Logistic Regression in Python

Category : Other
Type: Tutorials
Language: English
Total Size: 3.0 GB
Uploaded By: freecoursewb
Downloads: 39731
Last checked: Jul. 23rd '26
Date uploaded: Jul. 23rd '26
Seeders: 23603
Leechers: 9204
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About Logistic Regression in Python

Overview

Logistic Regression in Python https://WebToolTip.com Last updated 3/2026 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 3.04 GB | Duration: 7h 40m Logistic regression in Python tutorial for beginners. You can do Predictive modeling using Python after this course. What you'll learn Understand how to interpret the result of Logistic Regression model in Python and translate them into actionable insight Learn the linear discriminant analysis and K-Nearest Neighbors tec

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Logistic Regression in Python

https://WebToolTip.com

Last updated 3/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.04 GB | Duration: 7h 40m

Logistic regression in Python tutorial for beginners. You can do Predictive modeling using Python after this course.

What you'll learn
Understand how to interpret the result of Logistic Regression model in Python and translate them into actionable insight
Learn the linear discriminant analysis and K-Nearest Neighbors technique in Python
Preliminary analysis of data using Univariate analysis before running classification model
Predict future outcomes basis past data by implementing Machine Learning algorithm
Indepth knowledge of data collection and data preprocessing for Machine Learning logistic regression problem
Learn how to solve real life problem using the different classification techniques
Course contains a end-to-end DIY project to implement your learnings from the lectures
Basic statistics using Numpy library in Python
Data representation using Seaborn library in Python
Classification techniques of Machine Learning using Scikit Learn and Statsmodel libraries of Python

Requirements
Students will need to install Python and Anaconda software but we have a separate lecture to help you install the same