A step-by-step tutorial on training and deploying machine learning models in Alteryx Designer using PyCaret

Introduction

In this tutorial, I will show you how you can train and deploy machine learning pipelines in a very popular ETL tool Alteryx using PyCaret — an open-source, low-code machine learning library in Python. The Learning Goals of this tutorial are:

👉 What is PyCaret and how to get started?

👉 What is Alteryx Designer and how to set it up?

👉 Train end-to-end machine learning pipeline in Alteryx Designer including data preparation such as missing value imputation, one-hot-encoding, scaling, transformations, etc.

👉 Deploy trained pipeline and generate inference during ETL.

PyCaret

PyCaret is an open-source, low-code machine learning library and…


How to get started with PyCaret for all your machine learning projects

PyCaret — An open-source, low-code machine learning library in Python

PyCaret

PyCaret is an open-source, low-code machine learning library and end-to-end model management tool built-in Python for automating machine learning workflows. Its ease of use, simplicity, and ability to quickly and efficiently build and deploy end-to-end machine learning pipelines will amaze you.

PyCaret is an alternate low-code library that can replace hundreds of lines of code with few lines only. This makes the experiment cycle exponentially fast and efficient.

PyCaret is simple and easy to use. All the operations performed in PyCaret are sequentially stored in a Pipeline that…


A step-by-step guide on training and scoring machine learning models in KNIME using PyCaret

PyCaret is an open-source Python library and KNIME is an open-source data analytics platform

PyCaret

PyCaret is an open-source, low-code machine learning library and end-to-end model management tool built-in Python for automating machine learning workflows. Its ease of use, simplicity, and ability to quickly and efficiently build and deploy end-to-end machine learning pipelines will amaze you.

PyCaret is an alternate low-code library that can replace hundreds of lines of code with few lines only. This makes the experiment cycle exponentially fast and efficient.

PyCaret is simple and easy to use. All the operations performed in PyCaret are sequentially stored in a Pipeline that is fully automated for deployment. Whether it’s imputing missing values, one-hot-encoding, transforming…


A beginner-friendly, step-by-step tutorial on integrating MLOps in your Machine Learning experiments using PyCaret

Photo by Adi Goldstein on Unsplash

PyCaret

PyCaret is an open-source, low-code machine learning library and end-to-end model management tool built-in Python for automating machine learning workflows. It is known for its ease of use, simplicity, and ability to quickly and efficiently build and deploy end-to-end ML prototypes.

PyCaret is an alternate low-code library that can replace hundreds of code lines with few lines only. This makes the experiment cycle exponentially fast and efficient.


A step-by-step, beginner-friendly tutorial on how to write and train custom machine learning models in PyCaret

Photo by Rob Lambert on Unsplash

PyCaret

PyCaret is an open-source, low-code machine learning library and end-to-end model management tool built-in Python for automating machine learning workflows. It is incredibly popular for its ease of use, simplicity, and ability to quickly and efficiently build and deploy end-to-end ML prototypes.

PyCaret is an alternate low-code library that can replace hundreds of code lines with few lines only. This makes the experiment cycle exponentially fast and efficient.

PyCaret is simple and easy to use. All the operations performed in PyCaret are sequentially stored in a Pipeline that is fully automated for deployment.


A step-by-step, beginner-friendly tutorial on how to build an end-to-end Machine Learning Pipeline with PyCaret and deploy it as an API.

PyCaret — an open-source, low-code machine learning library in Python

👉 Introduction

This is a step-by-step, beginner-friendly tutorial on how to build an end-to-end Machine Learning Pipeline with PyCaret and deploy it in production as a web API using FastAPI.

Learning Goals of this Tutorial

  • Build an end-to-end machine learning pipeline using PyCaret
  • What is a deployment and why do we deploy machine learning models
  • Develop an API using FastAPI to generate predictions on unseen data
  • Use Python to send a request to API for generating predictions programmatically.

This tutorial will cover the entire machine learning life cycle at a high level which is broken down into the following sections:


Hands-on Tutorials

A step-by-step tutorial on unsupervised anomaly detection for time series data using PyCaret

PyCaret — An open-source, low-code machine learning library in Python

👉 Introduction

This is a step-by-step, beginner-friendly tutorial on detecting anomalies in time series data using PyCaret’s Unsupervised Anomaly Detection Module.

Learning Goals of this Tutorial

  • What is Anomaly Detection? Types of Anomaly Detection.
  • Anomaly Detection use-case in business.
  • Training and evaluating anomaly detection model using PyCaret.
  • Label anomalies and analyze the results.

👉 PyCaret

PyCaret is an open-source, low-code machine learning library and end-to-end model management tool built-in Python for automating machine learning workflows. It is incredibly popular for its ease of use, simplicity, and ability to build and deploy end-to-end ML prototypes quickly and efficiently.

PyCaret is an alternate low-code library that can be used to replace…


A step-by-step tutorial to develop and interact with machine learning pipelines rapidly

Photo by Hunter Harritt on Unsplash

👉 Introduction

This tutorial is a step-by-step, beginner-friendly explanation of how you can integrate PyCaret and Gradio, the two powerful open-source libraries in Python, and supercharge your machine learning experimentation within minutes.

This tutorial is a “hello world” example, I have used Iris Dataset from UCI, which is a multiclassification problem where the goal is to predict the class of iris plants. The code given in this example can be reproduced on any other dataset, without any major modifications.

👉 PyCaret

PyCaret is an open-source, low-code machine learning library and end-to-end model management tool built-in Python for automating machine learning workflows. …


A beginner-friendly introduction to Time Series Forecasting

Photo by Chris Liverani on Unsplash

👉 What is Time Series Data?

Time series data is data collected on the same subject at different points in time, such as GDP of a country by year, a stock price of a particular company over a period of time, or your own heartbeat recorded at each second, as a matter of fact, anything that you can capture continuously at different time-intervals is a time series data.

See below as an example of time series data, the chart below is the daily stock price of Tesla Inc. (Ticker Symbol: TSLA) for last year. The y-axis on the right-hand side is the value in US$ (The…


A step-by-step tutorial to forecast multiple time series with PyCaret

PyCaret — An open-source, low-code machine learning library in Python

PyCaret

PyCaret is an open-source, low-code machine learning library and end-to-end model management tool built-in Python for automating machine learning workflows. It is incredibly popular for its ease of use, simplicity, and ability to build and deploy end-to-end ML prototypes quickly and efficiently.

PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few lines only. This makes the experiment cycle exponentially fast and efficient.

PyCaret is simple and easy to use. All the operations performed in PyCaret are sequentially stored in a Pipeline that is fully automated for deployment. Whether it’s imputing…

Moez Ali

Data Scientist, Founder & Author of PyCaret

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