Ambeone Student’s Projects Gallery

Based on the Big Data Analytics & Machine Learning Techniques taught in Ambeone’s Programs

This is a Gallery of some glimpses Data Science projects done by recent Ambeone students as part of their program.In case you are interested to know more about a particular project/projects, you may contact us for details .

Ambeone Data Science Project

Bitcoin Stock Market Prediction using Data Science & Time Series Modeling & Understanding Public Perceptions using Sentiment Analysis

Submitted by : Daniel Alex


Ambeone Data Science Project


This project used Data Science techniques for BitCoin .

Bitcoin and cryptocurrencies are notorious for volatile market returns. Cryptocurrencies are hard to gain information on and ‘predict’ their future and longevity. A large part of this, is consumer misunderstanding based on the technology itself and the applications involved. Due to the highly ‘technical’ nature of the product and the novel concept, it can be difficult for the general public to have a clear singular view on Bitcoin as a currency and investment.

The objective was to explain the potential reasons for volatility in both the global markets and consumer perception.


  1. Provide a broad stock market prediction model using various Time Series models
  2. Get a better understanding of public perception and industry experts using Sentiment Analysis
  3. Use word clouds to break apart hidden patterns that reveal new information. i.e, the rise of Bitcoin scams
  4. Provide explanations for volatility in both markets and consumer recognition
  5. Provide potential solutions to decrease volatility and cognitive dissonance
  6. Explore business and industry opportunities to ‘close the information gap’

Data Source 

Yahoo Finance Historic Bitcoin Data

Data Science Techniques & Models Used

Time Series:
  • ETS, Arima, Auto Arima and Log Models
  • Garch Model
Social Media Sentiment Analysis
  • Twitter Sentiment Analysis: on Cryptocurrencies and Bitcoin: General Public
  • Twitter Sentiments: Industry and Financial experts
  • Wordcloud
  • Trend Analysis: WikiPedia Search Results
  • Youtube Sentiment Analysis: Fraudulent Giveaways
Ambeone Data Science Project
Ambeone Data Science Project
Spotify Artist Recommender System and Classification
Churn Model for Telecom Company Predicting Customers who may move to Competitor
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