Twitter Sentiment Analysis refers to the process of extracting and interpreting emotions, opinions, and attitudes from tweets. Given the platform’s fast-paced, text-driven nature, it offers a rich and immediate source of public sentiment across diverse topics. Businesses, political analysts, and researchers increasingly rely on Twitter sentiment analysis to gauge public opinion in real time. Twitter’s ...
In today’s rapidly evolving medical landscape, data has become a cornerstone of effective healthcare delivery. From patient records to clinical trials, hospitals and healthcare providers are generating vast volumes of data every day. Harnessing this data through healthcare analytics enables professionals to make informed decisions that improve patient outcomes, optimize operations, and control costs. Whether ...
The exponential growth of data in recent years has ushered in the era of big data, where organizations across industries generate and collect massive volumes of information daily. Traditional data processing methods struggle to manage such scale, speed, and complexity. Enter MapReduce—a powerful programming model that revolutionized how large datasets are processed across distributed systems. ...
Lasso Regression, short for Least Absolute Shrinkage and Selection Operator, is a linear regression technique that enhances prediction accuracy and model interpretability by performing both variable selection and regularization. Unlike traditional linear regression, which can overfit data when too many features are involved, Lasso adds a penalty to the regression equation to shrink some coefficients ...
Image classification is a key task in computer vision that involves assigning labels to images based on their content. It enables machines to automatically recognize and categorize objects, patterns, and scenes, making it an essential technology in healthcare, security, retail, and autonomous systems. Machine learning (ML) plays a crucial role in automating image classification, eliminating ...
Model selection in machine learning is the process of identifying the most suitable algorithm for a given dataset to achieve optimal accuracy, efficiency, and generalization. Since different models have unique strengths and weaknesses, selecting the right one is crucial for ensuring reliable predictions and scalable AI solutions. Choosing an appropriate model directly impacts performance metrics, ...
Artificial Intelligence (AI) is transforming the transportation industry, making mobility safer, smarter, and more efficient. AI-powered solutions are enhancing traffic management, predictive maintenance, autonomous driving, and logistics optimization, creating a more sustainable and connected transport ecosystem. One of the key roles of AI in transportation is improving efficiency by analyzing vast amounts of data from ...
Azure Machine Learning (Azure ML) is a cloud-based platform designed by Microsoft to simplify and accelerate the development, training, and deployment of machine learning models. It provides a robust ecosystem that enables data scientists, AI engineers, and businesses to build and manage machine learning workflows with ease. As part of the Microsoft Azure AI ecosystem, ...
Large Language Models (LLMs) have become essential in natural language processing (NLP) and AI applications, enabling more human-like text generation and comprehension. Evolving from basic rule-based models to advanced deep learning architectures, LLMs now drive automation, enhance AI communication, and expand capabilities in diverse industries, transforming how AI interacts with language. What is a Large ...
Artificial Intelligence (AI) is a rapidly evolving field, with applications spanning healthcare, finance, robotics, and entertainment. AI is broadly categorized into Strong AI and Weak AI, each with distinct capabilities and implications. Weak AI is designed to perform specific tasks efficiently but lacks human-like intelligence. Strong AI, on the other hand, represents a theoretical concept ...
Mohit Uniyal
Mayank Gupta
Team Applied AI