Having a high quality software is essential in software engineering, which requires robust validation and verification processes during testing activities. Manual testing, while effective, can be time consuming and costly, leading to an increased demand for automated methods. Recent advancements in Large Language Models (LLMs) have significantly influenced software engineering, particularly in areas like requirements analysis, test automation, and debugging. This paper explores an agent-oriented approach to automated software testing, using LLMs to reduce human intervention and enhance testing efficiency. The proposed framework integrates LLMs to generate unit tests, visualize call graphs, and automate test execution and reporting. Evaluations across multiple applications in Python and Java demonstrate the system's high test coverage and efficient operation. This research underscores the potential of LLM-powered agents to streamline software testing workflows while addressing challenges in scalability and accuracy.

Topics include Machine Learning, Deep Learning, GUI, Computer Vision, and API development. Author is a Machine Learning Researcher, currently working in IBM. Taught 20,000 students & working professionals to crack coding interviews and land their dream job.

This will help you get started with audio data and understand how to work with unstructured data. Large scale scene understanding (LSUN) is a dataset of millions of colored images of scenes and objects. It is much bigger than imagenet dataset. There are around 59 million images, 10 different scenes categories, and 20 different object categories.

Python is one of the most popular programming languages in the world--consistently ranking at the top of the TIOBE programming community index. Its popularity is no surprise: Python is easy to learn, elegant, and powerful. It offers many possibilities and is used in popular technologies like the Raspberry Pi and computer games like Minecraft. In addition, Python is the ideal introduction to the field of artificial intelligence and machine learning. This comprehensive Python compendium familiarizes you with basic and advanced techniques so that you have a good foundation for your professional Python projects.

Datasets are essential for machine learning Python project's success A number of cutting-edge technologies are being explored by students and future professionals. These machine-learning Python projects are a great way to get hands-on experience in machine training and the popular programming language Python. Sometimes they need to have several datasets for their projects. These project databases can be found online without making students feel overwhelmed. Let's take a look at the top ten datasets for machine-learning Python projects in order to gain more in-depth knowledge.

Looking to build a career in Python? Want to improve your resume with multiple personal projects on it? Then this blog of Python projects with source code is for you. You earlier read about the top 5 data science projects; now, we bring you 12 projects implementing data science with Python. In this blog, you'll find the entire code to all the projects.

Python is the hottest and trendiest programming language in the community of developers and programmers. Meanwhile, GitHub offers an open-source community with Git repositories to more than 73 million developers. Python projects are in high demand to increase the knowledge of the programming language efficiently and GitHub can provide help in that. Open source Python projects are crucial to learning to solve complex problems in the global tech market. Thus, there are innumerable GitHub projects that can help developers to work with open-source Python projects effectively.

If you've been a fan of Marvel Comics, you know Jarvis, who is a personal assistant of Iron Man. He knows everything and he can control everything related to computer tasks. In this tutorial, I am going to create a similar kind of program using the Python programming language.

Do you trust all the news you hear from social media? All news are not real, right? How will you detect fake news? By practicing this advanced python project of detecting fake news, you will easily make a difference between real and fake news. Before moving ahead in this machine learning project, get aware of the terms related to it like fake news, tfidfvectorizer, PassiveAggressive Classifier.

Time for another Python beginners list, this time we're talking about some awesome machine learning projects you can build with Python! If you're extremely new to machine learning, check out this article I wrote a few months back as a refresher guide to machine learning: