Paper PublishingBitcoin Price Prediction using Machine Learning
Objective
The goal of this paper is to ascertain with what accuracy the direction of Bitcoin price in USD can be predicted. The price data is sourced from the Bitcoin Price Index. The task is achieved with varying degrees of success through the implementation of a Bayesian optimized recurrent neural network (RNN) and a Long Short Term Memory (LSTM) network.
Abstract
In this project, we attempt to predict the Bitcoin price accurately taking into
consideration various parameters that affect the Bitcoin value. For the first
phase of our investigation, we aim to understand and identify daily trends in
the Bitcoin market while gaining insight into optimal features surrounding
Bitcoin price. Our data set consists of various features relating to the
Bitcoin price and payment network over the course of five years, recorded
daily. For the second phase of our investigation, using the available
information, we will predict the sign of the daily price change with highest
possible accuracy.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
HARDWARE SPECIFICATIONS:
- Processor: I3/Intel
- Processor RAM: 4GB (min)
- Hard Disk: 128 GB
- Key Board: Standard Windows Keyboard
- Mouse: Two or Three Button Mouse
- Monitor: Any
SOFTWARE SPECIFICATIONS:
- Operating System: Windows 7+
- Server-side Script: Python 3.6+
- IDE: Jupyter Notebook
- Libraries Used: Pandas, Numpy.
Learning Outcomes
- About Python.
- About Pandas.
- About Numpy.
- About Sklearn.
- About Machine Learning.
- About Artificial Intelligent.
- About how to use the libraries.
- Cloud Overview.
- Virtualization.
- About how to create the registration table in sql.
- About model choosing.
- About how to generate the predictions with python code.
- Project Development Skills:
- Problem analyzing skills.
- Problem solving skills.
- Creativity and imaginary skills.
- Programming skills.
- Deployment.
- Testing skills.
- Debugging skills.
- Project presentation skills.
- Thesis writing skills.
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Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
