It is one of the most widely known modeling techniques. Simple linear regression is useful for finding relationships between two continuous… — It is one of the most widely known modeling techniques. Simple linear regression is useful for finding relationships between two continuous variables. One is a predictor or independent variable and the other is a response or dependent variable. It looks for a statistical relationship but not a deterministic relationship.

Regression analysis is a form of predictive modeling technique which investigates the relationship between a target and predictor. This… — Regression analysis is a form of predictive modeling technique which investigates the relationship between a target and predictor. This technique is used for forecasting, time series modeling, and finding the causal effect relationship between the variables. Why do we use Regression Analysis?

Evaluating the Model is considered a core part of building an effective machine learning model. Evaluating the model allows us to ask… — Evaluating the Model is considered a core part of building an effective machine learning model. Evaluating the model allows us to ask important questions like How well is my model doing? Is it a useful model? Will training my model on more data improve its performance?

The most important part of a machine learning project is preparing the data. Data preparation is the process of cleaning and transforming… — The most important part of a machine learning project is preparing the data. Data preparation is the process of cleaning and transforming raw data before processing and analysis. …

Exploratory Data Analysis (EDA) is an approach for data analysis that employs a variety of techniques (mostly graphical) to — Exploratory Data Analysis (EDA) is an approach for data analysis that employs a variety of techniques (mostly graphical) to maximize insight into a data set; uncover underlying structure; extract important variables; detect outliers and anomalies; test underlying assumptions;