Hands-On Machine Learning with Python [DAY- 21] Implementing Multiple Linear and Logistic Regression

#inzint
Welcome to Inzint's advanced training session on Python, Multiple Linear Regression, and Logistic Regression. This workshop is designed to provide you with in-depth knowledge and hands-on experience in implementing these powerful regression techniques using Python, enabling you to tackle complex data analysis and predictive modeling tasks effectively.
In this session, we’ll begin by exploring multiple linear regression, a method used to model the relationship between one dependent variable and multiple independent variables. You’ll learn how to set up and interpret multiple linear regression models, understand the assumptions behind the method, and evaluate the performance of your models. Through practical exercises, you'll gain proficiency in using Python libraries like NumPy, Pandas, and Scikit-Learn to implement multiple linear regression on real-world datasets.
Next, we’ll dive into logistic regression, a technique used for binary classification problems. You’ll learn the differences between linear and logistic regression, understand the logistic function, and discover how to apply logistic regression to predict categorical outcomes. We'll cover important concepts such as odds ratios, the interpretation of coefficients, and model evaluation metrics like confusion matrix, accuracy, precision, recall, and AUC-ROC.
Throughout the session, you’ll engage in hands-on coding exercises, implementing both multiple linear regression and logistic regression models in Python. You’ll also learn best practices for data preprocessing, feature selection, and model tuning to ensure your models are robust and accurate.
By the end of this training, you’ll have a comprehensive understanding of multiple linear regression and logistic regression, along with the practical skills to implement these techniques using Python. Whether you’re a data analyst, researcher, or developer, this workshop will empower you to apply these regression methods to solve real-world problems and make data-driven decisions.
Join us at Inzint and elevate your data science skills with advanced regression techniques in Python!
Let’s unlock the potential of predictive modeling and classification together! 📊🤖
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Timecodes-
00:00 - Intro
00:10 - multiple linear regression
27:00 - Logistic LR
47:14 - Implementation
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Tags-
#PythonProgramming
#MultipleLinearRegression
#LogisticRegression
#MachineLearning
#DataAnalysis
#PredictiveModeling
#DataScience
#InzintTraining
#TechWorkshop
#LearnPython
#DataVisualization
#StatisticalAnalysis
#ScikitLearn
#MLAlgorithms
#AITraining
#ModelEvaluation
#DataEngineering
#DataPrep
#BinaryClassification
#RegressionAnalysis