Supervised learning, one of the most used methods in ML, takes both training data (also called data samples) and its associated output (also called labels or responses) during the training process. The major goal of supervised learning methods is to learn the association between input training data and their labels. For this it performs multiple training data instances.Let’s understand its working with the help of below given example −Suppose we have, Input variables − m andOutput variable − NThe mapping function from the input to output is as follows −𝑁 = 𝑓(𝑚)To learn such mapping function, we need an algorithm ... Read More

There are four learning styles in machine learning algorithms. Let’s have a look at them −Supervised LearningSupervised learning, one of the most used methods in ML, takes both training data (also called data samples) and its associated output (also called labels or responses) during the training process. The major goal of supervised learning methods is to learn the association between input training data and their labels. For this it performs multiple training data instances.Based on machine learning based tasks, we can divide supervised learning algorithms in two classes namely Classification and Regression.Unsupervised LearningUnsupervised learning methods, (opposite to supervised learning methods) ... Read More

In this article, we will find out the number of subarrays having a sum less than K using C++. In this problem, we have an array arr[] and an integer K. So now we have to find subarrays that have a sum less than K. Here is the example −Input : arr[] = {1, 11, 2, 3, 15} K = 10 Output : 4 {1}, {2}, {3} and {2, 3}Approach to Find SolutionNow we will use two different methods to solve the given problem −Brute ForceIn this approach, we will iterate through all the subarrays and calculate their sum and ... Read More

The Python ecosystem, growing at a rapid pace day by day, became the dominant platform for machine learning. Here we will discover the most useful components of the Python ecosystem for machine learning. Let’s get started.SciPySciPy, pronounced as “Sigh Pie”, is an ecosystem of Python open-source libraries for performing Mathematical, Scientific, and Engineering computations. SciPy is comprised of the following core packages relevant to machine learning −NumPy − NumPy is a base N-dimensional array package for SciPy that allows us to efficiently work with data in arrays.Matplotlib − Matplotlib is used to create comprehensive 2-D charts and plots from data.Pandas ... Read More

From process automation to web development to AI-based projects to machine learning, Python is used everywhere, and it helps developers to be productive and confident about the software they are building. Today, because of the benefits like simplicity, consistency, extensive set of libraries, platform independence, flexibility, and a wide community support, Python has become one of the most favored programming languages among machine learning professionals.Simplicity and Consistency − Machine learning relies on complex algorithms and workflows, but it is Python’s simplicity that allows machine learning developers to build reliable applications. Python is so simple that the developers do not need ... Read More

In this article, we will solve the number of subarrays having sum in a given range using the C++ program. We have an array arr[] of positive integers, and a range {L, R} and we have to calculate the total number of subarrays having sum in the given range form L to R. So here is the simple example for the problem −Input : arr[] = {1, 4, 6}, L = 3, R = 8 Output : 3 The subarrays are {1, 4}, {4}, {6}. Input : arr[] = {2, 3, 5, 8}, L = 4, ... Read More

While machine learning is rapidly evolving, it still has a long way to go. The reasons behind this are the various challenges an ML practitioner faces while developing an application. Let’s take a look at these challenges −Data collection − Data plays the most important role in developing any machine learning application. Most of the work of an ML practitioner lies in collecting good quality data. If you are a beginner and want to experiment with machine learning, you can find datasets from Kaggle or UCI ML Repository. But if you want to implement real case scenarios or need to ... Read More

In this article, we will provide a brief explanation on solving the number of subarrays that have bitwise OR>=K in C++. So we have an array arr[] and an integer K, and we have to find the number of subarrays that have OR(bitwise or) greater than or equal to K. So here is the example of the given problem −Input: arr[] = {1, 2, 3} K = 3 Output: 4 Bitwise OR of sub-arrays: {1} = 1 {1, 2} = 3 {1, 2, 3} = 3 {2} = 2 {2, 3} = 3 {3} = 3 4 sub-arrays have ... Read More

To understand various components of a machine learning algorithm, we first understand the definition of machine learning given by Professor Mitchell −“A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.”As we can see the above definition, the main components of any machine learning algorithm are Task(T), Performance(P), and Experience(E).Based on these three components, let’s simplify the definition of machine learning −Machine learning is a subset of Artificial Intelligence (AI) and a field ... Read More

Do you know how much data a person is creating every second? The numbers are astonishing. According to Domo, during 2020 every person created 1.7MB of data every second and it is not going to slow down in the future as well. It would not be wrong to say that we are living in the 'age of data'. One of the biggest challenges in front of businesses and organizations is to make sense of all the data. They are trying to deal with it by creating intelligent systems using the concepts and methodologies from Machine Learning (ML), one of the ... Read More