Simplifying Machine Learning with PyCaret in Python

Gain insights into simplifying machine learning with PyCaret. Delve into regression, classification, clustering, and anomaly detection, and learn to deploy applications using Streamlit.

Beginner

48 Lessons

2h 15min

Certificate of Completion

Gain insights into simplifying machine learning with PyCaret. Delve into regression, classification, clustering, and anomaly detection, and learn to deploy applications using Streamlit.

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Explanations

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This course includes

84 Playgrounds

6 Quizzes

This course includes

84 Playgrounds

6 Quizzes

Course Overview

PyCaret is an low-code, open-source, machine learning library for Python. It can be used in machine learning tasks such as data preparation and model deployment. In this course, you will learn multiple topics related to machine learning. You will start with a brief introduction to the basic concepts of machine learning, and then continue with case studies of regression, classification, clustering, and anomaly detection based on the respective modules of the PyCaret library. Finally, we will focus on using ...Show More

What You'll Learn

Knowledge of PyCaret

Expertise in Streamlit and app deployment on Streamlit Cloud

Regression with PyCaret and familiarity with exploratory data analysis, environment setup and building machine learning models

Classification with PyCaret and creating, tuning, plotting and saving machine learning models

Clustering tasks with PyCaret

Anomaly Detection with PyCaret

What You'll Learn

Knowledge of PyCaret

Course Content

Introduction to Machine Learning

Get familiar with PyCaret, machine learning types, and applications in this beginner course.

Getting Started

Machine Learning and its Types

Regression

Get started with regression techniques, EDA, PyCaret setup, model building, and practical coding challenges.

Regression with PyCaret

Exploratory Data Analysis Getting Familiar with the PyCaret Environment Building the Model Coding Challenge: Train Random Forest Model Solution Review: Train Random Forest Model Quiz: Regression

Classification

Go hands-on with understanding and implementing classification using PyCaret in Python.

Classification with PyCaret Exploratory Data Analysis Getting Familiar with the PyCaret Environment Building the Model Coding Challenge: Make Predictions and Plot Model Solution Review: Make Predictions and Plot Model Quiz: Classification

Clustering

Build a foundation in clustering techniques using PyCaret, from setup to model evaluation.

Clustering with PyCaret Exploratory Data Analysis Getting Familiar with the PyCaret Environment Building the Model Coding Challenge: Create k-Means Model Solution Review: Create k-means Model Quiz: Clustering

Customer Segmentation with K-Means Clustering

Project

Anomaly Detection

Map out the steps for building and evaluating anomaly detection models using PyCaret.

Anomaly Detection with PyCaret Exploratory Data Analysis Getting Familiar with the PyCaret Environment Building the Model Coding Challenge: Create Local Outlier Factor Model Solution Review: Create Local Outlier Factor Model Quiz: Anomaly Detection

Natural Language Processing

9 Lessons

See how it works to conduct NLP analysis, topic modeling, and classification with PyCaret.

Deploying a Machine Learning Model

7 Lessons

Master the steps to deploy machine learning models using Streamlit, build web apps, and visualize data.

Conclusion

1 Lesson

Sharpen your skills in machine learning basics and explore further with PyCaret and Streamlit.

Appendix

1 Lesson

Get started with installing PyCaret and its dependencies for efficient machine learning.

Course Author

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Anthony Walker

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Emma Bostian 🐞

@EmmaBostian

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

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Kenan Eyvazov

DevOps Engineer

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

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