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Category upCore Concepts

Math and Logic

Math and logic are the cornerstones of almost all computer science problems.

  • Probability and Statistics (21)
  • Geometry (14)
  • Optimization (10)
  • Matrix (9)
  • Training (5)
  • Regression (5)
  • Array (3)
  • Prime Numbers (3)
  • PCA (2)
  • CPU (2)
  • Formal Languages (2)
  • Recursion (2)
  • Image Processing (2)
  • Linked List (2)
  • Naive Bayes (2)

>> How to Convert Radians to Degrees and Vice Versa?

>> Confidence Intervals

  • Probability and Statistics

>> How to Rotate a Two-Dimensional Array

>> Unit Digit in Exponentiation: How to Compute It?

>> What Is Singular Value Decomposition?

>> Algorithm for Online Outlier Detection in Time Series

  • Probability and Statistics

>> Bitwise Shift Operators

>> Finding a Matrix Determinant

>> Recognizable vs. Co-recognizable vs. Decidable Languages

  • Formal Languages

>> Infix, Prefix, and Postfix Expressions

>> From Recursion to Iteration – Factorial Function Example

>> The Stable Marriage Problem

>> Difference Between Fundamental Matrix and Essential Matrix

>> XOR Swap

>> Modulus Division

>> What Are Regular Languages?

  • Formal Languages

>> How to Check if a Line Segment Intersects a Rectangle?

>> What Is Cosine Similarity?

>> Differences Between Homography and Affine Transformation

  • Image Processing

>> Information Theory

>> The 3Sum Problem

>> Introduction to Gibbs Sampling

  • Probability and Statistics

>> Statistical Independence

  • Probability and Statistics

>> Bayes’ Theorem

  • Probability and Statistics

>> Probability: Joint vs. Marginal vs. Conditional

  • Probability and Statistics

>> Combinatorial Optimization

>> Finding the Digital Root

>> Why Use a Surrogate Loss

>> Calculating the Average of a Set of Circular Data

  • Probability and Statistics

>> How to Calculate the Angle from Rotation Matrix

>> Optimization: Local vs. Global Optima

>> Random Variables

  • Probability and Statistics

>> Calculating the Odds of a Team Winning a Sports Match Given Full History

  • Probability and Statistics

>> Optimization: Objective Functions, Decision Variables and Constraints

>> Finding Neighbors of a Matrix Cell

>> The Direct Linear Transform

>> The XOR Operation

>> What Is Constrained Optimization?

>> How to Project a 3D Point Onto a 2D Plane?

>> What Is “Energy” in Image Processing?

  • Image Processing

>> Deep Dive Into Optimization

>> Correcting Fisheye Images

>> The Mahalanobis Distance

  • Probability and Statistics

>> Fast Fourier Transform (FFT)

>> Sampling From the Exponential Distribution

  • Probability and Statistics

>> Fuzzy Logic Explained

>> What’s a Hypothesis Space?

>> Converting Floats into Fractions

>> Interpolation and Regression: Similarities and Differences

>> Fast Algorithms for Solving a System of Linear Equations

>> Intersection Over Union for Object Detection

>> Determining the Most Distant Pair of Points

>> Robust Estimators in Robust Statistics

  • Probability and Statistics

>> Transfer Learning vs Domain Adaptation

>> Antipatterns: Magic Numbers

>> How to Test if a Number Is a Fibonacci Number

>> What Is Depth in a Convolutional Neural Network?

>> What Is the Difference Between Natural Cubic Spline, Hermite Spline, Bézier Spline and B-Spline?

>> Pseudo-Polynomial vs. Polynomial Complexity

>> Introduction to Curve Fitting

>> What Is a Random Walk?

  • Probability and Statistics

>> An Introduction to the Hidden Markov Model

>> Multi-Verse Optimizer

>> Master Theorem for Asymptotic Analysis

>> The Monty Hall Problem

  • Probability and Statistics

>> Basics of Polynomial Interpolation

>> The Importance of Central Limit Theorem

  • Probability and Statistics

>> Why Are Floating Point Numbers Inaccurate?

>> What Is Selection Bias and How Can We Prevent It?

>> Streaming Median

  • Probability and Statistics

>> Circle Line-Segment Collision Detection Algorithm

>> Generating Permutations with Repetition

>> How Many Principal Components to Take in PCA?

>> Fastest Algorithm to Find Prime Numbers

>> Intuitive Explanation of the Expectation-Maximization (EM) Technique

  • Probability and Statistics

>> An Algorithm for Inflating and Deflating Polygons

>> Extended Euclidean Algorithm

>> Choosing the best q and p from ACF and PACF plots in ARMA-type modeling

  • Probability and Statistics

>> Binary Trees vs. Linked Lists vs. Hash Tables

  • Hashing

>> Sine Cosine Algorithm

>> Finding Three Elements in an Array Whose Sum Is Closest to a Given Number

>> How to Find an Area of Overlapping Rectangles

>> Grey Wolf Optimization Algorithm

>> Dijkstra vs Floyd-Warshall Algorithms

>> The Most Efficient Way to Implement an Integer Based Power Function

>> Finding the Next Smaller Element for Each Element in an Array

>> Algorithms to Check If a Number Is a Power of 2

>> Primality Test: Miller-Rabin Method

>> Fermat Primality Test

>> Pairing Socks From a Pile Efficiently

>> Polynomial Addition and Multiplication Using Linked List

>> Ackermann Function

>> Alternatives of Ten – Binary, Octal, Hexadecimal

>> How to Improve Naive Bayes Classification Performance?

  • Probability and Statistics

>> Ugly Duckling Theorem

>> Gradient Descent Equation in Logistic Regression

>> Correlated Features and Classification Accuracy

  • Probability and Statistics

>> Find Local Minimum in N x N Matrix

>> Using Min/Max Within an Integer Linear Program

>> How to Determine if a List of Polygon Points Are in Clockwise Order

>> Haversine Formula

>> Sum of Digits in Factorial

>> The Pigeonhole Principle

>> Matrix Multiplication Algorithm Time Complexity

>> Time Complexity of Euclid’s Algorithm

>> Greedy Algorithm to Find Minimum Number of Coins

>> The Difference Between Lower Bound and Tight Bound

>> Maximizing Profit for Given Stock Quotes

>> Understanding Forecast Accuracy: MAPE, WAPE, WMAPE

>> Maximum Single-Sell Profit

>> How to Calculate the Area of a 2D Polygon?

>> What the Correlation Coefficient Actually Represents

>> How to Prove That a Problem Is NP-Complete?

>> What Is the Difference Between Gradient Descent and Gradient Ascent?

>> Finding XOR of All Numbers in a Given Range

>> Boolean Algebra: Basic Laws

>> Why Does the Cost Function of Logistic Regression Have a Logarithmic Expression?

>> Linear Regression vs. Logistic Regression

>> First-Order Logic

>> Propositional Logic

>> SAT and 3-SAT – Cook-Levin Theorem

>> A Simple Explanation of Naive Bayes Classification

  • Probability and Statistics

>> Euclidean Distance vs Cosine Similarity

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