devinaa1604 Goto Github PK

api

This repository is for me to practice with APIs on Python

automation_with_python

This project aims to create a Python script for analyzing the financial records of a pseudo company by automating the process.

aws_and_unsupervised_learning

Generated analysis of cryptocurrencies is available on the trading market and how they can be grouped using classification. To do this I used unsupervised learning and Amazon SageMaker by clustering cryptocurrencies and creating plots to present results.

aws_cloud

This repository is for me to experiment with AWS Cloud.

classification

This repository is for me to experiment with various Classification Models using Python.

credit_risk_analysis_using_classification

This project aims to predict credit risk using various ensemble machine learning techniques. I have also tried to handle imbalance by using various sampling methods.

crypto_prices_using_nlp

I have applied natural language processing to understand the sentiment in the latest news articles featuring Bitcoin and Ethereum. I have used sentiment analysis and POS tagging for that.

deep-learning

This repository is for me to experiment with Deep Learning on Python.

demonetization_sentiment_analysis

This project aims to understand the sentiment when a bit policy is introduced by the government. I have used Twitter data to do sentiment analysis using R.

financial_planning-api

This project aims to assess personal finances, and also be able to forecast a reasonably good retirement plan based on cryptocurrencies, stocks, and bonds. It uses Alpaca API to extract the data and uses Python to run analysis and create visualizations.

fintech-case-study

fradulent_transactions-sql

Used SQL to analyze historical credit card transactions and consumption patterns in order to identify possible fraudulent transactions. Analyzed on Python and created visualizations.

lstm_stock_predictor-deep_learning

This project builds and evaluates deep learning models such as RNN using both the FNG values and simple closing prices to determine if the FNG indicator provides a better signal for cryptocurrencies than the normal closing price data.

multi-blockchain_wallet_in_python

myers_briggs_personality_predictor

The project aims to predict personality types using Natural Language Processing on the social media presence of more than 8600 individuals and implement various machine learning algorithms on a data set from Kaggle.

natural_language_processing

This repository is for me to practice with Natural Language Processing.

pandas

This repository is for me to practice with Pandas to use them in a financial environment.

portfolio_selection-pandas

This project aims to analyze various portfolios based on volatility, returns, risk, and Sharpe Ratio using Python and Pandas concepts.

predicting_housing_prices

Our aim was to make a model of housing prices that mimic the infamous Boston Housing Data but on a macro level. We wanted to use Multiple Linear Regression in order to predict the housing prices and make an interactive dashboard that tells the top 25 cities in the US for home investors in the next 5 years.

python

This repository is for me to practice with Python.

python-pandas

This repository is for me to practice with Python and Pandas.

pyviz

This repository is for me to practice visualizations and Python Dashboards using PyViz Library.

san_francisco_rental_analysis-pyviz

This project runs a rental analysis on the property in San Francisco and aims to provide customers with a broad range of portfolio options. I have used Python's PyViz library to create a dashboard that helps the customers determine if they want to invest in rental properties in San Francisco.

sql

This repository is for me to practice SQL using PostGreSQL and connecting it with Pandas.

subset_selection

This aims to run a subset selection process on the data set using R

testnet_blockchain

time-series

This repository is for me to practice Time Series Forecasting.

time_series_analysis_on_yen

This project aims to predict future yen prices using time-series models such as ARIMA as well as making out of sample and in sample predictions on Python