Google Colaboratory : Tool for Deep Learning and Machine Learning Applications
Deep Learning, Google Colab, MobileNetV2, Transfer Learning, XlM-Roberta.
Manuscript Received : May 27, 2021 ; Revised : June 28, 2021 ; Accepted : July 12, 2021. Date of Publication : August 5, 2021.
- Y. Bengio, G. Hinton, and Y. LeCun, “Deep learning,” Nature, vol. 521, no. 7553, p. 436, 2015.
- A. R. Brodtkorb, C. Dyken, T. R. Hagen, J. M. Hjelmervik, and O. O. Storaasli, “State-of-the-art in heterogeneous computing,” Scientific Programming, vol. 18, no. 1, pp. 1–33, 2010. https://doi.org/10.3233/SPR-2009-0296
- NVIDIA Corporation, “Tesla V100 performance guide: Deep learning and HPC applications,” NVIDIA Corporation Whitepaper, 2016.
- M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. H. Katz, A. Konwinski, G. Lee, D. A. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, “Above the clouds: A Berkeley view of cloud computing,” Technical Report No. UCB/EECS-2009-28, EECS Department, University of California, Berkeley, Technical Report 2009. [Online]. Available: https://www2.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.html
- NVIDIA Corporation, “Introduction to NVIDIA GPU cloud,” NVIDIA Corporation Application Note, 2018.
- Google, “Colaboratory : Frequently asked questions,” 2018. [Online]. Available: https://research.google.com/colaboratory/faq.html. Accessed on June 21, 2018.
- G. Juve, E. Deelman, K. Vahi, G. Mehta, B. Berriman, B. P. Berman, and P. Maechling, “Scientific workflow applications on Amazon Ec2,” in 2009 5th IEEE Int. Conf. on E-Science Workshops. IEEE, pp. 59–66, 2009.
- K. R. Jackson, L. Ramakrishnan, K. Muriki, S. Canon, S. Cholia, J. Shalf, H. J. Wasserman, and N. J. Wright, “Performance analysis of high-performance computing applications on the Amazon Web Services cloud,” in 2010 IEEE Second Int.Conf. on Cloud Computing Tech.and Sci. IEEE, 2010, pp. 159–168. Doi: https://doi.org/10.1109/CloudCom.2010.69
- R. R. Expósito, G. L. Taboada, S. Ramos, J. Touriño, and R. Doallo, “Performance analysis of HPC applications in the cloud,” Future Generation Comp. Syst., vol. 29, no. 1, pp. 218–229, 2013. Doi: https://doi.org/10.1016/j.future.2012.06.009
- N. Sharma, V. Jain, V., and A. Mishra, “An analysis of Convolutional Neural Networks for image classification,” Procedia Comp. Sci., vol. 132, pp. 377–384,2018. Doi: https://doi.org/10.1016/j.procs.2018.05.198
- M. Shaha, and M. Pawar, “Transfer learning for image classification,” In 2018 Second Int. Conf. on Electronics, Communication, and Aerospace Tech. (ICECA), IEEE, 2018, pp. 656–660. Doi: https://doi.org/10.1109/ICECA.2018.8474802
- P. Gujjar J. and P. Kumar H. R., “Sentiment analysis for running text in Email conversation,” Int. J. of Comp. Sci. Eng., vol. 9, no. 4, pp. 259–263, 2020. [Online]. Available: http://www.ijcse.net/docs/IJCSE20-09-04-007.pdf
- T. Manjunatha and P. Gujjar J., “Performance analysis of Indian information technology companies using DuPont Model,” IUP J. of Manage. Res., vol. 17, no. 4, pp. 7-14, 2018. [Online]. Available: https://www.proquest.com/openview/dd55d1644ea7a53a495edee2d4395fc8/1?pq-origsite=gscholar&cbl=54462
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