From face recognition to dynamic lock, there are options you may be unfamiliar with. Are you dealing with a Windows PC or laptop that won't stop crashing? Maybe your PC is constantly freezing or displaying error messages. We know how frustrating a PC that won't work right can be. Luckily, there are some easy ways to fix a Windows PC that is consistently crashing.

Recent advancements in Artificial Intelligence (AI), particularly the widespread adoption of Large Language Models (LLMs), have significantly enhanced text analysis capabilities. This technological evolution offers considerable promise for automating the review of scientific papers, a task traditionally managed through peer review by fellow researchers. Despite its critical role in maintaining research quality, the conventional peer-review process is often slow and subject to biases, potentially impeding the swift propagation of scientific knowledge. In this paper, we propose RelevAI-Reviewer, an automatic system that conceptualizes the task of survey paper review as a classification problem, aimed at assessing the relevance of a paper in relation to a specified prompt, analogous to a "call for papers". To address this, we introduce a novel dataset comprised of 25,164 instances. Each instance contains one prompt and four candidate papers, each varying in relevance to the prompt. The objective is to develop a machine learning (ML) model capable of determining the relevance of each paper and identifying the most pertinent one. We explore various baseline approaches, including traditional ML classifiers like Support Vector Machine (SVM) and advanced language models such as BERT. Preliminary findings indicate that the BERT-based end-to-end classifier surpasses other conventional ML methods in performance. We present this problem as a public challenge to foster engagement and interest in this area of research.

The correct method could make converting an MBR disk to a GPT disk easy and efficient. Pick and follow the suitable way with a simple guide to successfully convert your disk from MBR to GPT on Windows PC.

Machine Learning is very useful in detecting many diseases early on in the medical field. Diabetes prediction is one such Machine Learning model which helps to detect diabetes in humans. Also, we will see how to Deploy a Machine Learning model using Streamlit. The very first step is to choose the dataset for our model. We can get a lot of different datasets from Kaggle.

This article was published as a part of the Data Science Blogathon. AWS is a cloud computing service that provides on-demand computing resources for storage, networking, Machine learning, etc on a pay-as-you-go pricing model. AWS is a premier cloud computing platform around the globe, and most organization uses AWS for global networking and data storage. The article is for those Machine learning practitioners who know the model building and even they have deployed some projects on other platforms but want to learn how to deploy on major cloud platforms like AWS. In the article, our main aim is to learn deployment over AWS, but we will walk through each step from the development of the Machine learning model to deployment over AWS from scratch.

Extremely realistic-looking images can now be created almost instantaneously by artificially intelligent internet bots. Should photographers, illustrators and graphic designers be threatened by this new industry development? In recent years, AI and smart programs have been advancing, especially in the fields of art, design and photography. Even Google is developing a new advanced AI system (opens in new tab) that can create hyper-realistic images from just a basic text prompt. You might be familiar with an AI program called the Dall-E Mini (opens in new tab), which set the internet abuzz a few months back with the ability to create any image you ask it for, and the results are completely original, too.

Robot Framework is an open-source Test Automation framework. It was initially developed by Nokia Networks, however, it is now maintained by the Robot Framework Foundation. You will learn about the features, pros, and cons of the Framework along with instructions to install the needed software. Robot Framework is a Test Automation tool in which the test cases are written using keywords that makes it easy to learn and use. These keywords are written in a tabular form. With Robot Framework, the Test Scripts are replaced by a few keywords thereby replacing the need for large pieces of code.

I hope you read and enjoyed my previous blog titled'Introduction to Rasa X' since it is a precursor to this one. In case you haven't, you can read it here. In this blog, I am going to lead you through the installation, folder structure, controls, and features of Rasa as well as Rasa X to develop an assistant. Let's first dive into installing Rasa. To install Rasa, you require Python 3.7 or Python 3.8.

Working on a machine learning project means we need to experiment. Having a way to configure your script easily will help you move faster. In Python, we have a way to adapt the code from command line. In this tutorial, we are going to see how we can leverage the command line arguments to a Python script to help you work better in your machine learning project. There are many ways to run a Python script.

NER, short for, Named Entity Recognition is a standard Natural Language Processing problem which deals with information extraction. The primary objective is to locate and classify named entities in text into predefined categories such as the names of persons, organizations, locations, events, expressions of times, quantities, monetary values, percentages, etc. To put it simply, NER deals with extracting the real-world entity from the text such as a person, an organization, or an event. Named Entity Recognition is also simply known as entity identification, entity chunking, and entity extraction. They are quite similar to POS(part-of-speech) tags. NLTK is a standard python library with prebuilt functions and utilities for the ease of use and implementation.