## Basics of Classification Model

For problems where the target variable takes continuous values, regression is used. However, classification deals…

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## Basics of Classification Model

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## Prediction Using Regression Model

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## Real-World Applications of Machine Learning

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## Introduction to Machine Learning

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## Data Science Project Life Cycle

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For problems where the target variable takes continuous values, regression is used. However, classification deals with a set of problems having target variables as discrete values i.e., some categories. There are various classification algorithms that deal with such problems. In this blog, we will discuss the basics of the classification problem. Learning Outcomes Classification is…

Machine learning is divided into two major categories: Supervised and Unsupervised. In supervised machine learning, there are major two categories: Regression and Classification. Regression reveals the relationship between variables and drives the success of machine learning. In this blog, we will discuss about regression problem. Learning Outcomes Regression analysis is a statistical method to model…

Machine Learning (ML) is a buzz word in today’s era with its application lying in day-to-day life. We make use of ML in our daily routine without being aware about it. So, let’s us know how and where we use ML and how dependent are we on these technology. Let us discuss each application with…

With the plethora of available and ever-growing data produced every day, Machine Learning (ML) has become a buzzword from the past few years. Now-a-days, ML is used anywhere and everywhere from healthcare to education to e-commerce. Learning Outcomes ML is the field of study that learns from data, update itself, and then apply knowledge without…

With the upcoming and ongoing plethora of projects using Artificial Intelligence (AI) since the year 2021, the job roles in the field of data science has increased multi-folds. To build any data science project, understanding the life cycle and different phases involved in the process is important. Learning Outcomes Data Science The most common…