ARCHIVE December2023
Artificial Intelligence Hardware Requirements
Artificial intelligence enables pervasive computing and becoming an omnipresent feature of everyday life.From datacenters to smartphones and personal assistants, there is a compelling need to develop bespoke hardware that is energy-efficient and […]
Adaptive Boosting Algorithm Explained
Adaptive Boosting or AdaBoost is one of the earliest implementations of the boosting algorithm. It forms the base of other boosting algorithms, like gradient boosting and XGBoost. In this post, we are […]
Data Analytics Meaning
Data is powerful, and organizations around the world understand the value that data analytics hold when it comes to driving organizational growth and profitability. Whether you’re a recent graduate or looking to […]
Data Splitting in Machine Learning
Dataset splitting is highly necessary to eliminate or reduce bias to training data in Machine Learning Models. This process is always done to prevent the machine learning algorithms from resulted into an […]
Confusion Matrix
When a Machine Learning model is built, various evaluation metrics are used to check the quality or the performance of a model. For classification models, metrics such as Accuracy, Confusion Matrix, Classification […]
Data Science Meaning
Data science is an interdisciplinary academic field that uses statistics, scientific computing, processes, algorithms to extrapolate knowledge and insights from potentially structured or unstructured data. Also Data science continues to evolve as […]
Machine Learning Engineer
Machine learning is a fascinating branch of artificial intelligence that involves predicting and adapting outcomes as data is received. The demand for machine learning professionals has also grown exponentially in recent years. […]
Ensemble Learning in Machine Learning
Machine learning predictions follow following behavior. Models process given inputs and produce an output. The output is a prediction based on what pattern the models see during the training process. But in […]
Hybrid Machine Learning
Machine learning (ML) is a technique that allows complex systems with vast data to be learned, analyzed, and predicted. . Machine learning (ML) uses algorithms and statistical models to identify patterns, mine […]
Batch Machine Learning
In machine learning, batch learning also known as offline learning is a technique where the model is trained on the entire dataset available in certain time. Batch learning is suitable for scenarios […]
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