deep-learning-and-machine-learning

Big Data has five characteristics:

• velocity
• volume
• variety
• veracity
• value.

The five cloud computing characteristics

• on-demand self-service
• broad network access
• resource pooling
• rapid elasticity
• measured service.

Data mining has a six-step process:

• goal setting
• selecting data sources
• preprocessing
• transforming
• mining
• evaluation. 

[[Deep Learning]] utilizes neural networks to teach itself patterns in inputs and outputs.

[[Machine Learning]] is a subset of AI that uses computer algorithms to learn about data and make predictions without explicitly programming the analysis methods into the system.

[[Regression]] identifies the strength and amount of the correlation between one or more inputs and an output.

Skills involved in processing Big Data include the application of [[General/Notion/Math/Statistics]], [[Machine Learning]] models, and some computer programming.

[[Generative AI]], a subset of [[artificial intelligence]], focuses on producing new data rather than just analyzing existing data.

It allows machines to create content, including images, music, language, computer code, and more, mimicking creations by people.