Alpa Sheladia's Projects
A repository for Columbia FinTech Bootcamp Module 21 Advance Solidity homework
You sure can attract a crowd, ERC20 PupperCoin, Testing the Crowdsale
Tokenomics, Key Concepts, Ethereum, Smart Contract Vulnerabilities, Mapping Types, OpenZeppelin
In this project, our team collectively decided to compare two specific industries that have been negatively and postively affected by the Covid-19 pandemic. Due to the travel restrictions placed on people around the glode because of the pandemic, the airline industry has struggled to persevere in the market. On the other hand, the tech industry after taking a hit from the March lows has recovered completely and has even reached new record highs when compared with stock prices. We will be cleaning financial data of both the industries including the operating balance sheets of different companies and then also compare the two industries with stock prices and market caps.
Algorithmic trading, back testing, creating framework ect
API files
Machine learning and Algorithmic trading Using NLP / Logistic Regression to Predict Future Stock Movement Program that allows a user to choose a stock from the S&P 500 or VIX run a logistic regression model to predict the price movement of this stock ‘s on the future trade based on current sentiments of Reuters news articles and social media post related to that organization. This platform performs data training using various models to provide best analysis to help traders decide whether to buy or sell the stock.
AWS services utilization, SageMaker, Chatbot , Lambda function and more
Amazon Console developing RoboAdvisor using Lambda function
https://www.investopedia.com/terms/b/blockchain.asp Nodes https://medium.com/coinmonks/blockchain-what-is-a-node-or-masternode-and-what-does-it-do-4d9a4200938f Blockchain Wallets https://www.investopedia.com/terms/b/blockchain-wallet.asp https://blog.unocoin.com/what-happens-if-you-forget-your-bitcoin-wallet-keys-bbf563ce281a Digital Signature https://www.instantssl.com/digital-signature https://medium.com/@xragrawal/digital-signature-from-blockchain-context-cedcd563eee5 Hash https://www.investopedia.com/terms/h/hash.asp Blockchain Mining https://www.bitcoinmining.com/ , Consensus Algorithms https://www.binance.vision/blockchain/what-is-a-blockchain-consensus-algorithm , Proof of Authority https://www.binance.vision/blockchain/proof-of-authority-explained, Proof of Work https://en.bitcoin.it/wiki/Proof_of_work, Proof of Stake
use smart contracts to leverage an automated system that serves as a trading platform.
Blockchain Transactions, Wallets, Digital Signature, Hash, BIP, BIP32, BIP44, BIP 39,
Will create an account, Request a service/product, Provide a service/product, Pay with Nano, Receive Nano
This is a model of housing prices in California using the California Census Data.
Applying Binary Classification, supervise and unsupervised machine learning , prediction, decision trees ect
In this assignment, I have built and evaluate several machine-learning models to predict credit risk using free data from LendingClub. Credit risk is an inherently imbalanced classification problem (the number of good loans is much larger than the number of at-risk loans), so I needed to employ different techniques for training and evaluating models with imbalanced classes. You will see use of the imbalanced-learn and Scikit-learn libraries to build and evaluate models using the two following techniques: Resampling and Ensemble Learning.
Amazon SageMaker
RNN LSTM for Time Series, RNN LSTM for NLP, Tuning RNN LSTM Models, ROC Curve and AUC
Decentralized finance
Financial analysis and data slicing
A machine learning project for FinTechs
Deep Learning
Tokenization, Stopwords, Regex , Lemmatization, N-grams, corpus, TF-IDF, NLTK vs. spaCy, POS Tagging vs. Dependency Parsing
Tales from the Crypto
new repo