COURSE AUTHOR –
Start-Tech Academy
1. Understand how to interpret the result of Logistic Regression model in Python and translate them into actionable insight
2. Learn the linear discriminant analysis and K-Nearest Neighbors technique in Python
3. Preliminary analysis of data using Univariate analysis before running classification model
4. Predict future outcomes basis past data by implementing Machine Learning algorithm
5. Indepth knowledge of data collection and data preprocessing for Machine Learning logistic regression problem
6. Learn how to solve real life problem using the different classification techniques
7. Course contains a end-to-end DIY project to implement your learnings from the lectures
8. Basic statistics using Numpy library in Python
9. Data representation using Seaborn library in Python
10. Classification techniques of Machine Learning using Scikit Learn and Statsmodel libraries of Python
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