Logistic Regression in Python
Logistic regression in Python tutorial for beginners. You can do Predictive modeling using Python after this course.
What you’ll learn
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Understand how to interpret the result of Logistic Regression model in Python and translate them into actionable insight
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Learn the linear discriminant analysis and K-Nearest Neighbors technique in Python
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Preliminary analysis of data using Univariate analysis before running classification model
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Predict future outcomes basis past data by implementing Machine Learning algorithm
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Indepth knowledge of data collection and data preprocessing for Machine Learning logistic regression problem
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Learn how to solve real life problem using the different classification techniques
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Course contains a end-to-end DIY project to implement your learnings from the lectures
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Basic statistics using Numpy library in Python
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Data representation using Seaborn library in Python
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Classification techniques of Machine Learning using Scikit Learn and Statsmodel libraries of Python
Requirements
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Students will need to install Python and Anaconda software but we have a separate lecture to help you install the same
Who this course is for:
- People pursuing a career in data science
- Working Professionals beginning their Data journey
- Statisticians needing more practical experience
- Anyone curious to master classification machine learning techniques from Beginner to Advanced in short span of time
