Understanding data is the cornerstone of any successful analysis or decision-making process. Before applying advanced algorithms or models, data exploration provides the essential groundwork, offering insights into patterns, trends, and anomalies. This foundational step ensures data quality and prepares datasets for more complex analysis, significantly improving outcomes. Learn more about data exploration in data science. ...
In the world of machine learning, the ability to classify data into multiple categories is a critical task with widespread applications. This is known as multiclass classification, a method where a model predicts one label from three or more possible categories for each input. It goes beyond binary classification, enabling machines to handle more complex ...
Decision trees are one of the most popular and intuitive algorithms in machine learning, valued for their simplicity and interpretability. Among these, the ID3 (Iterative Dichotomiser 3) algorithm stands out as a foundational method that paved the way for more advanced decision tree algorithms. Developed by Ross Quinlan in 1986, the ID3 algorithm is used ...
Artificial Intelligence (AI) is transforming various industries, with medicine being one of its most impactful domains. By enabling precise diagnostics, personalized treatments, and streamlined operations, AI is revolutionizing medical practices. Its integration into healthcare promises better patient outcomes, increased efficiency, and significant advancements in disease management and prevention. What is Artificial Intelligence in Medicine? Artificial ...
Artificial Intelligence (AI) has evolved rapidly, becoming a cornerstone of innovation and progress in the modern era. Its transformative impact spans industries, revolutionizing how we work, communicate, and solve problems. Understanding AI’s growing significance is essential to navigating its influence on shaping contemporary life and the future. What is Artificial Intelligence? Artificial Intelligence (AI) refers ...
Artificial Intelligence (AI) stands as a transformative force, revolutionizing industries from healthcare to finance. Its ability to mimic human intelligence through advanced algorithms and computational power has unlocked unprecedented opportunities for innovation. Selecting the right research topic in AI is crucial for making impactful contributions to this dynamic field. With AI’s diversity spanning natural language ...
Artificial Intelligence (AI) has become an integral part of our daily lives, from personalized recommendations to autonomous vehicles. However, as AI systems grow more complex, their decision-making processes often become opaque, leading to what is called the “black-box problem.” This lack of transparency raises concerns about trust, fairness, and accountability. Explainable AI (XAI) aims to ...
Data science continues to thrive in 2025 as one of the most in-demand skills globally, driving innovation across industries. From healthcare to finance and e-commerce, data science applications are shaping decision-making processes and solving complex challenges. With the rise of machine learning and artificial intelligence, organizations are seeking skilled professionals who can work on real-world ...
Generative AI models represent a groundbreaking evolution in artificial intelligence, enabling machines to create new and unique content, such as text, images, music, and even code. Unlike traditional AI models that focus on prediction or classification, generative AI excels in mimicking human creativity by generating realistic and innovative outputs. These models, powered by architectures like ...
Adversarial search is a key concept in artificial intelligence (AI), especially in competitive scenarios where two or more agents interact, often with opposing goals. It is commonly used in game-playing AI, where the goal is to anticipate the opponent’s moves and respond strategically. For instance, in games like chess or tic-tac-toe, adversarial search enables AI ...
Mohit Uniyal
Mayank Gupta
Team Applied AI