Many statistical tests and procedures presume that the data is normal and has equal variances. These criteria frequently determine whether a researcher can apply a parametric or non-parametric test, frame hypotheses in specific ways, and so on. Bartlett's test is a prominent inferential statistics test that deals with data from a normal distribution. This post will show you how to run Bartlett's test in python. What is Bartlett’s test?  Bartlett's test is a statistical test that determines whether or not samples have equal variances. It is a hypothesis test that analyzes the variances of two or more samples to see ... Read More

Introduction The lifetime of a machine learning project is driven by the cloud service Azure Machine Learning. It can be used by machine learning experts, data scientists, including engineers in their daily workflows: Operate MLOps while training and deploying models. An open-source platform, including Pytorch, TensorFlow, sci-kit-learn, or a model we put together in Azure Machine Learning are both options. We may observe, retrain, and deploy models with the use of MLOp. In this article, we will be exploring Azure Machine learning and the usage. Cognitive Services and Azure Machine Learning Services Azure Table Storage is Microsoft's first offering with ... Read More

Introduction As the name implies, machine learning is the practice of creating computer algorithms that can learn from various types of data. In a broader definition, Arthur Samuel states that "machine learning is the scientific field which offers computers the power to learn and without being expressly taught." They are frequently used to deal with a variety of everyday difficulties. The algorithms, mathematical equations, and statistical calculations used in the past to perform Machine Learning tasks were all manually coded. As a result, the procedure was time-consuming, challenging, and ineffective. But because of a number of libraries, frameworks, and modules, ... Read More

Introduction Machine learning is indeed the idea that different technological tools, such as computers and tablets may understand anything dependent on coding along with other data. Although it looks like something from the future, most people use the internet on this level every day. Speaking recognition is a fantastic example of this. The technology is used by virtual personal assistants such as Siri and Alexa to read out reminders, respond to enquiries, and carry out tasks. More experts are considering employment as machine learning experts, as the sector grows. Making a project from start to finish is among the best ... Read More

Introduction: Simple Linear Regression The "Supervised Machine Learning" algorithm of regression is used to forecast continuous features. The simplest regression procedure, linear regression fits a linear equation or "best fit line" to the observed data in an effort to explain the connection between the dependent variable one and or more independent variables. There are two versions of linear regression depending on the number of characteristics used as input Multiple Linear Regression Simple Linear Regression In this article, we will be exploring the concept of Simple Linear Regression. Simple Linear Regression Model A form of regression method called simple ... Read More

Introduction The link between the dependent and independent variables, Y and X, is modelled as the nth degree of the polynomial in polynomial regression, a type of linear regression. In order to draw the best line using data points, this is done. Let’s explore more about the Polynomial regression in this article. Polynomial Regression One of the rare instances of multiple linear regression models is polynomial regression. In other words, it is a sort of linear regression when the dependent and independent variables have a curvilinear connection to one another. In the data, a polynomial connection is fitted. Additionally, by ... Read More

Introduction Since its inception in 1956, the term "artificial intelligence" (AI) has advanced significantly and grown in popularity. Salutations to the vast amounts of data, sophisticated algorithms, and advancements in processing power and storage. The development of Machine learning and artificial intelligence has increased the need for smart individuals to assist in solving urgent business difficulties more effectively and quickly. By 2024, the global AI employment market is predicted to reach $191 billion and add over 2 million new positions across all industries. With competitive pay, investing in professional development and knowing the best AI learning journey is undoubtedly the ... Read More

In this article, we are going to learn about the difference between – Training, Testing, and Validation sets Introduction Data splitting is one of the simplest preprocessing techniques we can use in a Machine Learning/Deep Learning task. The original dataset is split into subsets like training, test, and validation sets. One of the prime reasons this is done is to tackle the problem of overfitting. However, there are other benefits as well. Let's have a brief understanding of these terms and see how they are useful. Training Set The training set is used to fit or train the model. These ... Read More

In this article, let’s explore 7 such areas which are promising and booming in 2022 related to Artificial Intelligence. Introduction Over the last decade, we saw tremendous growth and development in Artificial Intelligence-related technologies in almost every domain and is still becoming more relevant in the current era or decade. There have been ground-breaking research in AI and ML which has changed the current scenario of how we pursue technology infused with machine intelligence.AI related technology has found application in every domain. To name a few like Healthcare, Cybersecurity, HR Processes, Space exploration, and many more. Trends in 2022 1. ... Read More

Introduction Regression Analysis is the most basic form of predictive analysis. In Statistics, linear regression is the approach of modeling the relationship between a scalar value and one or more explanatory variables. In Machine learning, Linear Regression is a supervised algorithm. Such an algorithm predicts a target value based on independent variables. More About Linear Regression and Regression Analysis In Linear Regression / Analysis the target is a real or continuous value like salary, BMI, etc. It is generally used to predict the relationship between a dependent and a bunch of independent variables. These models generally fit a linear equation, ... Read More