Stock Market is a bit volatile and to predict the future trend of the stock and predict a price of a stock in days to come would benefit the Investment Banking/Brokerage Firm to assist their end clients. Hence predicting the same using advanced Neural Network gives a huge advantage to the volatile Trading Market. In this course, Deep Learning Application for Finance, you’ll learn to understand the benefits deep learning offers to resolve problem statements in the Finance Industry such as Fraud, Stock Market Prediction or Portfolio Recommendations. First, you’ll explore the basic nuances of deep learning. Next, you’ll discover different types of neural net models that can resolve different types of case-studies. Finally, you’ll learn how to apply Stacked LSTM to predict the stock price of a company using Keras/Tensorflow. When you’re finished with this course, you’ll have the skills and knowledge of Deep Learning Application for Finance needed to resolve the problem statements connected to the Finance Industry.
Author Name: Niraj Joshi
Author Description:
Niraj is a AWS/Azure DevSecOps Cloud Specialist with over a decade of work experience into Data Modeling with Databases like Cassandra, MongoDB, SparkSQL, ElasticSearch and SQL Server. He has over 7 years of work ex into Computer Vision, Artificial Intelligence, DevOps, Machine Learning and Big Data Stack, he has been a consultant to companies like CISCO, ERICSSON, Dynamic Elements and JP Morgan He has excellent data visualization/ analytics skills and quite proficient in languages like Python ,… more