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Introduction Statistical modeling is a powerful technique used in data analysis to uncover patterns, relationships, and trends within datasets. By applying statistical methods and models, researchers and analysts can gain insights, make predictions, and support decision-making processes. R, a popular programming language for statistical computing and graphics, offers a wide range of tools and libraries for statistical modeling. In this article, we will delve into the world of statistical modeling with R, exploring its key concepts, techniques, and applications. Understanding Statistical Modeling Statistical modeling is the process of formulating mathematical representations or models that describe the underlying structure of data. ... Read More
In digital signal processing and image processing, the convolution is a crucial mathematical operation. The primary function of the convolution is to combine two signals to produce a resulting signal. The resulting signal specifies the interaction between the two signals that we combined. In MATLAB, we can perform the convolution of two signals by using a built−in function ‘conv()’. This MATLAB function performs the convolution by using a discrete approximation of the integration. For this, it uses discrete samples of the input signals. Syntax The following is the general syntax for the ‘conv()’ function, a = conv(x, y, shape); ... Read More
Introduction Machine learning has revolutionized the field of artificial intelligence and data analysis. With the ever-increasing availability of data and computational power, machine learning algorithms have become essential tools for extracting valuable insights and making predictions from large and complex datasets. Among the various programming languages used in machine learning, R stands out as a popular choice due to its versatility and extensive library support. In this article, we will provide a comprehensive introduction to R for machine learning, exploring its capabilities, libraries, and applications. What is R? R is a powerful statistical programming language widely used for data analysis, ... Read More
Introduction Data visualization plays a crucial role in analyzing and communicating insights from complex datasets. With the advent of advanced data visualization tools and techniques, researchers and analysts can now present data in more meaningful and engaging ways. In this article, we will explore advanced data visualization techniques using R, a powerful programming language widely used for data analysis and visualization. We will delve into various subheadings that cover different aspects of data visualization in R, providing detailed insights and examples. Exploratory Data Analysis (EDA) Visualizations Exploratory Data Analysis (EDA) involves visualizing and understanding the underlying patterns and relationships in ... Read More
The NumPy library has a wide range of tools which perform the comparison and filtering of the arrays. The comparison of arrays will be done element by element in row wise and column wise based on the dimension of the array. When we want to retrieve a particular array element, then we can apply the filtering. NumPy is abbreviated as Numerical python, which is used to perform mathematical and scientific calculations on multidimensional arrays and matrices. There are different functions and methods available in NumPy to perform the filtering and comparison of the arrays. Comparing NumPy Arrays Following are ... Read More
Machine Learning is a field of study of smart and efficient use of data and existing algorithms to make machines imitate humans in performing tasks with greater accuracy. It is one of the fastest growing branches in Computer Science , along with Artificial Intelligence. Machine Learning can be rightly called as a subset of artificial intelligence, as a lot of ML algorithms and results are of AI . Automation of Routine Tasks We are living in a fast moving world where people have no time to carry out their regular chores manually. Nearly half of the population ... Read More
Python is a powerful language to be used for performing various statistical tests. One such statistical test is the Welch’s t-test. When there are two datasets with equal variances and you have to find out whether their means are the same or not, then using a two sample t-test would be wise enough. However, if the variances of the two datasets are not the same, then Welch’s t-test should be used to compare the means. Syntax stats.ttest_ind(dataset_one, dataset_two, equal_var = False/True) Here, ttest_ind is the function that performs Welch’s t-test. It takes three parameters, The first ... Read More
In this article, we will learn to configure the Run button for functions in MATLAB. In MATLAB, the `Run` button is used execute a MATLAB code. Also, MATLAB allows us to configure the `Run` button to execute a specific user defined function. Algorithm to Configure Run Button The step−by−step process to configure the Run button to execute a specific function in MATLAB is explained below: Step 1 − Firstly, create a new script to open the MATLAB editor. Step 2 − Define or create a function for which you want to configure the Run button. For example, we create ... Read More
ANN or artificial neural networks are the computing systems developed by taking inspiration from the biological neural networks; the human brain being its major unit. These neural networks are made functional with the help of training that follows some kind of a learning rule. A learning rule in ANN is nothing but a set of instructions or a mathematical formula that helps in reinforcing a pattern, thus improving the efficiency of a neural network. There are 6 such learning rules that are widely used by neural networks for training. Hebbian Learning Rule Developed by Donald Hebb in 1949, ... Read More
Intelligence can be defined as the ability to learn, understand and apply knowledge and skills. Human Intelligence is a multifaceted concept that encompasses many types. Before understanding the types of human intelligence let’s have a look at the basic difference between Human intelligence and Artificial intelligence − Human intelligence is associated with creativity, emotion, flexibility, and the ability to learn from a wide range of experiences. Unlike human intelligence, artificial intelligence cannot think creatively, experience emotions, adapt to new circumstances, or understand ethical and moral issues. While machine learning and human learning share some similarities, reinforcement learning uses ... Read More