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Telnet, a widely−used network protocol, empowers users to remotely control computers and devices through a command−line interface (CLI). With Telnet, it becomes possible to execute commands and retrieve information from a remote system effortlessly. In this article, we delve into Telnet with IP address and port in Python, focusing on how to establish connections with remote servers. By harnessing the power of Python's Telnet lib module, we can seamlessly interact with Telnet services. From setting up the environment to sending and receiving data, we explore the necessary steps for establishing a Telnet connection. Furthermore, we discuss handling timeouts and exceptions ... Read More
Transferring Linux binaries from one system to another can be a challenging and time-consuming task, especially when you need to install the software on multiple machines. However, there is a tool available that simplifies this process - Exodus. It is a powerful tool that allows you to export and import software packages, including binaries and their dependencies, from one Linux system to another. In this article, we will explore the steps involved in using Exodus to copy Linux binaries from one system to another. We'll cover essential steps such as identifying the location of binaries and dependencies, creating an archive ... Read More
In this tutorial, we will explore Collectl, a powerful performance analysis tool for Linux systems. Collectl provides comprehensive monitoring capabilities, allowing us to gather and analyze system performance metrics in real-time. Throughout this article, we will learn how to install Collectl and utilize its features to monitor various system resources, including CPU, memory, disk, and network usage. Installing Collectl To begin, let's install Collectl on our Linux system by following these steps − Step 1 − Open a terminal window on your linux machine. Step 2 − Update the package repository by running the following command − sudo apt update By executing the above command, ... Read More
Calculating the trace of a matrix using Numpy is a common operation in linear algebra that can be used to extract important information about the matrix. The trace of a matrix is defined as the sum of the elements on the matrix's main diagonal, which runs from the top left to the bottom right corner. In this article, we will learn various methods to calculate the trace of a matrix using the NumPy library in Python. Before we begin, let's first import the NumPy library − import numpy as np Next, let's define a matrix using the np.array ... Read More
In the era of data-driven decision-making, web scraping has become an indispensable skill for extracting valuable information from websites. However, as websites become more dynamic and sophisticated, traditional scraping techniques often fail to capture all the desired data. That's where advanced web scraping with Python comes into play. This article dives into the intricacies of handling JavaScript, cookies, and CAPTCHAs, which are common challenges web scrapers face. Through practical examples and techniques, we explore how Python libraries like Selenium, requests, and BeautifulSoup can be able to overcome these obstacles. By the end of this article, we will have a toolkit ... Read More
Python, a flexible programming language, offers developers extensive features and tools. Within its arsenal of powerful capabilities lies metaprogramming—an advanced technique that empowers developers to manipulate and generate code during runtime dynamically. In this article, we will embark on a journey into the realm of advanced Python metaprogramming, with a specific focus on dynamic code generation and reflection. By employing these techniques, developers can create code that adapts, modifies, and even introspects itself, unlocking a world of new possibilities for crafting flexible and efficient applications. By exploring the concepts and practical applications of dynamic code generation and reflection in Python, ... Read More
The field of machine learning has become very popular in the last few years with significant innovation and advancement in this field. There are lots of machine learning startups in the world that are trying to solve some real-world problems with the help of machine learning, these companies are using machine learning to automate complex processes, develop new products and services, and make better decisions with the help of machine learning. Here are the top 10 machine learning startups in 2023. 1. OpenAI OpenAI is the world’s leading machine learning and artificial intelligence startup which was founded in 2015 by several ... Read More
Machine learning is a subset of artificial intelligence in which machines learn from the data and make predictions or decisions on the new data without being explicitly programmed. Machine learning is an industry that is continuously evolving with several new innovations coming up every year. The market for artificial intelligence is expected to be worth $500 billion in 2023 and $1, 597.1 billion in 2030. This indicates that there will be a continued high demand for machine-learning technologies in the future. In this article, we will see the top 5 machine-learning trends for 2023. 1. Foundation Models Foundation models are large ... Read More
GPT-3 is a neural network machine learning model that is trained on text data to generate text output. It is developed by OpenAI which can perform a wide range of NLP (Natural Language Processing) tasks from simple text generation to complex language understanding and translation. Based on the user input it can produce a large amount of response in form of text, it can even generate code for users. In this article, we will discuss the overview of GPT-3 and its capabilities as well as its application and the future of AI. GPT Architecture GPT architecture is based on the ... Read More
Data science is a field that combines statistical analysis, machine learning, and computer science to extract insight and knowledge from the data. From identifying business problems to implementing predictive models, a data science lifecycle is a methodical strategy for managing data science projects. The complete method has a number of steps including data collection, data cleaning, data transformation, modeling, and model evaluation and deployment. It’s a very long process and some general steps have been defined for a data science project which is used in all data science projects. In this article, we will discuss the different stages of a ... Read More