Exploring Data with NumPy, Matplotlib, Seaborn, Plotly, Pandas, and Linear Regression
What you will learn
How to use the powerful data analysis and manipulation capabilities of the Pandas library in Python to prepare, clean, and analyze data.
How to use machine learning model such as linear regression to make predictions and interpret data insights.
Techniques for handling missing values, removing duplicates, working with categorical data, and reshaping and pivoting data.
How to use various visualization and statistical techniques to understand the structure and characteristics of your data through Exploratory Data Analysis (EDA)
How to implement linear regression model in Pandas and Scikit-learn, evaluate the performance using various metrics.
Description
Welcome to our course, “Data Analysis with Python Pandas and Machine Learning Model”!
This course is designed to provide you with a comprehensive understanding of the powerful data analysis and manipulation capabilities of the Pandas library in Python, as well as the fundamental concepts and techniques of linear regression, one of the most widely used machine learning models.
You will learn how to use the Pandas library to prepare, clean, and analyze data, as well as how to use machine learning models such as linear regression to make predictions and interpret data insights. The course places a strong emphasis on data cleaning and preparation, which is a critical step in the data analysis process and is often overlooked in other courses.
Throughout the course, you will gain hands-on experience with data cleaning, preparation, and visualization techniques, including handling missing values, working with categorical data, and reshaping and pivoting data. You will also learn how to use various visualization and statistical techniques to understand the structure and characteristics of your data through Exploratory Data Analysis (EDA).
You will learn how to implement linear regression model in Pandas and Scikit-learn, evaluate their performance using various metrics, and interpret model coefficients and their significance.
This course is suitable for different levels of audiences, from beginner to advanced, who are interested in data analysis and machine learning. The course provides a hands-on approach to learning, with real-world examples that allow learners to apply the concepts and techniques they’ve learned.
By the end of the course, you will have a solid understanding of the data analysis and manipulation capabilities of Pandas and the concepts and techniques of linear regression, as well as the ability to analyze, report, and interpret data using a machine learning model.
Join us now and take your data analysis and machine learning skills to the next level!
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