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

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 [email protected] ⌚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