Applied Data Science Lab: Predicting Spotify Likes

Session 4: Model Deployment
Join us for the final session of our hands-on lab, where we bring everything together to build and deploy our models. In this session, we’ll review our model development from the previous session and finalize a predictive model using Spotify’s song data. We’ll encapsulate all our work into a single notebook, serving as a comprehensive guide for future projects. Next, we’ll discuss key steps in model deployment—saving our trained model and implementing a pipeline for song data preparation. Then, we’ll explore deploying two models: one to predict “Likes” and another for personalized music recommendations. We’ll conclude with final insights and discuss the next steps in applying these concepts to your own machine learning projects.

Format:
🔹 Session 1: Project Overview and Dataset Introduction
🔹 Session 2: Exploratory Data Analysis (EDA) and Feature Engineering
🔹 Session 3: Machine Learning: Model Development and Evaluation
🔹 Session 4: Model Deployment and Final Insights

We hope you join us!

AGENDA

• 6:00 p.m. – Welcome
• 6:05 p.m. – Review Session 3
• 6:15 p.m. – Standardizing Data
• 6:25 p.m. – Final Project Walk Through
• 6:40 p.m. – Independent Exploration of the Final Notebook
• 6:50 p.m. – Model Deployment: Prediction
• 7:00 p.m. – Model Deployment: Music Recommendations
• 7:10 p.m. – Final Insights & Next Steps
• 7:20 p.m. – Questions/Discussion
• 7:30 p.m. – End