Welcome!¶

This site serves as my personal digital garden – a collection of notes, thoughts, code snippets, and summaries related to the vast field of Data Science.

Here you'll find topics covering:

Foundational Mathematics (Linear Algebra, Statistics, Calculus)
Python Programming for Data Science
Data Collection, Cleaning, and Feature Engineering
Data Visualization Techniques
Core Machine Learning Algorithms and Concepts
Deep Learning Fundamentals
Big Data Technologies
...and more as I continue to learn and document!

Navigating the Notes¶

Use the navigation sidebar on the left to explore the different sections and topics. The search bar at the top can also help you find specific keywords quickly.

Main Sections¶

Here are the primary areas covered in these notes:

The Basics: Core concepts and foundational knowledge.
Mathematics: Essential mathematical underpinnings for data science.
Data Collection: Methods for acquiring data.
Feature Engineering: Transforming raw data into useful features.
Data Visualization: Techniques for visually representing data.
Machine Learning: Algorithms and techniques for building predictive models.
Deep Learning: Notes on neural networks and advanced architectures.
Big Data Technologies: Tools for handling large datasets (Spark, Hadoop, etc.).
Ethics and Bias: Important considerations in responsible data science.

Please note: This is a living collection of notes reflecting my ongoing learning journey. Content may be updated or reorganized over time.