Andrew Gurung
  • Introduction
  • Data Science
    • Natural Language Processing
      • Sentiment analysis using Twitter
    • Linear Algebra
      • Linear algebra explained in four pages
      • Vectors
        • Vector Basics
        • Vector Projection
        • Cosine Similarity
        • Vector Norms and Orthogonality
        • Linear combination and span
        • Linear independence and Basis vectors
      • Matrices
        • Matrix Arithmetic
        • Matrix Operations
        • Functions and Linear Transformations
        • Matrix types
      • Eigendecomposition, Eigenvectors and Eigenvalues
      • Principle Component Analysis (PCA)
      • Singular-Value Decomposition(SVD)
      • Linear Algebra: Deep Learning Book
    • Calculus
      • Functions, Limits, Continuity and Differentiability
      • Scalar Derivative and Partial Derivatives
      • Gradient
      • Matrix Calculus
      • Maxima and Minima using Derivatives
      • Gradient Descent and its types
    • Statistics and Probability
      • Probability Rules and Axioms
      • Types of Events
      • Frequentist vs Bayesian View
      • Random Variables
      • MLE, MAP, and Naive Bayes
      • Probability Distributions
      • P-Value and hypothesis test
    • 7 Step DS Process
      • 1: Business Requirement
      • 2: Data Acquisition
      • 3: Data Processing
        • SQL Techniques
        • Cleaning Text Data
      • 4: Data Exploration
      • 5: Modeling
      • 6: Model deployment
      • 7: Communication
    • Miscellaneous
      • LaTeX commands
  • Computer Science
    • Primer
      • Big O Notation
  • Life
    • Health
      • Minimalist Workout Routine
      • Reddit FAQ on Nootropics
      • Hiking/Biking Resources
    • Philosophy
      • Aristotle's Defense of Private Property
    • Self-improvement
      • 100 Mental Models
      • Don't break the chain
      • Cal Newport's 5 Productivity tips
      • Andrew Ng's advice on deliberate practice
      • Atomic Habits
      • Turn sound effects off in Outlook
    • Food and Travel
      • 2019 Guide to Pesticides in Produce
      • Recipe
        • Spicy Sesame Noodles
      • Travel
        • Hiking
    • Art
      • Scott Adams: 80% of the rules of good writing
      • Learn Blues Guitar
    • Tools
      • Software
        • Docker
        • Visual Studio Code
        • Terminal
        • Comparing Git Workflow
      • Life Hacks
        • DIY Deck Cleaner
  • Knowledge Vault
    • Book
      • The Almanack of Naval Ravikant
    • Media
    • Course/Training
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  1. Data Science
  2. 7 Step DS Process

1: Business Requirement

Previous7 Step DS ProcessNext2: Data Acquisition

Last updated 5 years ago

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Apart from learning technical skills like math, stats, computer science, machine learning algorithms, you need to have some business training to solve real business problems.

Resources to improve your business acumen for data science

Books:

Articles:

Data Science for Business
Lean Analytics
Story Telling with Data
10 Reads for Data Scientists Getting Started with Business Models