Machine Learning is a field of computer science where machines learn from data to make predictions or decisions without being explicitly programmed. One common type of machine learning is Supervised Learning, where models are trained on labeled data to make predictions. One popular technique within supervised learning is using ensemble methods. Ensemble methods combine multiple ...
Artificial Intelligence (AI) is transforming industries and reshaping how we interact with technology by enabling machines to perform tasks that typically require human intelligence. This includes functions like learning, problem-solving, and decision-making. As AI technology continues to evolve, understanding its various types becomes essential to grasp its capabilities and limitations. AI can be categorized into ...
Imagine you’re a real estate analyst tasked with predicting house prices based on factors like location, number of bedrooms, and house size. Accurately forecasting prices would require considering multiple variables simultaneously. Multiple Linear Regression (MLR) is a foundational tool in machine learning and statistics that allows us to do just that. It helps us understand ...
Machine learning involves building models that learn from data to make predictions or decisions. A hypothesis plays a crucial role in this process by serving as a candidate solution or function that maps input data to desired outputs. Essentially, a hypothesis is an assumption made by the learning algorithm about the relationship between features (input ...
Clustering is a fundamental task in machine learning, involving the grouping of similar data points. Density-based clustering methods, like DBSCAN (Density-Based Spatial Clustering of Applications with Noise), are highly effective for identifying clusters in noisy datasets. Unlike centroid-based methods, DBSCAN forms clusters based on data point density, making it suitable for datasets with arbitrary shapes. ...
Artificial Intelligence (AI) is transforming industries across the globe, and India is emerging as a hub for AI talent. The demand for AI engineers is on the rise, driven by rapid technological advancements and the adoption of AI across sectors like healthcare, finance, retail, and automotive. Understanding salary trends is essential for aspiring AI professionals ...
ETL (Extract, Transform, Load) plays a pivotal role in data-driven decision-making. It serves as the backbone of data integration, allowing businesses to consolidate and process data efficiently. By enabling smooth data flow from various sources to target systems, ETL ensures that organizations can leverage their data for meaningful insights and analytics. What is ETL? ETL ...
Artificial Intelligence (AI) continues to reshape industries, with the global AI market projected to reach $407 billion by 2027 (Fortune Business Insights). AI adoption has surged, with 37% of organizations now using AI-based tools (Gartner). From self-driving cars to personalized marketing, AI enables businesses to optimize processes and enhance user experiences. However, it also presents ...
In machine learning, many tasks involve working with sequential data, such as predicting stock prices, recognizing speech, or analyzing weather patterns. Sequential data means that the order of data points matters, which makes it harder to model compared to independent data points. A significant challenge in such tasks is that some underlying patterns (states) affecting ...
Data analytics has become a key part of modern business, helping companies make smart, data-driven decisions. Whether you are looking to switch careers or just starting your professional journey, understanding data analytics can open doors to exciting opportunities. Companies today need experts who can handle data, analyze it, and extract meaningful insights to improve operations ...
Team Applied AI
Abhimanyu Saxena
