Logistic Regression is a supervised classification algorithm that is used to predict the probability of a categorical dependent variable using a given set of independent variables. It is a predictive analysis algorithm and based on the concept of probability. The most common use of logistic regression models is in binary classification problems. Some…
Gradient Descent is an optimization algorithm used to find the values of the parameters of any function that minimizes the cost function. The average difference of the squares of all the predicted values of y and the actual values of y is called a Cost Function. It is also called…
Linear regression is a supervised machine learning algorithm used for modeling the relationship between a dependent variable and one or more independent variables by fitting a linear equation. I would like to say it is the starting point of anyone’s ML journey! Linear regression is the simplest and most widely…
There are the five major assumptions: 1. Linear relationship: There should be a linear and additive relationship between the dependent (Y) variable and the independent (X –> x1,x2,x3,…) variable(s). A linear relationship suggests that a change in response Y due to one unit change in x1 is constant, regardless of…
Now that you are all set to start with Git, here are some of the frequently used Git commands for your reference: git add Usage: git add [file] This command adds a file to the staging area. Usage: git add * This command adds one or more to the staging area. git…
Here are the basic steps to install Git and create a free GitHub account. Installing on Windows There are also a few ways to install Git on Windows. The most official build is available for download on the Git website. Just go to https://git-scm.com/download/win and the download will start automatically. Note that…
Git is a version control system. Version control is a system that records changes to a file or set of files over time so that you can recall specific versions later. A version control automatically tracks every minute change in your project and allows us to revert back to a…
Unsupervised learning is a class of ML where we do not have any clue about the target data. We have to approach the problem by clustering the given unlabeled data based on the relationship between the input variables. We have to analyze the data; find patterns and relationships among them….
Supervised learning is a class of ML where machines can learn through examples. The historical data set has both input and output (also called target or response) values. Based on the training data set, the machine already has some idea of what the target value would look like, which kind…
I will discuss the most popular machine learning algorithms. There are so many algorithms available and I categorized algorithms based on the learning style. Let’s take a look at four different learning styles in machine learning algorithms: Supervised Learning Unsupervised Learning Semi-supervised Learning Reinforcement Learning Here is the list of…