Trigonometric Functions

Lengths and ratios of right-angled triangles (Basic knowledge) Trigonometric functions (sin, cos, tan, etc.) are frequently used in machine learning as tools to effectively work with angles, periods, rotations, and positions. Once the angles of a right triangle are determined, the ratio is also determined. Commercially available set squares have well-known trigonometric ratios. As shown in the figure, the… Read More »

Merge Sort (basic algorithm)

Merge sort is an efficient sorting algorithm based on the divide-and-conquer paradigm. It recursively divides a large array into smaller sub-arrays, sorts those sub-arrays, and then merges them back together to create the final sorted array. Features: Algorithm Steps Example Let’s look at the process of sorting the array [8, 3, 1, 7, 0, 10, 2] using merge sort. Python… Read More »

Levenshtein distance(Basic algorithm)

The Levenshtein distance (also known as edit distance) is a metric for measuring the similarity between two strings. It’s defined as the minimum number of operations required to transform one string into the other using insertion, deletion, and substitution operations. We can efficiently calculate the Levenshtein distance using dynamic programming. Example: Levenshtein Distance between “kitten” and “sitting” Let’s… Read More »

Quicksort (Basic Algorithm)

Quicksort is an efficient sorting algorithm based on the divide-and-conquer paradigm. It works as follows: Example of Quicksort: Let’s consider sorting the following array [5, 2, 8, 1, 9, 4, 7]. Python Code Example Quicksort Characteristics: Pivot Selection Strategies: The choice of pivot significantly impacts Quicksort’s performance. Quicksort is widely used due to its relatively simple implementation and speed.… Read More »

Bubble Sort (Basic algorithm)

Bubble sort is one of the simplest sorting algorithms. It works by repeatedly stepping through the list, comparing adjacent elements and swapping them if they are in the wrong order. Larger elements “bubble” to the end of the list with each pass. This process continues until the entire list is sorted in ascending (or descending) order. Example: Let’s… Read More »

k-Means Clustering (basic algorithms -machine learning )

k-means clustering is an unsupervised learning algorithm used to partition a given dataset into several groups (clusters). It works by iteratively updating the “centroids” – the center points of each cluster – and assigning data points to the closest centroid. Features: Steps of k-Means Clustering Let’s consider the following 2D dataset as an example: We want to cluster… Read More »

Basic Mathematics and Python (Level-2)

“Learn machine learning in Python while understanding the underlying mathematics and algorithms.”  Scheduled for release at the end of March Chapter 1: Basic Mathematics and Python CodeMatrices/SequencesVectorsCombinatorics and ProbabilityComplex Numbers and Complex EquationsTrigonometric FunctionsExponential and Logarithmic FunctionsEquations and CurvesLimitsDifferential CalculusIntegral Calculus Chapter 2: Linear AlgebraAlgorithm 1Algorithm 2Algorithm 3 ・・・ Chapter 3: Machine Learning・・・・