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Computational Techniques
Computational techniques refer to the methods and algorithms used to solve problems in the field of data science and artificial intelligence. These techniques involve the use of mathematical models, statistical analysis, and computer programming to process and analyze large datasets. Computational techniques are used to develop predictive models, identify patterns and trends in data, and make data-driven decisions. They are also used to optimize algorithms and improve the performance of machine learning models. Some common computational techniques used in data science and artificial intelligence include regression analysis, clustering, classification, and neural networks.
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- RNA-Seq: RNA-Seq is a high-throughput sequencing technique that allows researchers to quantify gene expression levels by sequencing the RNA molecules in a sample. The technique involves converting RNA molecules into cDNA, which is then sequenced usi ... Read More >>
- Energy-Dispersive X-ray Spectroscopy: Energy-Dispersive X-ray Spectroscopy (EDS) is an analytical technique used in materials science and engineering to identify the elemental composition of a sample. EDS works by detecting the characteristic X-rays emitted by a sample when it ... Read More >>
- Hardware: Hardware refers to the physical components of a computer system, including the central processing unit (CPU), memory, storage devices, input/output devices, and other peripheral devices. In the context of data science and artificial intelli ... Read More >>
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