Fields
Fields refer to the different areas of study within Data Science and Artificial Intelligence that focus on specific topics or problems. These fields include but are not limited to machine learning, natural language processing, computer vision, data mining, and big data analytics. Machine learning involves the use of algorithms and statistical models to enable computer systems to learn from data and improve their performance on a specific task. Natural language processing focuses on the interaction between computers and human language, enabling machines to understand, interpret, and generate human language. Computer vision involves the use of algorithms to enable machines to interpret and understand visual data from the world around them. Data mining involves the process of discovering patterns and insights from large datasets, while big data analytics involves the use of advanced analytics techniques to analyze and extract insights from large and complex datasets.
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- Parallel Computing: Parallel computing is a type of computation where multiple calculations or the execution of processes are carried out simultaneously. This is achieved by breaking down a large problem into smaller sub-problems that can be solved concurrentl ... Read More >>
- Hash Function: A hash function is a mathematical function that takes in an input (or 'key') and returns a fixed-size string of characters, which is typically a unique representation of the input. In data science and artificial intelligence, hash functions ... Read More >>
- Collision-Resistant: Collision resistance is a property of cryptographic hash functions that ensures that it is computationally infeasible to find two inputs that hash to the same output. In other words, it is difficult to find two different messages that produ ... Read More >>
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