PyTorch is a popular open−source machine learning framework that provides efficient tensor operations on both CPUs and GPUs. A tensor is a multi−dimensional array in PyTorch, and it is the fundamental data structure used for storing and manipulating data in PyTorch. In this context, a 3D tensor is a tensor with three dimensions, and it can be represented as a cube−like structure with rows, columns, and depth. To access elements in a 3D PyTorch tensor, you need to know its dimensions and the indices of the elements you want to access. The indices of a tensor are specified using square ... Read More

Unstructured data is data that does not follow any specific data model or format, and it can come in different forms such as text, images, audio, and video. Converting unstructured data to structured data is an important task in data analysis, as structured data is easier to analyse and extract insights from. Python provides various libraries and tools for converting unstructured data to structured data, making it more manageable and easier to analyse. In this article, we will explore how to convert unstructured biometric data into a structured format using Python, allowing for more meaningful analysis and interpretation of the ... Read More

Scikit−learn (sklearn) is one of the most popular machine learning libraries for Python. It provides a range of efficient tools for machine learning and statistical modelling, including a variety of datasets. These datasets are provided in the form of numpy arrays, which can be difficult to work with for certain tasks, such as exploratory data analysis. Pandas is a popular data manipulation library that provides powerful tools for data analysis and manipulation. It provides data structures for efficiently storing and manipulating large datasets, and provides a wide range of tools for data cleaning, transformation, and analysis. Below are the two ... Read More

Web scraping is the process of extracting data from websites. It involves parsing HTML or XML code and extracting relevant information from it. Scrapy is a popular Python−based web scraping framework that allows you to easily build web scrapers to extract structured data from websites. Scrapy provides a robust and efficient framework for building web crawlers that can extract data from websites and store it in various formats. One of the key features of Scrapy is its ability to parse and store data using custom Item classes. These Item classes define the structure of the data that will be extracted ... Read More

Extensible Markup Language (XML) is a popular data exchange format used in many applications. It provides a standardised way of representing data that can be easily understood by both humans and machines. In many cases, it is necessary to convert data stored in Python lists to XML format for various purposes, such as data exchange or storage. In this article, we will explore different approaches for converting Python lists to XML format using Python's built−in libraries. Below are the two different approaches that we can use to convert Python lists to XML in points. Using ElementTree library Import ... Read More

In order to make sure that the data is accurate, trustworthy, and appropriate for the intended analysis, cleaning the data is a crucial step in any data analysis or data science endeavour. The data cleaning functions in Pyspark, like dropna, make it a potent tool for working with big datasets. The dropna function in Pyspark allows you to remove rows from a DataFrame that contain missing or null values. Missing or null values can occur in a DataFrame for various reasons, such as incomplete data, data entry errors, or inconsistent data formats. Removing these rows can help ensure the quality ... Read More

Steady Flow Energy Equation (SFEE) is the application of conservation of energy on to an open system. Figure shown below is a schematic of open system in which fluid enters at 𝑖 and exits at 𝑒. The red broken line represents the control surface (CS) of the control volume (CV). The inlet and exit parameters are mentioned in the table shown below − Parameter Inlet Exit Pressure pi pe Velocity Vi Ve Density Pi Pe Specific volume vi ve Enthalpy hi he Area Ai Ae ... Read More

Simpson's rule is a very powerful tool to perform numerical integration. To maximise accuracy while requiring fewer divisions, Simpson's rules calculate the integrals using weighting factors. The trapezoidal rule only considers two points, 𝑥𝑖 and 𝑥𝑖+1, to estimate a trapezoid's area, but Simpson's rules use more than two points (or many strips) in each round (refer figure shown below). The values of 𝑓(𝑥) at the various points are updated by weighing various criteria in order to decrease the error Simpson’s 1/3 Rule This approach calculates the area of two strips simultaneously, so three different values of "x" are taken ... Read More

We know that Python is a programming language used for accomplishing various tasks in fields such as Data Analysis, AI, Machine Learning and so on. And obviously, there are different modules with special functions which help us to do the job. Similarly, Python code is made to interact with a PostgreSQL database using a module known as the “Psycopg2 module”. It is a popular PostgreSQL database adapter for Python. This module provides us with a set of functions and classes that help us with database connectivity, result handling as well as query execution. Key Features of ... Read More

As we know, Python is a language widely used for Data Science and Data Analytics. Alongside libraries such as NumPy and Pandas, Plotly is another such library to represent given data in charts and graphs of all sorts. Let’s learn more about this library! Why a whole library exists in Python just for the sake of Data Representation? Many might think of representing some data in a graph is simple, but that isn’t simple at all! For small amounts of data, it is a somewhat easy task to plot graphs manually. But when dealing with large amounts ... Read More