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[FreeCoursesOnline.Me] [Packt] AI For Finance [FCO]
TORRENT SUMMARY
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Explore Machine Learning methods to predict future financial events based on past data
Video Details
ISBN 9781789803778
Course Length 2 hours 19 minutes
Table of Contents
• INTRODUCTION TO FINANCIAL FORECASTING
• PREDICTING CURRENCY EXCHANGE RATES WITH MULTI-LAYER PERCEPTRON
• LOAN APPROVAL PREDICTION WITH GRADIENTBOOSTINGCLASSIFIER
• DETECTING FRAUD IN FINANCIAL SERVICES USING EXTREME GRADIENTBOOSTINGCLASSIFIER
• FORECASTING STOCK PRICES USING LONG-SHORT TERM MEMORY NETWORK
Video Description
A 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-Finance
Style and Approach
This video course offers a project-based approach with practical explanations to make sure you grasp the key aspects of each project and give you the skills required to develop financial forecasting tools in Python.
What You Will Learn
• Get hands-on financial forecasting experience using machine learning with Python, Keras, Scikit-Learn and pandas
• Use a variety of data preparation methods with financial data
• Predict future values based on single and multiple values
• Apply key modern Machine Learning methods for forecasting
• Understand the process behind choosing the best performing data preparation method and model
• Grasp Machine Learning forecasting on a specific real-world financial data
Authors
Jakub Konczyk
Jakub Konczyk has enjoyed and done programming professionally since 1995. He is a Python and Django expert and has been involved in building complex systems since 2006. He loves to simplify and teach programming subjects and share it with others. He first discovered Machine Learning when he was trying to predict the real estate prices in one of the early stage start-ups he was involved in. He failed miserably. Then he discovered a much more practical way to learn Machine Learning that he would like to share with you in this course. It boils down to “Keep it simple!” mantra.
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FILE LIST
Filename
Size
01.Introduction to Financial Forecasting/0101.The Course Overview.mp4
64 MB
01.Introduction to Financial Forecasting/0102.What’s Financial Forecasting and Why It’s Important.mp4
45.5 MB
01.Introduction to Financial Forecasting/0103.Installing Pandas, Scikit-Learn, Keras, and TensorFlow.mp4
23.4 MB
01.Introduction to Financial Forecasting/0104.Summary.mp4
7.3 MB
02.Predicting Currency Exchange Rates with Multi-Layer Perceptron/0201.Getting and Preparing the Currency Exchange Data.mp4
41 MB
02.Predicting Currency Exchange Rates with Multi-Layer Perceptron/0202.Building the MLP Model with Keras.mp4
38.4 MB
02.Predicting Currency Exchange Rates with Multi-Layer Perceptron/0203.Training and Testing the Model.mp4
79.9 MB
02.Predicting Currency Exchange Rates with Multi-Layer Perceptron/0204.Summary and What’s Next.mp4
6.5 MB
03.Loan Approval Prediction with GradientBoostingClassifier/0301.Getting and Preparing the Loan Approval Data.mp4
37.8 MB
03.Loan Approval Prediction with GradientBoostingClassifier/0302.Creating, Training, Testing, and Using a GradientBoostingClassfier Model.mp4
28.9 MB
03.Loan Approval Prediction with GradientBoostingClassifier/0303.Summary and What’s Next.mp4
4.9 MB
04.Detecting Fraud in Financial Services Using Extreme GradientBoostingClassifier/0401.Getting and Preparing Financial Fraud Data.mp4
38 MB
04.Detecting Fraud in Financial Services Using Extreme GradientBoostingClassifier/0402.Creating, Training, and Testing XGBoost Model.mp4
28.4 MB
04.Detecting Fraud in Financial Services Using Extreme GradientBoostingClassifier/0403.Summary and What’s Next.mp4
4.9 MB
05.Forecasting Stock Prices Using Long-Short Term Memory Network/0501.Getting and Preparing the Stock Prices Data.mp4
48.1 MB
05.Forecasting Stock Prices Using Long-Short Term Memory Network/0502.Building the LSTM Model with Keras.mp4
26.6 MB
05.Forecasting Stock Prices Using Long-Short Term Memory Network/0503.Training and Testing the Model.mp4
40.5 MB
05.Forecasting Stock Prices Using Long-Short Term Memory Network/0504.Summary and What’s Next.mp4
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