Regression Single And Multiple Dependent Variablesmedium.com Logistic Regression : All You wanna Know Complete implementation from scratchmedium.com Support Vector Machines is a very powerful classifier which can work both on linearly and non-linearly separable data…

classification of an image into different groups Image segmentation is a process of partitioning an image into multiple segments. The main motive behind this is to change the representation of image to more informative or we can focus on only those regions which are important. Applications It is used in medical…

From scratch explanation and implementation K-means Clustering is an unsupervised machine learning technique. It aims to partition n observations into k clusters. Kmeans algorithm is an iterative algorithm that tries to partition the dataset into K distinct non-overlapping subgroups (clusters) where each data point belongs to only one group

Complete implementation from scratch Logistic Regression is used to model probability of a certain class so that it can be assigned value of 0 or 1. It is a statistical and supervised learning model. It is a go-to method for binary classification. For instance you want to predict whether is…

Complete Implementation From Scratch Decision Tree is the most powerful and popular tool used for both classification and regression. It is like a flow-chart or we can a tree like model where every node depicts a feature while top node is called root node.

MACHINE LEARNING ALGORITHM KNN is a simple and intuitive Machine Learning Algorithm. It can be used for both classification and regression. It is a sort of Supervised Learning where we get both x and y. KNN is Non-Parametric which means it makes no assumptions so accuracy depends on the quality…

Single And Multiple Dependent Variables Regression basically means when you want to predict a continuous data. Regression Analysis is a form of predictive modelling technique which investigates relation between dependent and independent variable.

Machine Learning is an interdisciplinary field that uses statistics, probability, algorithms to learn from data and provide insights which can be used to build intelligent applications Joint Probability Distribution Probability of events A and B denoted byP(A and B) or P(A ∩ B)is the probability that events A and B both occur. P(A…

Using Numpy and Statistics Module Statistics is a collection of tools that you can use to get answers to important questions about data. We need statistics to help transform observations into information and to answer questions about samples of observations. To summarize → Statistics is a collection of tools developed…