Logistic Regression in Python

Logistic Regression in Python

Language: English
Created by: Start-Tech Academy
Rate: 4.3 / 754 ratings
Enroll: 89,500 students

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

Description

You’re looking for a complete Classification modeling course that teaches you everything you need to create a Classification model in Python, right?

You’ve found the right Classification modeling course!

After completing this course you will be able to:

  • Identify the business problem which can be solved using Classification modeling techniques of Machine Learning.
  • Create different Classification modelling model in Python and compare their performance.
  • Confidently practice, discuss and understand Machine Learning concepts

How this course will help you?

Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course.

If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you the most popular Classification techniques of machine learning, such as Logistic Regression, Linear Discriminant Analysis and KNN

Why should you choose this course?

This course covers all the steps that one should take while solving a business problem using classification techniques.

Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.

What makes us qualified to teach you?

The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course

We are also the creators of some of the most popular online courses – with over 150,000 enrollments and thousands of 5-star reviews like these ones:

This is very good, i love the fact the all explanation given can be understood by a layman – Joshua

Thank you Author for this wonderful course. You are the best and this course is worth any price. – Daisy

Our Promise

Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.

Download Practice files, take Quizzes, and complete Assignments

With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning.

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
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