Introduction Clustering is a technique to group data points into various subgroups such that each point within each subgroup are similar. It is an unsupervised algorithm and there are no labels or ground truth. Mini batch K Means is a variant of the K−Means algorithm that trains from batches at random from memory. In this article let us understand Mini Batch K−Means in detail. Before moving on to Mini Batch K−Means let us have a look at K−Means in general The K−Means clustering approach The K−Means is an iterative approach that tries to group data points into K separate subgroups ... Read More

Introduction Ensemble Classifiers are class models that combine the predictive power of several models to generate more powerful models than individual ones. A group of classifiers is learned and the final is selected using the voting mechanism. Data mining is the process of exploring and analyzing large datasets to find and explore important patterns, relationships, and information. The extracted information can then be used to solve business problems, predict trends and generate strategic plans by organizations. Ensemble classifiers are used in data mining to perform such tasks. Why do we need ensemble classifiers? Ensemble models(classifiers) can solve many problems and ... Read More

Introduction Logistic Regression is the simplest of all classification algorithms in Machine Learning. Logistic Regression uses log loss or cross−entropy loss instead of mean squared error for loss function. Since we already have linear regression why do we need Logistic Regression for classification and why can't use Linear Regression for classification? Let us understand this fact through this article and explore the cost function used in Logistic Regression in detail. Why do we need Logistic Regression and can't use Linear Regression? In Linear Regression, we predict a continuous value. If we fit Linear Regression to the classification task, the line ... Read More

Introduction The Internet of Things (IoT) is the network of embedded devices, smart devices, and computers infused with sensors that can communicate with each other as well as send and receive packets of data through the network. These devices can communicate with the real world through sensors and can control or move a system using actuators that are the heart of an IoT system. Machine learning and IoT have a very association in the sense that many organizations using machine learning and Ai based applications rely on terabytes of data captured through IoT and embedded devices. This da can be ... Read More

Introduction Boosting is a class of ensemble modeling algorithms where we build a strong model from several weak models. In boosting all the classifiers are present in series. First, a single model is trained on the actual training data. Then the second classifier is built which is trained on the errors produced by the first model and it tries to correct the errors produced by the previous model. This process is repeated continuously and new models are added till there are non−errors and the prediction on training data is accurate or we have reached the maximum threshold of models to ... Read More

A queue is a linear data structure that works on the FIFO property where each element is added to the queue from the rear and the elements are extracted from the front and use the principle of first in first out. In the list, we can access every element while in the queue we can only access the first element. In this tutorial, we are going to see two methods of how to convert a queue into the list. Creating a Queue in Python Queue in a linear data structure which works on the first in first out property and ... Read More

Permutations and Combinations refer to the arrangements of objects in mathematics. Permutation − In permutation, the order matters. Hence, the arrangement of the objects in a particular order is called a permutation. Permutations are of two types − Permutation with repetition Suppose we have to make a three-digit code. Some possible numbers are 123, 897, 557, 333, 000, and 001. So how many numbers can we make like this? Let us look at it this way− In the once place, we have ten options − 0-9 Similarly, at the tenth and the hundredth place also, we have ten options. 0-9. ... Read More

HCF or the Highest common factor of two or more numbers refers to the highest number which divides them. A rational number is the quotient p/q of two numbers such that q is not equal to 0. Problem Statement Given an array with fractional numbers, find the HCF of the numbers. Example 1 Input [{4, 5}, {10, 12}, {24, 16}, {22, 13}] Output {2, 3120} Explanation The fractional numbers given are: 4/5, 10/12, 24/16 and 22/13 2/3120 is the largest number that divides all of them. Example 2 Input [{18, 20}, {15, 12}, {27, 12}, {20, 6}] ... Read More

In mathematics, a Stella Octangula number is a figurate number based on the Stella Octangula, of the form n(2n2 − 1). Stella Octangula numbers which are perfect squares are 1 and 9653449. Problem Statement Given a number n, check whether it is the Stella Octangula number or not. The sequence of Stella Octangula numbers is 0, 1, 14, 51, 124, 245, 426, 679, 1016, 1449, 1990 Example1 Input x = 14 Output Yes Explanation $$\mathrm{For\: n = 2, expression \:n\lgroup 2n^2 – 1\rgroup is\: 14}$$ Example2 Input n = 22 Output No Explanation $$\mathrm{There \:is\: no\: ... Read More

According to Nicomachus’ Theorem, the sum of the cubes of the first n integers is equal to the square of the nth triangular number. Or, we can also say − The sum of cubes of first n natural numbers is equal to square of sum of first natural numbers. Putting it algebraically, $$\mathrm{\displaystyle\sum\limits_{i=0}^n i^3=\lgroup \frac{n^2+n}{2}\rgroup^2}$$ Theorem $$1^3 = 1$$ $$2^3 = 3 + 5$$ $$3^3 = 7 + 9 + 11$$ $$4^3 = 13 + 15 + 17 + 19\vdots$$ Generalizing $$n^3 =\lgroup n^2−n+1\rgroup+\lgroup n^2−n+3\rgroup+⋯+\lgroup n^2+n−1\rgroup$$ Proof By Induction For all n Ε Natural ... Read More