CampusX

Machine Learning Pipelines streamline the end-to-end process of model building, evaluation, and deployment, ensuring a systematic and reproducible workflow.

Code Used : https://github.com/campusx-official/100-days-of-machine-learning/tree/main/day29-sklearn-pipelines

============================
Do you want to learn from me?
Check my affordable mentorship program at : https://learnwith.campusx.in/s/store
============================

📱 Grow with us:
CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official
CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official
My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789
Discord: https://discord.gg/PsWu8R87Z8
Instagram: https://www.instagram.com/campusx.official
E-mail us at support@campusx.in

⌚Time Stamps⌚

00:00 - Intro
00:32 - SKLearn Pipelines
03:42 - Example through Titanic Dataset
06:12 - Train/Test/Split
07:15 - Applying Imputation
13:30 - Pickling the model
21:35 - Strategy for the Pipeline
30:00 - Creating Pipeline
30:43 - Pipeline vs make_pipeline
33:40 - Explore the pipeline
39:20 - Cross Validation using Pipeline

Machine Learning Pipelines A-Z | Day 29 | 100 Days of Machine Learning

Machine Learning Pipelines A-Z | Day 29 | 100 Days of Machine Learning

Get Full Course Access

Highly Recommended Courses

Explore top skills

In-demand Careers

Popular Topics

Creative Skills

Business Skills

Choose your learning path