Overfitting and Underfitting in Machine Learning Gradient Descent in Machine Learning

Application of Neural Networks

Neural networks are broadly used, with applications for financial operations, enterprise planning, trading, business analytics, and product maintenance. Neural networks have also gained widespread adoption in business applications such as forecasting and marketing research solutions, fraud detection, and risk assessment.
A neural network evaluates price data and unearths opportunities for making trade decisions based on the data analysis. The networks can distinguish subtle nonlinear interdependencies and patterns other methods of technical analysis cannot. According to research, the accuracy of neural networks in making price predictions for stocks differs. Some models predict the correct stock prices 50 to 60% of the time, while others are accurate in 70% of all instances. Some have posited that a 10% improvement in efficiency is all an investor can ask for from a neural network.
List of references

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