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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- CNN: CNN (Convolutional Neural Network) is a type of deep learning algorithm that is commonly used for image and video recognition tasks. It is inspired by the structure of the human visual system and is designed to automatically and adaptively ... Read More >>
- Deduplication: Deduplication is the process of identifying and removing duplicate records from a dataset. In data science, deduplication is an important step in data preprocessing, as it helps to ensure data quality and accuracy. Deduplication can be perf ... Read More >>
- Transformations: Transformations refer to the process of converting raw data into a more useful format for analysis. This involves cleaning, aggregating, and manipulating data to create new variables or features that can be used to build models or gain insi ... Read More >>
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