More people invest their money in the stock market. However, this kind of investment possesses a lot of risks. Therefore, many works have been done to build a model using Machine Learning algorithm to ...

Predictive Modeling: Developed and fine-tuned predictive models using Linear Regression, Ridge Regression, ElasticNet, XGBoost, Decision Trees, and Long Short-Term Memory (LSTM) networks. Achieved ...

Learn about how predictive analytics works, the types, benefits, use cases, and top tools. Predictive analytics is a process that uses statistics and modeling techniques to make informed decisions ...

Investment firms, hedge funds and even individuals have been using financial models to better understand market behavior and make profitable investments and trades. A wealth of information is ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

Machine learning is reshaping the landscape of finance, empowering professionals to make data-driven decisions, enhance predictive analytics, and manage risks more effectively.

Types of Machine Learning: Supervised Learning: Involves training a model on labeled data. Regression: Predicting continuous numerical values (e.g., housing prices, stock prices). Classification: ...

Abstract: In the current era stock price prediction plays a key role for prediction of future data with respect to training the past data by using machine learning or deep learning technologies.