Machine Learning: Machine Learning Pipeline Topics discussed: 1. Machine Learning Pipeline: i. Problem Definition ii. Data Collection iii. Basic Data Cleaning iv. Data Splitting v. Data Preprocessing and Feature Engineering vi. Selecting Algorithm vii. Model Training viii. Model Evaluation and Pipeline Saving ix. Making Predictions x. Monitor and Iterate. ✧✧ Playlist ✧✧ Machine Learning Playlist: https://www.youtube.com/playlist?list=PLBlnK6fEyqRi-VHKpqEQNIjotoP-e9lht ✧✧ Support & Contribution ✧✧ Contribute: https://nesoacademy.org/donate Memberships: https://www.youtube.com/channel/UCQYMhOMi_Cdj1CEAU-fv80A/join ✧✧ Socials ✧✧ Instagram ► https://www.instagram.com/nesoacademy Discord ► https://discord.gg/hhW2NJucQD WhatsApp ► https://whatsapp.com/channel/0029Va9B1Bq4tRru0nqgtx3h Twitter [X] ► https://x.com/nesoacademy ✧✧ Main Presence ✧✧ Website ► https://www.nesoacademy.org/ App ► https://play.google.com/store/apps/details?id=org.nesoacademy ✧✧ Resources ✧✧ Books: https://nesoacademy.org/recommended-books ✧✧ Credits ✧✧ Music: 1. Axol x Alex Skrindo - You [NCS Release] #MLByNeso #MachineLearning #MLPipeline