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Scala Machine Learning Projects

You're reading from   Scala Machine Learning Projects Build real-world machine learning and deep learning projects with Scala

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788479042
Length 470 pages
Edition 1st Edition
Languages
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Author (1):
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Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
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Toc

Table of Contents (13) Chapters Close

Preface 1. Analyzing Insurance Severity Claims FREE CHAPTER 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 12. Other Books You May Enjoy

Historical and live-price data collection

As stated earlier, we will utilize both historical as well live data. We will be using the Bitcoin historical price data from Kaggle. For the real-time data, Cryptocompare API will be used.

Historical data collection

For training the ML algorithm, there is a Bitcoin Historical Price Data dataset available to the public on Kaggle (version 10). The dataset can be downloaded from https://www.kaggle.com/mczielinski/bitcoin-historical-data/. It has 1 minute OHLC data for BTC-USD pairs from several exchanges.

At the beginning of the project, for most of them, data was available from January 1, 2012 to May 31, 2017; but for the Bitstamp exchange, it's available until October...

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