herrera-ignacio/datascience

Data science notes

Data Science

• Data Science
  • Must know concepts
  • Mathematics
    • General
    • Statistics
    • Probability Theory
  • Data preprocessing
  • Recommended books

Must know concepts

• ML, DL and AI
• Categorical Variables
• Feature Engineering
• Features
• Feature Columns

Mathematics

What are mathematics?

General

• Mathematical Analysis
• Algebra
• Number Theory
  • Arithmetic
• Geometry

Statistics

• Standard Deviation
• Regression Analysis
• Statistical Model
• Statistical Inference

Probability Theory

• Sample Space
• Random Variables
• Event
• Bernoulli trial
• Probability Distribution
• Probability Measure

Data preprocessing

• Data cleaning
• Data Encoding
  • Label Encoding
  • One Hot Encoding
  • Cardinal Encoding
  • Helmert Encoding
  • Binary Encoding
  • Frequency Encoding
  • Mean Encoding
• Feature scaling

Recommended books

• Understanding Analysis - Abbot

• Linear Algebra Done Right - Sheldon Axler

• Linar Algebra - Stephen H. Friedberg, Arnold J. Insel, and Lawrence E. Spence

• Topology Through Inquiry - Michael Starbid and Francis Su

• Differential Equations with Boundary-Value Problems - Dennis G. Zill and Michael R. Cullen

• Contemporary Abstract Algebra - Joseph A. Gallian

• A Geometric Approach to Differential Forms - David Bachman

• An Introduction to Manifolds - Loring W. Tu

• Calculus: Early Trascendentals James Stewart

• Physics for Scientists and Engineers

• Modern Physics

• Introduction to Abstract Mathematics (Logics & Proof)

• Mathematical Statistics with Applications

• Fundamentals of Differential Equations

• Discrete and Combinatorial Mathemtatics

• Partial Differential Equations

• Fundamentals of Complex Analysis

• Abstract Algebra

• Advanced Calculus

• Elements of Point Set Topology