10最好的逻辑回归教程推荐

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特写 iPhone，显示 Udemy 应用程序和带笔记本的笔记本电脑有数以千计的在线课程和课程可以帮助您提高 逻辑回归 技能并获得 逻辑回归 证书。

在这篇博客文章中，我们的专家汇总了 10 个精选列表 最好的 逻辑回归 课程, 现在在线提供的教程、培训计划、课程和认证。

我们只包括那些符合我们高质量标准的课程。我们花了很多时间和精力来为您收集这些。这些课程适合所有级别的初学者、中级学习者和专家。

以下是这些课程以及它们为您提供的内容！

10最好的逻辑回归教程推荐

课程名 在校生（人数） 评论（计数）
1. Logistic Regression in Python 我们的最佳选择 95533+ 792+
2. Logistic Regression in R Studio 82472+ 302+
3. Linear Regression and Logistic Regression in Python 52166+ 310+
4. Deep Learning Prerequisites: Logistic Regression in Python 27026+ 3714+
5. Theoretical Machine Learning From Scratch – Linear Models 14086+ 65+
6. Logistic Regression using SAS – Indepth Predictive Modeling 6261+ 1094+
7. Logistic Regression using Stata 1745+ 115+
8. Prediction Maps & Validation using Logistic Regression & ROC 640+ 121+
9. Logistic Regression (Predictive Modeling) workshop using R 525+ 97+
10. Logistic Regression using R in 10 easy steps! 91+ 39+

1. Logistic Regression in Python 经过 Start-Tech Academy Udemy课程 我们的最佳选择

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

截至目前，超过 95533+ 人们已经注册了这门课程，而且已经结束了 792+ 评论.

课程内容
Introduction
Introduction to Machine Learning
Basics of Statistics
Setting up Python and Jupyter Notebook
Data Preprocessing
Classification Models
Linear Discriminant Analysis (LDA)
Test-Train Split
K-Nearest Neighbors classifier
Understanding the Results
Appendix 1: Linear Regression in Python
Course Conclusion

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2. Logistic Regression in R Studio 经过 Start-Tech Academy Udemy课程

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

截至目前，超过 82472+ 人们已经注册了这门课程，而且已经结束了 302+ 评论.

课程内容
Introduction
Basics of Statistics
Getting started with R and R studio
Introduction to Machine Learning
Data Preprocessing
Classification Models
Linear Discriminant Analysis (LDA)
Test-Train Split
K-Nearest Neighbors classifier
Understanding the Results
Appendix 1: Linear Regression in R
Course Conclusion

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3. Linear Regression and Logistic Regression in Python 经过 Start-Tech Academy Udemy课程

Build predictive ML models with no coding or maths background. Linear Regression and Logistic Regression for beginners

截至目前，超过 52166+ 人们已经注册了这门课程，而且已经结束了 310+ 评论.

课程内容
Introduction
Setting up Python and Python Crash Course
Basics of Statistics
Data Preprocessing before building Linear Regression Model
Building the Linear Regression Model
Introduction to the classification Models
Building a Logistic Regression Model
Test-Train Split
Congratulations & about your certificate

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4. Deep Learning Prerequisites: Logistic Regression in Python 经过 Lazy Programmer Inc. Udemy课程

“Data science, machine learning, and artificial intelligence in Python for students and professionals”

截至目前，超过 27026+ 人们已经注册了这门课程，而且已经结束了 3714+ 评论.

课程内容
Start Here
Basics: What is linear classification? What’s the relation to neural networks?
Solving for the optimal weights
Practical concerns
Checkpoint and applications: How to make sure you know your stuff
Project: Facial Expression Recognition
Background Review
Setting Up Your Environment (FAQ by Student Request)
Extra Help With Python Coding for Beginners (FAQ by Student Request)
Effective Learning Strategies for Machine Learning (FAQ by Student Request)
Appendix / FAQ Finale

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5. Theoretical Machine Learning From Scratch – Linear Models 经过 Raviteja Kolapalli Udemy课程

Learn the theory and math behind Linear and Logistic regression and also learn to code them from scratch

截至目前，超过 14086+ 人们已经注册了这门课程，而且已经结束了 65+ 评论.

课程内容
Course Intro and Pre-requisites(Don’t Skip)
Linear Regression
Logistic Regression
Course Outro

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6. Logistic Regression using SAS – Indepth Predictive Modeling 经过 Gopal Prasad Malakar Udemy课程

“Analytics /Machine Learning / Data Science: Statistical / Econometrics foundation, SAS Program details, Modeling demo”

截至目前，超过 6261+ 人们已经注册了这门课程，而且已经结束了 1094+ 评论.

课程内容
Course Outline
Introduction to Credit Scoring / Credit Score card development
Data Design for Modelling
Data Audit – Make sure to check that data is right for the modelling
Variable Selection – Select important numeric and character variables
Multi Collinearity Treatment
Iterate for final model / Understand strength of the model
Strength of a Model and Model Validation Methods
Reject Inference – Developing application score on scored population
Appendix Topics (It will have contents based on student’s demands)

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7. Logistic Regression using Stata 经过 Najib Mozahem Udemy课程

Theory and Application

截至目前，超过 1745+ 人们已经注册了这门课程，而且已经结束了 115+ 评论.

课程内容
Contingency Tables
Logistic Regression
Prediction and Model Fit
Application: Fitting the Model
Application: Model Fit
Application: Visualizing the Model
Conclusion

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8. Prediction Maps & Validation using Logistic Regression & ROC 经过 Dr. Omar AlThuwaynee Udemy课程

Comprehensive (Step-by-Step) Procedure From Prediction to ROC Validation of Maps using Logistic Regression In GIS and R

截至目前，超过 640+ 人们已经注册了这门课程，而且已经结束了 121+ 评论.

课程内容
“Introduction
Prepare dichotomous binary (1,0) training data in ArcGIS
Settings and Packages preparation in R Studio
Data Visualization and preparation in R studio
Data conversion and resampling in R Studio
Run multivariate Logistic Regression in R
ROC and Model Validation”

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

9. Logistic Regression (Predictive Modeling) workshop using R 经过 Gopal Prasad Malakar Udemy课程

Predictive Analytics – Learn R syntax for step by step logistic regression model development and validations

截至目前，超过 525+ 人们已经注册了这门课程，而且已经结束了 97+ 评论.

课程内容
Course details and preparing yourself for modeling
Understand Data and go for variable selection
Refine Variable list
Iterate for final model
Appendix topics – (Based on Student’s demand) – will keep growing

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10. Logistic Regression using R in 10 easy steps! 经过 Aze Analytics Udemy课程

“Learn to build Logistic Regression model using R, with a real life case study!”

截至目前，超过 91+ 人们已经注册了这门课程，而且已经结束了 39+ 评论.

课程内容
“Logistic Regression – Overview, Model Building, Assessment & Implementation”

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

下面是一些关于学习的常见问题逻辑回归

学习逻辑回归需要多长时间？

“学习逻辑回归需要多长时间”这个问题的答案是。 . .这取决于。每个人都有不同的需求，每个人都在不同的场景下工作，所以一个人的答案可能与另一个人的答案完全不同。

考虑这些问题：你想学习 逻辑回归 是为了什么？你的出发点在哪里？您是初学者还是有使用 逻辑回归 的经验？你能练习多少？每天1小时？每周40小时？ 查看本课程关于 逻辑回归.

逻辑回归 学起来容易还是难？

不，学习 逻辑回归 对大多数人来说并不难。检查这个 关于如何学习的课程 逻辑回归 立刻！

如何快速学习逻辑回归？

学习 逻辑回归 最快的方法是先得到这个 逻辑回归 课程, 然后尽可能练习你学到的任何东西。即使每天只有 15 分钟的练习。一致性是关键.

在哪里学习 逻辑回归？

如果您想探索和学习 逻辑回归，那么 Udemy 为您提供了学习 逻辑回归 的最佳平台。查看此 关于如何学习的课程 逻辑回归 立刻！