by Jakub Konczyk | Released February 2019 | ISBN: 9781789803778

Explore Machine Learning methods to predict future financial events based on past dataAbout This VideoLearn the key Machine Learning (ML) techniques commonly used for Financial forecasting: from a simple Machine Learning model to using more complex onesExplore tools such as pandas, Scikit-Learn, Keras, and Tensorflow for applications in FinanceGet Hands-on training to prepare financial data for analysis and use it to make future value predictionsIn DetailA lot of solutions to key problems in the financial world require predicting the future patterns in data from the past to make better financial decisions right now. The evolution of modern machine learning methods and tools in recent years in the field of computer vision bring promise of the same progress in other important fields such as financial forecasting.In this course, you'll first learn how to quickly get started with ML in finances by predicting the future currency exchange rates using a simple modern machine learning method. In this example, you'll learn how to choose the basic data preparation method and model and then how to improve them. In the next module, you'll discover a variety of ways to prepare data and then see how they influence models training accuracy. In the last module, you'll learn how to find and test a few key modern machine learning models to pick up the best performing one.After finishing this course, you'll have a solid introduction to apply ML methods to financial data forecasting.The code bundle for this video course is available at - https://github.com/PacktPublishing/AI-for-FinanceDownloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com. If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you. Show and hide more

1. Chapter 1 : Introduction to Financial Forecasting
   • The Course Overview 00:05:37
   • What’s Financial Forecasting and Why It’s Important? 00:06:59
   • Installing Pandas, Scikit-Learn, Keras, and TensorFlow 00:06:11
   • Summary 00:01:07
2. Chapter 2 : Predicting Currency Exchange Rates with Multi-Layer Perceptron
   • Getting and Preparing the Currency Exchange Data 00:10:47
   • Building the MLP Model with Keras 00:10:03
   • Training and Testing the Model 00:21:12
   • Summary and What’s Next? 00:03:48
3. Chapter 3 : Loan Approval Prediction with GradientBoostingClassifier
   • Getting and Preparing the Loan Approval Data 00:09:53
   • Creating, Training, Testing, and Using a GradientBoostingClassfier Model 00:07:31
   • Summary and What’s Next? 00:02:39
4. Chapter 4 : Detecting Fraud in Financial Services Using Extreme GradientBoostingClassifier
   • Getting and Preparing Financial Fraud Data 00:09:51
   • Creating, Training, and Testing XGBoost Model 00:07:19
   • Summary and What’s Next? 00:02:46
5. Chapter 5 : Forecasting Stock Prices Using Long-Short Term Memory Network
   • Getting and Preparing the Stock Prices Data 00:12:43
   • Building the LSTM Model with Keras 00:06:53
   • Training and Testing the Model 00:10:43
   • Summary and What’s Next? 00:03:23
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