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PyCaret

Anatomy of Regression

Muhammad Saad uddin

In this 2 hour and 15 mins long project-based course, you will learn how to ow to set up PyCaret Environment and become familiar with the variety of data preparing tasks done during setup, be able to create, see and compare the performance of several models, learn how to tune your model without doing an exhaustive search, create impressive visuals of models, interpret models with the wrapper around SHAP Library and much more & all this with just a few lines of code.

Note: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

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What's inside

Syllabus

PyCaret Anatomy of Regression

Here you will describe what the project is about. It should give an overview of what the learner will achieve by completing this project.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Suitable for learners in North America who are interested in data science and machine learning

Focuses on developing practical skills in data preparation, model training, and model evaluation

Provides a hands-on learning experience with PyCaret, a user-friendly machine learning library

Leverages SHAP to support model interpretability, enabling learners to understand how models make predictions

Limited in scope, targeting specific use cases rather than a comprehensive understanding of machine learning

May require learners to have some prior knowledge in data science and machine learning concepts

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in PyCaret: Anatomy of Regression with these activities:

Set Jupyter Notebook Environment

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This initial review is necessary to ensure that everybody starts at the same level.

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Download Python and install it on your computer
Download and install Jupyter Notebook
Set up a new Jupyter Notebook

Attend a PyCaret workshop

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Workshop attendance provides opportunities to learn from experts and gain practical experience.

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Find a PyCaret workshop near you
Register for the workshop
Attend the workshop

Practice the basics

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Repetition can accelerate learning outcomes, especially when skills are fresh and new.

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Code basic regression models in PyCaret
Fit and evaluate multiple models

Seven other activities

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Practice PyCaret Functions in Jupyter Notebooks

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Helps build proficiency in using PyCaret functions for regression tasks, improving efficiency and accuracy.

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Create a Jupyter notebook
Import the necessary libraries
Load the dataset
Apply PyCaret functions for data preparation, model creation, and tuning
Analyze and interpret the results

Advanced PyCaret features

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Building on foundational PyCaret skills through practice is recommended for deeper learning outcomes.

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Use PyCaret's hyperparameter tuning
Use PyCaret's feature engineering
Use PyCaret's model interpretation tools

PyCaret project: Predicting house prices

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Students, especially in technical subjects, benefit from working on projects to put their skills into practice and reinforce knowledge acquisition.

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Gather a dataset of house prices
Preprocess the data
Train and evaluate a PyCaret regression model
Deploy the model as a web application

Develop a Regression Model using PyCaret and SHAP

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Enhances understanding of model interpretation and feature importance by applying PyCaret and SHAP to build a regression.

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Load and prepare the dataset
Train a regression model using PyCaret
Interpret the model using SHAP
Generate visualizations to explain model predictions
Document the process and share the results

Blog post: PyCaret for beginners

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Content creation encourages deeper understanding and mastery through extraction and synthesis of learned concepts.

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Summarize the key concepts of PyCaret
Provide examples of how to use PyCaret
Share tips for getting started with PyCaret

Presentation: PyCaret for data scientists

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Content creation encourages deeper understanding and mastery through extraction and synthesis of learned concepts.

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Summarize the key features of PyCaret
Provide examples of how PyCaret can be used for data science tasks
Share tips for getting started with PyCaret

Contribute to the PyCaret codebase

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Contributing to an open source project demonstrates knowledge and provides real-world experience.

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Identify an issue or feature to work on
Fork the PyCaret repository
Make changes to the code
Submit a pull request

Career center

Learners who complete PyCaret: Anatomy of Regression will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts use their expertise in data analysis tools and techniques to solve critical business problems and transform companies into more data-driven organizations. This course, PyCaret: Anatomy of Regression, can help Data Analysts build a foundation in regression modeling, which is a fundamental skill for analyzing and understanding data. By learning how to set up a PyCaret environment, prepare data, create and compare models, and tune models, Data Analysts can enhance their ability to extract meaningful insights from data and make informed decisions.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their knowledge of machine learning, statistics, and programming to build models that can solve real-world problems. This course, PyCaret: Anatomy of Regression, can help Data Scientists develop their skills in regression modeling, which is a widely-used technique for predicting continuous outcomes. By understanding how to select the right regression model, tune the model parameters, and interpret the model results, Data Scientists can improve the accuracy and reliability of their models.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers apply machine learning techniques to solve complex problems in various industries. This course, PyCaret: Anatomy of Regression, can help Machine Learning Engineers build a strong foundation in regression modeling, which is a fundamental technique for making predictions. By learning how to preprocess data, train models, and evaluate model performance, Machine Learning Engineers can develop robust and efficient machine learning solutions.

See salaries and explore the career path for Machine Learning Engineer

Statistician

Statisticians use statistical methods to analyze and interpret data. This course, PyCaret: Anatomy of Regression, can help Statisticians expand their knowledge of regression modeling, which is a powerful technique for understanding the relationship between variables. By learning how to choose the appropriate regression model, interpret regression results, and communicate findings effectively, Statisticians can enhance their ability to provide valuable insights and support decision-making.

See salaries and explore the career path for Statistician

Business Analyst

Business Analysts use data and analytics to solve business problems and improve decision-making within organizations. This course, PyCaret: Anatomy of Regression, can equip Business Analysts with the skills to perform regression analysis, which is essential for understanding relationships between variables and predicting outcomes. By learning how to prepare data, select the right regression model, interpret results, and communicate findings, Business Analysts can make data-driven recommendations that drive business success.

See salaries and explore the career path for Business Analyst

Financial Analyst

Financial Analysts use financial data to make investment recommendations and provide guidance to clients. This course, PyCaret: Anatomy of Regression, can provide Financial Analysts with a solid foundation in regression modeling, which is a valuable tool for analyzing financial data and making predictions. By understanding how to build and interpret regression models, Financial Analysts can enhance their ability to identify trends and make informed investment decisions.

See salaries and explore the career path for Financial Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical techniques to analyze financial data and make investment decisions. This course, PyCaret: Anatomy of Regression, can help Quantitative Analysts build a strong foundation in regression modeling, which is a fundamental technique for understanding the relationship between variables and predicting outcomes. By learning how to select the right regression model, interpret regression results, and communicate findings effectively, Quantitative Analysts can improve their ability to make data-driven investment decisions.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries use mathematical and statistical models to assess and manage financial risks. This course, PyCaret: Anatomy of Regression, can provide Actuaries with a solid foundation in regression modeling, which is a crucial technique for analyzing large datasets and making predictions. By understanding how to build and interpret regression models, Actuaries can enhance their ability to assess risks, calculate premiums, and make informed decisions.

See salaries and explore the career path for Actuary

Market Researcher

Market Researchers gather and analyze data to understand consumer behavior and market trends. This course, PyCaret: Anatomy of Regression, can help Market Researchers build a strong foundation in regression modeling, which is a valuable technique for analyzing large datasets and identifying patterns. By learning how to select the right regression model, interpret regression results, and communicate findings effectively, Market Researchers can gain valuable insights into consumer behavior and make data-driven recommendations.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex problems in various industries. This course, PyCaret: Anatomy of Regression, can provide Operations Research Analysts with a solid foundation in regression modeling, which is a powerful technique for analyzing data and making predictions. By understanding how to build and interpret regression models, Operations Research Analysts can enhance their ability to optimize processes, improve efficiency, and make informed decisions.

See salaries and explore the career path for Operations Research Analyst

Product Manager

Product Managers oversee the development and launch of new products. This course, PyCaret: Anatomy of Regression, can provide Product Managers with a solid foundation in regression modeling, which is a useful technique for understanding customer behavior and predicting demand. By learning how to build and interpret regression models, Product Managers can enhance their ability to make data-driven decisions about product development and marketing strategies.

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Risk Manager

Risk Managers identify, assess, and manage risks faced by organizations. This course, PyCaret: Anatomy of Regression, can provide Risk Managers with a solid foundation in regression modeling, which is a valuable technique for analyzing data and making predictions. By understanding how to build and interpret regression models, Risk Managers can enhance their ability to identify potential risks, assess their impact, and develop mitigation strategies.

See salaries and explore the career path for Risk Manager

Data Engineer

Data Engineers design, build, and maintain data pipelines and systems. This course, PyCaret: Anatomy of Regression, may be useful for Data Engineers as it provides a hands-on introduction to regression modeling, which is a fundamental technique for analyzing data and making predictions. By understanding how to build and interpret regression models, Data Engineers can gain a better understanding of how data can be used to solve business problems.

See salaries and explore the career path for Data Engineer

Software Engineer

Software Engineers design, develop, and maintain software systems. This course, PyCaret: Anatomy of Regression, may be useful for Software Engineers as it provides a practical introduction to regression modeling, which is a valuable technique for analyzing data and making predictions. By understanding how to build and interpret regression models, Software Engineers can gain a better understanding of how data can be used to improve software performance and functionality.

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Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in PyCaret: Anatomy of Regression.

The Elements of Statistical Learning

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A more advanced textbook that provides a comprehensive overview of statistical learning methods, including regression.

The Elements of Statistical Learning: Data Mining,...

Hardcover

$$$

PyCaret

Anatomy of Regression

Two deals to help you save

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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