MAMuhammad Ariel Shakaramiroinshaka-ai.hashnode.dev·1d ago · 7 min readPredicting Baldness Probability: From Messy Data to a Working Machine Learning ModelIf you think baldness is purely a matter of genetics, here's a plot twist: a few surprisingly sensible patterns show up once you dig into age, smoking habits, and stress levels together. This post wal00
MAMuhammad Ariel Shakaramiroinshaka-ai.hashnode.dev·1d ago · 7 min readMemprediksi Probabilitas Kebotakan: Dari Data Kotor sampai Model Machine Learning TerbaikKalau kamu pikir kebotakan cuma soal gen dari orang tua, coba tunggu dulu — dari eksplorasi data kali ini, muncul beberapa pola menarik (dan cukup masuk akal) dari kombinasi umur, kebiasaan merokok, d00
MAMuhammad Ariel Shakaramiroinshaka-ai.hashnode.dev·1d ago · 18 min readHands-On Data Preprocessing with Python: From Missing Values to PCALearning notes with code that actually runs — six core data preprocessing techniques you'll reach for before feeding data into a Machine Learning model, backed by real execution output instead of made00
MAMuhammad Ariel Shakaramiroinshaka-ai.hashnode.dev·1d ago · 16 min readPraktik Data Preprocessing dengan Python: dari Missing Value sampai PCACatatan belajar plus kode langsung jalan — enam teknik inti data preprocessing yang paling sering dipakai sebelum data masuk ke model Machine Learning, lengkap dengan angka hasil eksekusi asli, bukan 00
MAMuhammad Ariel Shakaramiroinshaka-ai.hashnode.dev·1d ago · 11 min readFrom Messy Data to Production-Ready: Building an ETL Pipeline with Python, Pandas & pytestMost data science courses start with a clean dataset. Real-world data doesn't work that way. What you actually get is a CSV with categories written in inconsistent casing, a date column mixing four di00
