Programming Articles - Page 275 of 3363

In this problem, we will find all unique characters of the string with their first index, which is present in the string, after incrementing all characters of the given string by K. For a problem solution, we can take each unique character of the given string. Next, we can update each character individually and check whether the updated character is present in the string and not updated to another character to get the answer. Problem statement − We have given a string alpha and positive integer K. We need to increment each character’s ASCII value of the given string by ... Read More

In this problem, we will find each word of the string which comes after all words of the ‘words’ array. The first approach to solve the problem is to split the string into words and match elements of the words[] array with the string words. If we find words[] array’s element in the same order inside the string, we print the next word of the string. Another approach is to create a string of all elements of the words[] array. After that, we can find that string as a substring in the alpha string. If we find it as a ... Read More

In this problem, we will find the string of length equal to the given string so that when we sum both strings, we get the palindromic strings. Here, we can find another string such that the sum of both becomes 99999…, the largest palindromic string of the same length. If the given string starts with the ‘9’, we can find another string such that the sum of both becomes ‘11111…’. Problem statement – We have given a num string containing the numeric digits. We need to find the numeric string of the same length without leading zeros so that ... Read More

Python provides a robust set of tools and libraries to generate random numbers within a specific range and calculate their average. We can use the Numpy library, statistics module, random module, and random.choice function etc to Randomly generate numbers within a range and find their average. In this article, we will use these methods to generate random numbers and find their average. Algorithm A general algorithm to generate random numbers and find the average using Python is as follows: Generate random numbers within a range Store these numbers in a list or array. Calculate the average of the ... Read More

In this problem, we will count ways to partition the given string into the K substrings such that it follows the condition given in the problem statement. We will use the recursion to solve the problem. Also, we will use the tabular dynamic programming approach to solve the problem efficiently. Problem statement − We have given a string named bin_Str of a particular length. The string contains only numeric digits from ‘0’ to ‘9’. We need to count the number of ways to partition the string in K substrings such that it follows the below condition. The substring should ... Read More

We will use HTML and CSS to align dropdown widgets in Jupyter. We may modify the alignment of the dropdown widget by adding certain CSS classes to it. This allows us to place the dropdowns in our Jupyter notebook either side by side or one below the other, making it seem visually attractive. Here is a simple method to help us align dropdown widgets in Jupyter and improve the user experience. The following syntax is used in the examples − Dropdown() The Dropdown() is a built-in function that follows the module named ipywidgets and it builds the list ... Read More

Understanding various techniques for estimating covariance matrices is essential in the field of machine learning. The Scikit-Learn package has two popular covariance estimation methods, which will be compared in this article. Ledoit-Wolf Oracle Approximating Shrinkage (OAS) Estimation. Introduction to Covariance Estimation Before we begin comparing, let's establish covariance estimation. In statistics and data analysis, covariance estimation is a technique used to understand and quantify the relationship between multiple dimensions or features in your data collection. This becomes much more important when working with multidimensional data sets because understanding the relationships between various variables may improve the performance of your machine ... Read More

Several strategies stand out in the vast field of machine learning because of their distinctive approaches and effectiveness in handling challenging jobs. Learning Vector Quantization (LVQ), which presents a compelling alternative to conventional classification algorithms, is one such method. With the use of real-world examples, this essay delves deeply into LVQ, covering both its core ideas and prospective applications. Understanding Learning Vector Quantization The supervised learning approach known as Learning Vector Quantization, or LVQ for short, is prototype-based. It uses a competitive (or winner-takes-all) learning technique and is classified as an artificial neural network. With the use of this method, ... Read More

Pandas DataFrame is a part of the Data Structure that is used to represent the 2D structure in tabular form(rows and columns). In Python, we have some built-in functions like eq(), any(), loc[], and, apply() that can be used to search a value within a Pandas DataFrame row. For example- Searching a value is defined by the availability of any specific data. Syntax The following syntax is used in the examples − DataFrame() This is an in-built function in Python that follows the pandas module and show the 2D rows and column into a single frame. eq() This ... Read More

In this problem, we will count substrings of the given binary string containing the number of ‘0’ and ‘1’ characters in the X : Y ratio. The naïve approach finds all substrings of the given binary string, counts ‘0’ and ‘1’, and checks whether the counts are in the X : Y ratio. The efficient approach uses the prefix sum technique to solve the problem. Problem statement − We have given a binary string of length bin_len. We need to count substrings having a number of 0s and 1s in the ratio of X : Y. Sample examples Input ... Read More