Regression Modeling with Statistics and Machine Learning in Python

本课程是统计和机器学习分析的一站式指南。本课程将以实用，动手的方式教您使用Python进行回归分析（用于统计数据分析和机器学习）。

具体来说，该课程将：

•使您从基本的统计知识水平提高到可以执行一些最常见的基于高级回归分析的技术的水平

•使您能够使用Python执行各种统计和机器学习数据分析任务

•向您介绍一些最重要的统计和机器学习概念，因此您可以将它们应用于实际数据分析和解释

您将对一些最重要的统计和机器学习概念及其在回归分析中的应用有深刻的了解。您将能够决定哪种回归分析技术最适合回答您的研究问题，并且最适用于您的数据；然后您将解释结果。

MP4 | Video: AVC, 1920×1080 30 fps | Audio: AAC, 48 KHz, 2 Ch | Duration: 5h 47m
Genre: eLearning | Language: English | Size: 804 MB

This hands-on, regression-analysis bootcamp will help you master practical statistical modeling and machine learning in Python

Key Features
Minimal mathematical jargon. The course focuses on teaching you the most important Python data science concepts and packages, including Pandas
Implement clustering and classification models on data
Gain a thorough grounding in data science and understand which models should be used, and when.

What You Will Learn
Harness the power of Anaconda/iPython for practical data science
Read in data into the Python environment from different sources
Implement classical statistical regression modeling techniques such as linear regression in Python
Implement machine learning-based regression modeling techniques such as Random Forests and kNN for predictive modeling
Master neural network- and deep learning-based regression

About
This course is your one-shot guide to statistical and machine learning analysis. This course will teach you regression analysis (for both statistical data analysis and machine learning) in Python—all in a practical, hands-on way.

Specifically, the course will:

• Take you from a basic level of statistical knowledge to a level where you can perform some of the most common advanced regression analysis-based techniques

• Equip you to use Python to perform various statistical and machine learning data analysis tasks

• Introduce you in a hands-on way to some of the most important statistical and machine learning concepts, so you can apply them to practical data analysis and interpretation

You will get a strong background in some of the most important statistical and machine learning concepts and their applications in regression analysis. You will be able to decide which regression analysis techniques are best suited for answering your research questions and most applicable to your data; then you’ll interpret the results.

This is a practical, hands-on course—we spend time dealing with some theoretical concepts related to both statistical and machine learning regression analysis.