A Web Application for Bit Coin Price Prediction using Machine Learning

Project Code :TCMAPY550

Objective

The objective of this project is about forecasting for an bit coin data. Investing in Crypt-Currency have been increased a lot when compare to the earlier days. If we contribute to prevent the risk on investments, then it should be able to utilize for us, this study attempts to perform future forecasting on the price, by which we can control the risk. Our model will help to create future predictions which reduce the burden to the people who are continuously working on these.

Abstract

ABSTRACT:

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. The Random Forest achieves the highest classification accuracy. Finally, both deep learning models are benchmarked on both a GPU and a CPU with the training time on the GPU outperforming the CPU implementation by 67.7%.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

H/W SPECIFICATIONS:

Processor: I3/Intel Processor
RAM: 4GB (min)

Hard Disk: 128 GB

S/W SPECIFICATIONS:

Operating System: Windows 7+            
Server-side Script: Python 3.6+
IDE: PyCharm
Libraries Used: Pandas, Numpy, Scikit-Learn

Frame Work: Flask

Learning Outcomes

  • Scope of Real Time Application Scenarios.
  • What is a search engine and how browser can work.
  • What type of technology versions are used.
  • Use of HTML, and CSS on UI Designs.
  • Data Parsing Front-End to Back-End.
  • Working Procedure.
  • Introduction to basic technologies used for.
  • How project works.
  • Input and Output modules.
  • Practical exposure to
    • Hardware and software tools.
    • Solution providing for real time problems.
    • Working with team/ individual.
    • Work on Creative ideas.
  • Frame work use.
  • About python.

Demo Video

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