PlacesData API single-point runbook cutting SerpApi ($150/10K) and Google Maps ($320-$350/10K) bills while resolving OVER_QUERY_LIMIT at 240ms p50.

Materi ini membahas tahapan lengkap Analisis Regresi Linier Berganda, meliputi pengujian asumsi klasik (multikolinearitas, heteroskedastisitas, autokorelasi, dan normalitas), pengujian signifikansi parameter melalui Uji F dan Uji t, serta evaluasi model untuk mendeteksi pencilan (outlier) menggunakan Influence Plot dan Uji Bonferroni.

Unsupervised Learning Homework 1 github.com/thaivytr/usl-homework Uber trip data: - Load the data [uber-data.csv]. - Discover and comment clusters of uber data based on locations (longitude & latitude). - Analyze the cluster centers by time. - Analyze the cluster centers by date. - Remember to choose the right algorithm, compute the optimal number of - clusters and quality measures. - Develop adequate plots. - Apply the dataset for forecasting.