Improvement of Learning Ability and Prediction Accuracy of Intelligent Software Through Machine Learning and Deep Learning Algorithms

With the increasing demand for software, the learning ability and prediction accuracy of software can no longer meet people's needs, but there is currently no good solution. To address this issue, this study utilizes machine learning and deep learning algorithms to improve these issues. A literature review method is adopted to investigate and summarize the research on machine learning and deep learning algorithms in improving the learning ability and prediction accuracy of intelligent software. The learning ability of software is explored by collecting relevant literature, analyzing and comparing the characteristics and application scenarios of different algorithms, and a deep comparison is conducted on the prediction accuracy and learning ability of the software through experiments. The research results indicate that the prediction accuracy of the algorithm in this article is between 91% and 99%, and machine learning and deep learning algorithms have significant effects on improving the learning ability and prediction accuracy of intelligent software.