Machine Learning 101 with Scikit-learn and StatsModels

Description

Begin your machine learning journey by learning all about linear regression, logistic regression, and cluster analysis

Machine Learning is one of the fundamental skills you need to become a data scientist. It's the steppingstone that will help you understand deep learning and modern data analysis techniques. In this course, you'll explore the three fundamental machine learning topics - linear regression, logistic regression, and cluster analysis. Even neural networks geeks (like us) can't help but admit that it's these three simple methods that data science revolves around. So, in this course, we will make the otherwise complex subject matter easy to understand and apply in practice. This course supports statistics theory with practical application of these quantitative methods in Python to help you develop skills in the context of data science. We've developed this course with not one but two machine learning libraries: StatsModels and sklearn. You'll be eager to complete this course and get ready to become a successful data scientist! All the code and supporting files for this course are available at https://github.com/PacktPublishing/Machine-Learning-101-with-Scikit-learn-and-StatsModels

Confidently work with two of the leading ML packages: statsmodels and sklearn
Understand how to perform a linear regression
Become familiar with the ins and outs of logistic regression
Get to grips with carrying out cluster analysis (both flat and hierarchical)
Apply your skills to real-life business cases
Get insights into the underlying ideas behind ML models

If you want to get acquainted with fundamental machine learning methods, become a successful data scientist, or just get started with building valuable skills in machine learning and data science, this course is for you.

The course has a perfect blend of theory and practical knowledge to help you gain a solid understand of the concepts covered.

Learn machine learning with StatsModels and sklearn * Apply machine learning skills to solve real-world business cases * Get started with linear regression, logistic regression, and cluster analysis

https://github.com/packtpublishing/machine-learning-101-with-scikit-learn-and-statsmodels

365 Careers' courses have been taken by more than 203,000 students in 204 countries. People working at world-class firms such as Apple, PayPal, and Citibank have completed 365 Careers trainings. By choosing 365 Careers, you make sure you will learn from proven experts who have a passion for teaching, and can take you from beginner to pro in the shortest possible amount of time. If you want to become a financial analyst, a finance manager, an FP&A analyst, an investment banker, a business executive, an entrepreneur, a business intelligence analyst, a data analyst, or a data scientist, 365 Careers' courses are the perfect place to start.

1. Introduction

2. Setting Up the Working Environment

3. Linear Regression with StatsModels

4. Linear Regression with Sklearn

5. Linear Regression - Practical Example

6. Logistic Regression

7. Cluster Analysis

8. Cluster Analysis: Additional Topics