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Introduction Time series is one of the widely used in machine learning and data science, used to forecast and analyze the data collected with time components. It is a field of intelligence where the data can be forecasted and analyzed with the help of past data collected. In industry, businesses are using the time series analyzed and related methods to improvise their decision-making process. In this article, we will discuss the ways in which the time series can help improve the decision-making process in the industry and how businesses are using the same to enhance their productivity and ... Read More
Introduction In deep learning, computer vision is one of the most important fields which is used for many complex and advanced tasks related to image datasets. It is used for image analysis, object detection, segmentations, etc. This is mainly achieved with the combination of TensorFlow and Keras, which offers several inbuilt functions which automate and make the process of model training very easy. The Conv2D is also one of the most useful and powerful functions in the Keras library, which is used for applying convolutional operations to the image. In this article, we will discuss the Conv2D function ... Read More
Introduction Padding is one of the most used concepts in neural networks while working with convolutional neural networks. It is a most known concept to every neural network engineer and deep learning engineer to efficiently extract useful information from the given dataset in deep learning. In this article, we will discuss padding, what it is, why we need padding in neural networks, what is the significance of the same, and how we can apply padding in neural networks with code examples. This article will help one to understand padding from scratch and apply it when necessary. What is ... Read More
Introduction In machine learning, classification problems are one of the most widely seen problems, where machine learning models are built to classify several categories of the target variables. However, the classification report and confusion matrics are used in order to evaluate the performance of the model and to check where the model is making mistakes. In this article, we will discuss the classification report and confusion matrics, what they are, how we can use them, and what their interpretation is by calculating the same code examples in Python. This article will help one to clear an idea about ... Read More
Introduction Data Science and machine learning are the trending fields in current business scenarios, where almost all kinds of product and service-based companies are leveraging Machine learning and data science techniques to enhance their productivity and advance their workflows. In such cases, many data aspirants are trying to enter the field, but the issue here is with the role. As one single individual can not master all the fields in AI and hence the need for selection of roles comes, which becomes very confusing but important for the career. In this article, we will discuss the machine ... Read More
TestNG allows to run the test suites from IntelliJ IDE as well as command line. Usually, IntelliJ IDE is handy to run testng.xml for development purpose while command line (cmd) for actual execution. There are few pre−requisites to run test suites from IntelliJ IDE: testng.xml file should be created to define test suites and testing classes to execute. All dependent jars should be configured as External Libraries. It includes testing.jar, jcommander.jar and any other jars those are used in test cases. It usually gets done while setting up the project first time. JDK set up at project level, ... Read More
TestNG supports native dependency injection. It allows to declare additional parameters in methods. At the run time, TestNG automatically fill these parameters with right value. Following are few native dependencies in TestNG: ITestContext XmlTest Method ITestResult These dependencies help to retrieve the test execution status. Usually, @AfterMethod supports all these native dependencies and test status could be either Success, failure or Skip. However, TestNG supports following test status those can be retrieved by calling the function at right place. ... Read More
Introduction Most companies and businesses are leveraging and integrating data science and machine learning techniques into their workflow to enhance their sales, marketing, and productivity of the projects and workings on the same. The viral fever, or the TVF, is one of the biggest content creation companies which creates movies, web series, and serials, which is India based company. The TVF uses data science and machine learning techniques to enhance its productivity and user experience. In this article, we will discuss how TVF makes a profit using data science and machine learning, which techniques they might be using, ... Read More
Introduction Data analysis is an approach in the field of data science and machine learning where the dataset is analyzed well in order to get the relationship between dataset features and get an idea about the behavior of the data and its parameters. In data analysis, trial and error play a major role while developing a machine learning model. It has certain advantages that allow data analysts or data scientists to make the model more reliable and predictive according to the dataset available. In this article, we will discuss the role of trial and error in data analysis, ... Read More
Introduction In machine learning, the performance and accuracy of the model completely depend n the data that we are feeding to it, and hence it is the most influential parameter in model training and model building. Mainly while dealing with the supervised machine learning problems, we have mostly categorical and continuous variables in the dataset. There are some benefits of converting categorical variables into continuous variables. In this article, we will discuss some of the benefits of converting categorical variables to continuous variables, how it affects the model's performance, and what is the core idea behind doing so. ... Read More