Linear Regression and Logistic Regression in Python - Build predictive ML models with no coding or maths background. Linear Regression and Logistic Regression for beginners
Linear regression and logistic regression are two popular machine learning algorithms used for regression and classification tasks respectively. In Python, you can use the scikit-learn library to create, train, and test your first linear regression machine learning model 1. You can also implement logistic regression in Python with the StatsModels package
What you'll learn
- Learn how to solve real life problem using the Linear and Logistic Regression technique
- Preliminary analysis of data using Univariate and Bivariate analysis before running regression analysis
- Understand how to interpret the result of Linear and Logistic Regression model and translate them into actionable insight
- Indepth knowledge of data collection and data preprocessing for Linear and Logistic Regression problem
- Basic statistics using Numpy library in Python
- Data representation using Seaborn library in Python
- Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries of Python
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