Automation
Automation refers to the use of technology to perform tasks without human intervention. In the context of data science and artificial intelligence, automation involves the use of algorithms and machine learning models to automate data processing, analysis, and decision-making. This can include tasks such as data cleaning, feature engineering, model selection, and hyperparameter tuning. Automation can help to improve the efficiency and accuracy of data-driven processes, as well as reduce the time and resources required to perform these tasks manually. It can also enable organizations to scale their data science and AI capabilities, by allowing them to process and analyze larger volumes of data more quickly and effectively.
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- Stream Processing: Stream processing is a data processing technique that involves continuous processing of data in motion, also known as data streams. It involves real-time processing of data as it is generated, with the ability to handle high volumes of data ... Read More >>
- Python Libraries: Python libraries are collections of pre-written code that allow programmers to perform complex tasks without having to write the code from scratch. These libraries are designed to be reusable and can be easily integrated into a Python proje ... Read More >>
- Asynchronous: Asynchronous refers to a method of processing data where tasks are executed independently of each other, without waiting for the completion of the previous task. In other words, asynchronous processing allows multiple tasks to be executed s ... Read More >>
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