Top 100 mathematics keywords for Data Science – Part 1

Whoever is teaching you data science without teaching you Mathematics especially optimization is not teaching it right to you. That’s my biggest learning from Master of Data Science at IIT Gandhinagar – it will take you good 2 years to learn the related mathematics in all four major areas below. It’s not possible to learn this mathematics in few weeks even months, it will take a year or two. Here are the top 100 mathematical keywords commonly used in Data Science, Machine Learning, and AI (sourced from ChatGPT):

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1. Probability & Statistics

1. Probability
2. Random Variable
3. Expectation (Mean)
4. Variance
5. Standard Deviation
6. Skewness
7. Kurtosis
8. Probability Density Function (PDF)
9. Cumulative Distribution Function (CDF)
10. Bayes’ Theorem
11. Conditional Probability
12. Joint Probability
13. Likelihood
14. Maximum Likelihood Estimation (MLE)
15. Prior Probability
16. Posterior Probability
17. Hypothesis Testing
18. Null Hypothesis (H0H_0)
19. Alternative Hypothesis (HAH_A)
20. p-value
21. Confidence Interval
22. T-test
23. Chi-square Test
24. ANOVA (Analysis of Variance)
25. Z-score
26. Central Limit Theorem (CLT)
27. Law of Large Numbers
28. Binomial Distribution
29. Poisson Distribution
30. Normal Distribution
31. Gaussian Distribution
32. Exponential Distribution
33. Log-normal Distribution

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2. Linear Algebra

1. Vector
2. Matrix
3. Scalar
4. Tensor
5. Eigenvalues
6. Eigenvectors
7. Determinant
8. Singular Value Decomposition (SVD)
9. Principal Component Analysis (PCA)
10. Covariance Matrix
11. Orthogonality
12. Dot Product
13. Cross Product
14. Matrix Multiplication
15. Rank of a Matrix
16. Trace of a Matrix
17. Identity Matrix
18. Inverse Matrix
19. Transpose of a Matrix
20. Diagonalization
21. Gram-Schmidt Process

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3. Calculus & Optimization

1. Derivative
2. Partial Derivative
3. Gradient
4. Hessian Matrix
5. Jacobian Matrix
6. Chain Rule
7. Gradient Descent
8. Stochastic Gradient Descent (SGD)
9. Learning Rate
10. Loss Function
11. Cost Function
12. Objective Function
13. Convex Function
14. Concave Function
15. Local Minimum
16. Global Minimum
17. Local Maximum
18. Global Maximum
19. Lagrange Multipliers
20. Optimization
21. Regularization
22. L1 Regularization (Lasso)
23. L2 Regularization (Ridge)

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4. Machine Learning Metrics & Functions

1. Accuracy
2. Precision
3. Recall
4. F1-score
5. ROC Curve
6. AUC (Area Under Curve)
7. Confusion Matrix
8. True Positive (TP)
9. True Negative (TN)
10. False Positive (FP)
11. False Negative (FN)
12. Logarithm (Log)
13. Exponential Function
14. Softmax Function
15. Sigmoid Function
16. Activation Function
17. Cross-Entropy Loss
18. Mean Squared Error (MSE)
19. Mean Absolute Error (MAE)
20. Hinge Loss
21. Kullback-Leibler Divergence
22. Entropy
23. Information Gain

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These 100 mathematical keywords form the foundation of Data Science, Machine Learning, and AI.

• Email me: Neil@HarwaniSytems.in
• Website: www.HarwaniSystems.in
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