Machine Learning in Finance
Bob Mather
Are you a machine-learning enthusiast looking for a practical day-to-day application? Or are you just trying to incorporate machine-learning software in your trading decisions? This audiobook is your answer. While machine learning and finance have generally been seen as separate entities, this audiobook looks at several applications of machine learning in the financial world. Whether it is predicting the best time to buy a stock in a day-trading scenario or to determine the long-term value of a stock, financial ratios and common sense have always been used as reliable indicators. But how do these compare about advanced machine-learning algorithms like clustering and regression? When would be the best time to use these?
Duration - 1h 38m.
Author - Bob Mather.
Narrator - Cliff Weldon.
Published Date - Sunday, 22 January 2023.
Copyright - © 2018 Abiprod Pty Ltd ©.
Location:
United States
Description:
Are you a machine-learning enthusiast looking for a practical day-to-day application? Or are you just trying to incorporate machine-learning software in your trading decisions? This audiobook is your answer. While machine learning and finance have generally been seen as separate entities, this audiobook looks at several applications of machine learning in the financial world. Whether it is predicting the best time to buy a stock in a day-trading scenario or to determine the long-term value of a stock, financial ratios and common sense have always been used as reliable indicators. But how do these compare about advanced machine-learning algorithms like clustering and regression? When would be the best time to use these? Duration - 1h 38m. Author - Bob Mather. Narrator - Cliff Weldon. Published Date - Sunday, 22 January 2023. Copyright - © 2018 Abiprod Pty Ltd ©.
Language:
English
Opening Credits
Duration:00:00:12
1 chapter 1 01
Duration:00:09:52
2 chapter 2 01
Duration:00:27:09
3 chapter 3 01
Duration:00:19:05
4 chapter 4 01
Duration:00:07:46
5 chapter 5 f
Duration:00:06:36
6 chapter 6 01
Duration:00:24:51
7 conclusion 01
Duration:00:03:03
Ending Credits
Duration:00:00:18