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2. Automated decision-making - Wikipedia

   en.wikipedia.org/wiki/Automated_decision-making

   Automated decision-making involves using data as input to be analyzed within a process, model, or algorithm or for learning and generating new models. [7] ADM systems may use and connect a wide range of data types and sources depending on the goals and contexts of the system, for example, sensor data for self-driving cars and robotics, identity data for security systems, demographic and ...

3. Data analysis - Wikipedia

   en.wikipedia.org/wiki/Data_analysis

   Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

4. Predictive analytics - Wikipedia

   en.wikipedia.org/wiki/Predictive_analytics

   Predictive model solutions can be considered a type of data mining technology. The models can analyze both historical and current data and generate a model in order to predict potential future outcomes. [14] Regardless of the methodology used, in general, the process of creating predictive models involves the same steps.

5. Applications of artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Applications_of_artificial...

   Many AI platforms use Wikipedia data, [273] mainly for training machine learning applications. There is research and development of various artificial intelligence applications for Wikipedia such as for identifying outdated sentences, [ 274 ] detecting covert vandalism [ 275 ] or recommending articles and tasks to new editors.

6. Deep learning - Wikipedia

   en.wikipedia.org/wiki/Deep_learning

   Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.

7. Artificial intelligence engineering - Wikipedia

   en.wikipedia.org/wiki/Artificial_intelligence...

   Additionally, securing the data used to train AI models is of paramount importance. Encryption, secure data storage, and access control mechanisms are employed to safeguard sensitive information from unauthorized access and breaches. AI systems also require constant monitoring to detect and mitigate vulnerabilities that may arise post-deployment.