"Computationn" Example Sentences
1. Computation is made easier with the use of modern technology.
2. I have always been fascinated by the intricacies of computation.
3. The speed of computation is critical in data analysis.
4. Programming languages are essential for computation.
5. Predictive analysis is based on complex computation.
6. Computation is an important tool in scientific research.
7. Improper computation can lead to inaccurate data.
8. Computation can be used to solve complex mathematical problems.
9. Artificial intelligence heavily relies on computation.
10. The accuracy of financial forecasting is reliant on proper computation.
11. The exponential growth of technology has revolutionized computation.
12. Machine learning algorithms depend on fast computation.
13. The government uses advanced computation to process massive datasets.
14. Computation is crucial in understanding climate change trends.
15. Software development requires a deep understanding of computation.
16. Quantum computation is a cutting-edge field of physics.
17. The human brain utilizes intricate neural computation.
18. Computation plays a vital role in medical research.
19. Computation is important in predicting natural disasters.
20. Statistical analysis is heavily reliant on computation.
21. Accurate data analysis depends on proper computation.
22. Cloud computing has improved the speed of computation.
23. The accuracy of weather forecasting relies on fast computation.
24. Proper computation is essential in the development of new technologies.
25. Computational linguistics is a fascinating and rapidly growing field.
26. Computation-based solutions can help solve complex social problems.
27. Gaming technology has revolutionized the field of computation.
28. Computation has been a driving force behind the growth of e-commerce.
29. Advanced computation can help predict the spread of infectious diseases.
30. Computation is the backbone of modern data-driven business.
Common Phases
1. Running a computation;
2. Analyzing computational data;
3. Developing computational models;
4. Optimizing computational algorithms;
5. Implementing computational methods;
6. Simulating complex computational systems;
7. Validating computational results;
8. Integrating computational tools;
9. Visualizing computational outputs;
10. Parallelizing computations.