Model selection and evaluation are essential components of machine learning. The goal of model selection is to find the best algorithm and hyperparameters that can

Feature engineering and selection are essential steps in the process of building predictive models with machine learning. Feature engineering involves transforming raw data into features

Distributed computing refers to the practice of using a network of computers to work together to solve a common problem. The computers in the network

Apache Spark is an open-source big data processing framework that is designed to handle large-scale data processing and analytics. It is written in Scala and

Machine learning algorithms are used to build models that can automatically learn from data and make predictions or decisions. These algorithms use statistical methods to

Pandas is a popular open-source data analysis library for Python. It provides a powerful set of tools for working with structured data, such as tabular

NumPy provides a powerful set of linear algebra functions that can be used for a variety of data analysis tasks. Here are some basic linear

Python is a high-level, interpreted programming language that is widely used for a variety of tasks, including web development, data analysis, artificial intelligence, and scientific