What is the importance of Data Analysis at present? The use of data analytics in finance is expanding globally. From big financial names to stock market analysis, financial markets rely on data analytics to better understand their consumers and trends. What are the skills required for Data Analysis? If you’re wondering who analyzes large datasets in a huge financial organization, financial data analysts are professionals who analyze the data of any organization to make accurate business decisions for their company. One of their key responsibilities is analyzing and assessing the firms' financial information. Often, in a firm, Financial Data ... Read More

What is Pytorch? Pytorch is a Python - based framework in machine learning primarily used for scientific computations and to build deep learning models. A Tensor is a popular concept in Machine learning and Data science. Tensors are a generalized term for matrices and vectors. In simple words, Tensors can be anything - a n-dimensional array, a vector, or a matrix. In this article, we will be looking at the multiple methods used to create Tensors in Pytorch. Method of Creating Tensors Tensors can be created in multiple methods. Some of the important methods are listed below. ... Read More

Introduction Machine learning is a common topic in the technology and business world. Machine learning is a technology that processes the raw data, provides helpful information, including data prediction and analysis, and releases final statistics reports. In short, ML helps process the data and produces reports to achieve the set goals. It uses various high-end algorithms and paradigms to engage with the solutions. Artificial Intelligence is the fastest-growing technology under which machine learning and deep learning work. In this article, you will see the top 7 hackathons and technical events of machine learning, that are organized worldwide. This includes ... Read More

Introduction The Grubbs test is a statistical hypothesis testing method to detect outliers in a dataset. Outliers are the observations that disburse the data distribution and are also known as anomalies. The dataset with outliers tends to overfit more than data with a Normal/Gaussian distribution. Hence, it is necessary to tackle the outliers before Machine Learning modeling. Before handling, we must detect and locate the outliers in the dataset. The most popular outliers detection techniques are QQPlot, Inter-Quartile range, and Grubbs statistical test. However, this article will discuss only the Grubbs test to detect the outliers. You will learn: what ... Read More

Statisticians use F-test to check whether the two datasets have the same variance or not. F-test is named after Sir Ronald Fisher. To use the F-Test, we make two hypotheses, a null hypothesis, and one alternate hypothesis. Then we select any of these two hypotheses approved by the F-Test. Variance is a data distribution metric to tell the data deviation from the mean. The higher values show more dispersion than the smaller values. In this article, you will learn how to perform an F-Test in Python programming Language with its use cases. F -Test Process The process to perform the ... Read More

Introduction Data Scientists often use statistical methods for hypothesis testing to gain insights from the datasets. While there are multiple statistical methods available, this article will discuss the Chi-Square Goodness of fit test with its implementation in Python. The Chi-Square test validates the observed distribution of categorical variables to the expected distribution. It tells us if the available event values differ from the expected values. Chi-Square Test You can perform the Chi-Square test to verify the dataset distribution for observed events. The Chi-Square test makes some assumptions which are as follows − Variables are independent. Only one categorical feature ... Read More

The Brown-Forsythe test is a statistical test used to determine whether the variances of two or more groups are equal. While Levene's test uses the absolute deviations from the mean, the Brown-Forsythe test uses the deviations from the median. The null hypothesis used in the test is as follows − H0: The variance of the groups (populations) is equal The alternative hypothesis is that the variances are not equal − H1: The variance of the groups (populations) is not equal To perform the test, we calculate each group's median and the absolute deviations from the median. Then we calculate the ... Read More

Introduction to Ansible Tower Ansible Tower is a robust automation tool that assists IT teams in managing complicated installations, orchestrating applications, and streamlining operational procedures. Ansible Tower provides enterprises with a consolidated view of their automation environment and allows them to effortlessly manage automation workflows across their entire infrastructure. Ansible Tower's user-friendly web-based interface allows users to swiftly write and deploy automation playbooks, monitor task status, and follow system activities. This makes it simple for teams to cooperate on automated tasks and guarantees that everyone follows the same script. Ansible Tower also provides robust role-based access control (RBAC) capabilities, ... Read More

Python and Gator AI are two distinct technologies with different characteristics, purposes, and use cases. Python is a high-level, interpreted programming language used for a wide range of applications, while Gator AI is a natural language processing (NLP) technology used for language understanding and automation. What is Python AI? Python is an open-source, high-level programming language that is easy to learn and use. It has a simple and intuitive syntax, making it a popular choice for beginners and experts alike. Python is widely used in various fields, including web development, data analysis, machine learning, and artificial intelligence. It provides a ... Read More

What are the requirements of XML Documents? XML documents are used extensively in the process of data communication between various computer systems. Python comes with a number of built-in libraries that may be used for the processing and manipulation of XML files. In this piece, we will investigate the use of Python in the process of generating XML documents. First, we will look at a simple illustration, and then we will go to more complex illustrations. Prerequisites Python 3.0 An understanding of XML syntax Steps and processes Step 1: Creating a basic XML document To create an XML ... Read More