blackmarkt/udacity-ml

Udacity-ML

Problem Statement

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This project attempts to use Supervised Learning Classifier model to predict the price of Bitcoin.

Dataset

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The datasets used for this project can be downloaded from Blockchain

The following individual csv files were downloaded housing the datasets: Volume, Volatility, Hash Rate, Mining Difficulty, Average Number of Transactions, Average Block Size, Market Capitalization, Bid/Ask Spread.

Training set has 1436 samples. Testing set has 360 samples.

Libraries

The libraries used for this project are os, time, functools, numpy, pandas, matplotlib, a multiplicity of sklearn modules,

Scripts

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Several Python scripts are available to train the model:

• preprocess.py: script containing the function that imports the csv files, formats and returns a dataframe.

• visuals.py: script containing various plot functions

• walk_forward.py: script that contains the walk_forward function

• pred.py: script that contains the pred_dict, acc_test, f_test, and pred function

• capstone_btc_project_121417: All development Python code

Report A final report explaining this project and the surrounding problem domain is available as * report.pdf.

License---

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The code for this project is open source and available under the terms of the license in this repository.