Evaluating the performance of machine learning models is crucial, especially for classification tasks, where a model predicts one of several classes. While metrics like accuracy give an overview, they don’t provide a complete picture, especially when the data is imbalanced. This is where the confusion matrix plays a significant role. A confusion matrix is a ...
Big data refers to the vast amount of structured and unstructured data generated from sources like social media, IoT devices, and digital transactions. It plays a crucial role in today’s digital world, helping organizations analyze trends, forecast outcomes, and make informed decisions. Big data enables industries to personalize services, optimize operations, and drive innovation. Sectors ...
Artificial Intelligence (AI) refers to the development of machines and software systems capable of performing tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. In the business context, AI helps companies automate processes, analyze large datasets, and improve customer interactions. AI’s growing importance in business stems from its ability to boost efficiency, ...
Machine learning is a branch of artificial intelligence that enables computers to learn from data and make predictions or decisions without being explicitly programmed. As machine learning grows in importance across various industries, understanding the process involved in developing effective models becomes essential. This structured process is known as the Machine Learning Life Cycle. It ...
The data analytics landscape has undergone a rapid transformation, becoming a crucial part of decision-making in almost every industry. From finance to healthcare and retail, businesses are now relying heavily on data analytics to gain insights, optimize processes, and drive growth. As demand for data-driven decision-making increases, the need for skilled data analysts continues to ...
Artificial Intelligence (AI) has become an essential part of modern technology, transforming how industries operate and how individuals interact with digital systems. AI can be classified into three main types: Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI). Among these, Artificial Narrow Intelligence, often referred to as “Weak AI,” is the ...
Machine learning (ML) is a field that focuses on developing systems capable of learning from data to identify patterns and make decisions. Within ML, a key task is concept learning, which involves finding a hypothesis that best describes a given set of training examples. This process helps machines understand and generalize from data, enabling them ...
Data analytics is a rapidly growing field, and interviews often cover a wide range of topics, from basic concepts to advanced techniques. Whether you’re new to the field or aiming to level up, this article will guide you through 80+ interview questions, covering beginner, intermediate, and advanced levels. These questions will help you build a ...
Artificial Intelligence (AI) and human intelligence are distinct forms of intelligence, each with unique capabilities and limitations. AI refers to the ability of machines to perform tasks that typically require human intelligence, such as recognizing speech, making decisions, or solving problems. It relies on algorithms and large datasets to learn patterns and execute specific tasks ...
Gradient Descent is one of the most important optimization algorithms in the field of machine learning. Optimization algorithms are used to minimize or maximize a function, which is crucial for training models effectively. Gradient Descent helps find the best parameters (weights and biases) for a model by reducing the error in predictions step by step. ...
Team Applied AI
Anshuman Singh
