Machine learning (ML) is a branch of artificial intelligence that enables computers to learn from data and make decisions without explicit programming. There are different types of machine learning, mainly classified as supervised learning, unsupervised learning, and reinforcement learning. Unsupervised learning is a type of machine learning where the model works with unlabeled data. Unlike ...
In machine learning, understanding and managing uncertainty is essential. When building models, we often face questions about how well a model will perform on new data or how accurate the estimates are. Bootstrapping in machine learning is a statistical resampling technique that helps address these uncertainties by generating multiple samples from the original dataset and ...
In machine learning, a model is trained to make predictions or classify data based on patterns in a dataset. However, a single model can sometimes have limitations, such as overfitting, where the model performs well on training data but poorly on new data. Ensemble methods offer a solution by combining multiple models to improve accuracy ...
Machine learning is a branch of artificial intelligence that enables computers to learn from data and make informed decisions without explicit programming. With applications in fields like healthcare, finance, and retail, machine learning is transforming how industries solve complex problems and make predictions. To make this process easier, machine learning tools have become essential. These ...
What is Supervised Learning? Supervised learning is a type of machine learning where a model is trained using labeled data. In labeled data, each input is paired with a known output, allowing the model to learn patterns and relationships between them. This structured approach enables the model to make accurate predictions for new, unseen data. ...
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 ...
Machine learning (ML) has become an essential part of our lives, powering everything from recommendation systems on Netflix to image recognition in self-driving cars. At its core, machine learning is about enabling computers to learn from data, recognize patterns, and make decisions with minimal human intervention. There are several types of machine learning, each with ...
Machine Learning (ML) is a rapidly advancing field within artificial intelligence that empowers systems to learn from data and improve over time without explicit programming. With applications across sectors like healthcare, finance, and retail, ML is revolutionizing how we analyze data, make decisions, and automate processes. What is Machine Learning? Machine Learning (ML) is a ...
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, a branch of Artificial Intelligence, enables systems to learn from data and make decisions without explicit programming. One of the foundational models in Machine Learning is the Artificial Neural Network (ANN), inspired by the structure of the human brain. A basic type of ANN is the Perceptron, which has a single layer and ...
Mayank Gupta
Team Applied AI
Abhimanyu Saxena