Data Science Sitemap
John Spacey, updated on
Data science is the practice of discovering knowledge and information in data where knowledge has meaning to humans and information has meaning to machine processes. It is traditionally seen as an interdisciplinary field that includes areas such as statistics, algorithms, distributed computing, databases and machine learning. Data science also requires considerable domain expertise to understand the nature of data in an area such as marketing, financial markets or science. The following are common data science techniques and considerations.
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An overview of data with a list of examples. The basic types of data.
The definition of dark data with examples.
The mysteries of data massage.
Several useful definitions of data.A definition of analytics with examples.
The difference between data and information.
The difference between hard data and soft data.
A definition of human readable.
The common types of data loss.A few common types of artificial intelligence.
Technological singularity explained.Artificial intelligence and emotion.
An overview of artificial life.
How artificial intelligence can be illogical.
A definition of deep learning with examples.
The difference between supervised and unsupervised learning with an example.The common types of natural language processing.
Common types of autonomous systems.
Common examples of artificial intelligence.
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