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Scala Machine Learning Projects

You're reading from  Scala Machine Learning Projects

Product type Book
Published in Jan 2018
Publisher Packt
ISBN-13 9781788479042
Pages 470 pages
Edition 1st Edition
Languages

Table of Contents (17) Chapters

Title Page
Packt Upsell
Contributors
Preface
1. Analyzing Insurance Severity Claims 2. Analyzing and Predicting Telecommunication Churn 3. High Frequency Bitcoin Price Prediction from Historical and Live Data 4. Population-Scale Clustering and Ethnicity Prediction 5. Topic Modeling - A Better Insight into Large-Scale Texts 6. Developing Model-based Movie Recommendation Engines 7. Options Trading Using Q-learning and Scala Play Framework 8. Clients Subscription Assessment for Bank Telemarketing using Deep Neural Networks 9. Fraud Analytics Using Autoencoders and Anomaly Detection 10. Human Activity Recognition using Recurrent Neural Networks 11. Image Classification using Convolutional Neural Networks 1. Other Books You May Enjoy Index

High-level data pipeline of the prototype


The goal of this chapter is to develop a prototype of a system that will predict the short-term change of Bitcoin price, using historical data to train the algorithm, and real-time data to predict and select algorithms that perform better. In the scope of this project, there is no attempt to predict the actual price in dollars, but only whether it would increase or not. This is because Bitcoin price, to some extent, is not actually about price but about market expectations. This can be seen as patterns in a trader's behavior, which, on a higher level, is represented by previous price itself.

Figure 3: High-level data pipeline of the prototype

Of course, there is an objective price associated with Bitcoin; miners are willing to sell Bitcoins for profit. So the base price can be estimated by knowing all bills that all miners have to pay for the Bitcoins they mine, but that is outside the scope of this project.

From this perspective, rather than trying...

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