Citizen Data Scientist, Module VI: Mastering Models for Learning: A Deep Dive into Bagging, Neural Networks, and More
Learn about machine learning models like Random Forest, Neural Networks, and K-means clustering. This detailed guide explains concepts intuitively, with examples like predicting ice cream sales and classifying handwritten digits
Citizen Data Scientist, Module II: Supervised learning: Predicting the Future with Labeled Data
Supervised learning is at the heart of many machine learning applications, helping models make predictions based on labeled data. From predicting house prices to classifying emails, this blog post explores the basics of supervised learning, covering regression, classification, decision trees, and key concepts like gradient descent—all in an accessible and intuitive way.
Citizen Data Scientist, Module I: Introduction to Data Science: Laying the Foundation
In this first module of the Citizen Data Scientist course series, we explore the foundational principles of Data Science. From understanding key concepts like machine learning and the CRISP-DM process to getting hands-on with Python and essential libraries, this post lays the groundwork for your journey into the world of data-driven decision-making.