Pinned Repositories
A-Whale-off-the-Port-folio-
This project explores the risk of investments in algorithmic trading strategies.
Financial_Planning
In this project, I developed a prototype application to allow members to assess their monthly personal finances and also be able to forecast a reasonably good retirement plan based on cryptocurrencies, stocks, and bonds.
LSTM_Stock_Predictor
I used deep learning, recurrent neural networks to model bitcoin closing prices. One model uses the FNG indicators to predict the closing price while the second model uses a window of closing prices to predict the nth closing price.
PyBank
Using financial records, I automated a process to analyze and produce an easy-to-read output making your job easier.
Risky_Business
I built and evaluated several machine-learning models to predict credit risk using free data from LendingClub. I employed different techniques for training and evaluating models with imbalanced classes and used the imbalanced-learn and Scikit-learn libraries to build and evaluate models.
Robo_Advisor
I created a robo advisor that could be used by customers or potential new customers to get investment portfolio recommendations for retirement.
The-Young-and-the-Credit-less
Our group chose this question to bring attention to the little knowledge that young loan applicants have. Based on our findings in our models we explore: Which age group is the least likely to apply for loans? Which group is most likely to default on loans?
The_Presidential_Effect
This project plots four indicators as variables of the economy across the span of the Reagan, Bush Sr., Clinton, Bush Jr., Obama, and Trump presidencies. Balance of trade, real gross domestic product (GDP), stock, and unemployment were chosen as indicators of economic health.
Time_Series-Regression_Analysis
This project uses the many time-series tools (Hodrick-Prescott Filter, ARMA, ARIMA and GARCH models, linear regression, etc.) to predict future movements in the value of the Japanese yen versus the U.S. dollar.
You-Sure-can-Attract-a-Crowd-
I created an ERC20 token that was minted through a Crowdsale contract that I can leveraged from the OpenZeppelin Solidity library. This crowdsale contract managed the entire process, allowing users to send ETH and get back PUP (PupperCoin). This contract minted the tokens automatically and distributed them to buyers in one transaction.
ltayara1's Repositories
ltayara1/You-Sure-can-Attract-a-Crowd-
I created an ERC20 token that was minted through a Crowdsale contract that I can leveraged from the OpenZeppelin Solidity library. This crowdsale contract managed the entire process, allowing users to send ETH and get back PUP (PupperCoin). This contract minted the tokens automatically and distributed them to buyers in one transaction.
ltayara1/Financial_Planning
In this project, I developed a prototype application to allow members to assess their monthly personal finances and also be able to forecast a reasonably good retirement plan based on cryptocurrencies, stocks, and bonds.
ltayara1/Multi-Blockchain-Wallet-in-Python
This project builds a system that can create an HD wallet as a portfolio management system that supports not only traditional assets like gold, silver, stocks, etc, but crypto-assets as well. Once I've integrated this "universal" wallet, I used Ethereum and Bitcoin Testnet.
ltayara1/The-Young-and-the-Credit-less
Our group chose this question to bring attention to the little knowledge that young loan applicants have. Based on our findings in our models we explore: Which age group is the least likely to apply for loans? Which group is most likely to default on loans?
ltayara1/The_Presidential_Effect
This project plots four indicators as variables of the economy across the span of the Reagan, Bush Sr., Clinton, Bush Jr., Obama, and Trump presidencies. Balance of trade, real gross domestic product (GDP), stock, and unemployment were chosen as indicators of economic health.
ltayara1/Time_Series-Regression_Analysis
This project uses the many time-series tools (Hodrick-Prescott Filter, ARMA, ARIMA and GARCH models, linear regression, etc.) to predict future movements in the value of the Japanese yen versus the U.S. dollar.
ltayara1/A-Whale-off-the-Port-folio-
This project explores the risk of investments in algorithmic trading strategies.
ltayara1/Blockchain-Project-Approval-in-Local-Government
This project seeks to improve internal financial processes to increase accuracy, productivity, and efficiency using a blockchain contract to simplify processes.
ltayara1/LSTM_Stock_Predictor
I used deep learning, recurrent neural networks to model bitcoin closing prices. One model uses the FNG indicators to predict the closing price while the second model uses a window of closing prices to predict the nth closing price.
ltayara1/PyBank
Using financial records, I automated a process to analyze and produce an easy-to-read output making your job easier.
ltayara1/Risky_Business
I built and evaluated several machine-learning models to predict credit risk using free data from LendingClub. I employed different techniques for training and evaluating models with imbalanced classes and used the imbalanced-learn and Scikit-learn libraries to build and evaluate models.
ltayara1/Robo_Advisor
I created a robo advisor that could be used by customers or potential new customers to get investment portfolio recommendations for retirement.
ltayara1/Contracts-with-Solidity
This project builds a smart contract to automate company finances to increase transparency and automate accounting and auditing.
ltayara1/FinTech_Meets_GovTech
An overview of PayIt, a governmental financial technology payments company.
ltayara1/Proof-of-Authority
For this project, I set up a custom testnet blockchain, sent a test transaction, and created a repository. I also wrote instructions on how to use the chain.
ltayara1/Pythonic_Monopoly
This project builds a prototype dashboard and trials this initial offering with investment opportunities for the San Francisco market. The goal of this dashboard was to provide charts, maps, and interactive visualizations that help customers explore the data and determine if they want to invest in rental properties in San Francisco.
ltayara1/Tales-from-the-Crypto
The first part of this activity pulls the latest news articles for bitcoin and ethereum from the news api and creates a DataFrame for each with sentiment scores for each coin. We end by creating a summary of the bitcoin and ethereum DataFrames separately.