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An open-source machine learning framework developed by the Google Brain team. TensorFlow is widely used for building and training deep learning models.
An open-source machine learning library developed by Facebook. PyTorch is known for its dynamic computational graph, making it a popular choice for researchers and developers.
An open-source distributed computing system used for big data processing and analytics. Spark is known for its speed and ease of use in processing large-scale data.
A distributed event streaming platform that is widely used for building real-time data pipelines and streaming applications.
A unified analytics platform that simplifies the management and analysis of large-scale data using Apache Spark.
An open-source web application that allows for the creation and sharing of documents containing live code, equations, visualizations, and narrative text.
A comprehensive cloud computing platform providing a wide range of services, including data storage, computation, and machine learning.
A cloud-based service for building, training, and deploying machine learning models using Microsoft Azure.
(MongoDB, Express.js, AngularJS, Node.js): A full-stack JavaScript framework for building dynamic web applications. MongoDB is used for data storage, Express.js for web application framework, AngularJS for front-end, and Node.js for server-side scripting.
Elasticsearch, Logstash, Kibana: A set of tools for searching, analyzing, and visualizing log data in real-time. Elasticsearch is used for indexing and searching, Logstash for log data processing, and Kibana for visualization.
Widely used in data science and machine learning for its simplicity, readability, and a vast ecosystem of libraries such as NumPy, Pandas, and scikit-learn.
A programming language and environment designed for statistical computing and graphics, commonly used in data analysis and visualization.
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