فهرست مطالب

• Preface
• Chapter 1. Basic Math and Calculus Review
• Number Theory
• Order of Operations
• Variables
• Functions
• Summations
• Exponents
• Logarithms
• Euler’s Number and Natural Logarithms
• Limits
• Derivatives
• Integrals
• Conclusion
• Exercises
• Chapter 2. Probability
• Understanding Probability
• Probability Math
• Binomial Distribution
• Beta Distribution
• Conclusion
• Exercises
• Chapter 3. Descriptive and Inferential Statistics
• What Is Data?
• Descriptive Versus Inferential Statistics
• Populations, Samples, and Bias
• Descriptive Statistics
• Inferential Statistics
• The T-Distribution: Dealing with Small Samples
• Big Data Considerations and the Texas Sharpshooter Fallacy
• Conclusion
• Exercises
• Chapter 4. Linear Algebra
• What Is a Vector?
• Linear Transformations
• Matrix Multiplication
• Determinants
• Special Types of Matrices
• Systems of Equations and Inverse Matrices
• Eigenvectors and Eigenvalues
• Conclusion
• Exercises
• Chapter 5. Linear Regression
• A Basic Linear Regression
• Residuals and Squared Errors
• Finding the Best Fit Line
• Overfitting and Variance
• Stochastic Gradient Descent
• The Correlation Coefficient
• Statistical Significance
• Coefficient of Determination
• Standard Error of the Estimate
• Prediction Intervals
• Train/Test Splits
• Multiple Linear Regression
• Conclusion
• Exercises
• Chapter 6. Logistic Regression and Classification
• Understanding Logistic Regression
• Performing a Logistic Regression
• Multivariable Logistic Regression
• Understanding the Log-Odds
• R-Squared
• P-Values
• Train/Test Splits
• Confusion Matrices
• Bayes’ Theorem and Classification
• Receiver Operator Characteristics/Area Under Curve
• Class Imbalance
• Conclusion
• Exercises
• Chapter 7. Neural Networks
• When to Use Neural Networks and Deep Learning
• A Simple Neural Network
• Backpropagation
• Using scikit-learn
• Limitations of Neural Networks and Deep Learning
• Conclusion
• Exercise
• Chapter 8. Career Advice and the Path Forward
• Redefining Data Science
• A Brief History of Data Science
• Finding Your Edge
• What to Watch Out For in Data Science Jobs
• Does Your Dream Job Not Exist?
• Where Do I Go Now?
• Conclusion
• Appendix A. Supplemental Topics
• Appendix B. Exercise Answers
• Index