Author(s)

Tianyue Jiang ¹, Lihong Zhang ¹

Affiliation(s)

¹ Central University of Finance and Economics, Beijing, China

Corresponding Author

ABSTRACT

In recent decades, making machines learn from a massive dataset has become a prevalent task. It is significant to build a suitable deep learning model which would make its own decisions after training. This project aims to deal with a massive dataset with the trained deep learning model. More specifically, this project applies a Convolutional Neural Network (CNN) model to classify massive text data. It applies Generative Adversarial Network (GAN) model to regress image data. Furthermore, we start by building the model and enhance the model with necessary modifications for satisfying performance. Then we train and test the model to verify that the model achieves its aim. While the whole process implements based on Python and the Tensor Flow environment.

KEYWORDS

CITE THIS PAPER

Tianyue Jiang, Lihong Zhang, Machine learning: Training model with the case study. Journal of Artificial Intelligence Practice (2023) Vol. 6: 48-56. DOI: http://dx.doi.org/10.23977/jaip.2023.060808.

REFERENCES

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