• Ankit Katre
• Viraj Chogle
• Pratyusha Parashar

Data visualization is a quite new and promising field in computer science. It uses computer graphic effects to reveal the patterns, trends and relationships out of datasets. However, there is a dearth of visualization tools for deep learning algorithms along with the details buried in the algorithms that are properly accounted for. Gaining an understanding of this technology is somewhat difficult. While the theory is important, it is also helpful for novices and users not familiar with machine learning to develop an intuitive feel for the effect of different hyperparameters and structural variations. We propose a visualization tool for some of these algorithms along with the description of “intricate details” that often result in novices describing them as ‘black boxes’.

data visualization, deep learning, machine learning, hyperparameters.

"V-ML: VISUALIZATIONS FOR MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.1366-1368, April-2021, Available :http://www.jetir.org/papers/JETIR2104388.pdf

"V-ML: VISUALIZATIONS FOR MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp1366-1368, April-2021, Available at : http://www.jetir.org/papers/JETIR2104388.pdf