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Simplifying Machine Learning with PyCaret in Python

48 Lessons
6 Quizzes
84 Playgrounds
26 Illustrations

Takeaway Skills

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

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

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...

How You'll Learn

Hands-on coding environments

You don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.

Faster than videos

Videos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.

No set-up required

Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.

Progress you can show

Built in assessments let you test your skills. Completion certificates let you show them off.

Hands-on coding environments

You don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.

Faster than videos

Videos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.

No set-up required

Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.

Progress you can show

Built in assessments let you test your skills. Completion certificates let you show them off.

Course Contents

1. Introduction to Machine Learning
2. Regression
3. Classification
4. Clustering
5. Anomaly Detection
6. Natural Language Processing
7. Deploying a Machine Learning Model
8. Conclusion
9. Appendix

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COURSE BY:

Giannis Tolios

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