In this project we utilize PARSIQ Smart Triggers and Google Spreadsheets integration to track and visualize AXS token transfers on Ethereum and Binance Smart Chain that involves most liquid exchanges. AXS is an Ethereum token that powers Axie Infinity, a blockchain-based game where players can battle, collect, and build a digital kingdom for their pets. … Read more
As part of the Gitcoin bounty for Casper hackathon we developed web application in python Flask that generates QR code. We host the application at http://sample-env.eba-wb9b6xgh.us-east-2.elasticbeanstalk.com/ on AWS Elastic Beanstalk with GitHub pipeline. The GitHub repository for the project. The overview of the project The app generates QR codes for transactions on Casper local nodes, … Read more
On the first day of Autumn in 2021, I finished my first Kaggle competition as a part of Solvers Club. Solvers Club has a great community of Data scientists, Data engineers, programmers and great people, in general, that motivated me to try new ideas and blending techniques throughout the month. In particular, I want to congratulate all … Read more
Humans unlike computers make sense of what we see based on our experiences, memories and biological structure. Human brain extracts and analyses humongous volumes of data using visual cues. To understand the true effect of sight, 40% of our nerve fibers are linked to the retina, and 90% of information transmitted to the brain is … Read more
Volatility estimators are especially valuable in modelling financial returns and capturing time-variability of financial series. The ongoing $100k Optiver Realized Volatility Prediction Competition on Kaggle has further sparked interest in the research of high-frequency data and revitalized the interest in the field. In the following articles we introduced time-series data and realized volatility as well as financial … Read more
This post is a write up on sklearn pipeline with multiple regression models for multiple target columns using traditional and established libraries such as numpy, pandas, scipy and sklearn. This post explores further the topics of the previous article on sklearn pipeline for time-series data, which you can find here: Some of the ideas for … Read more
Following $100k Optiver Realized Volatility Prediction Competition on Kaggle, interest in financial time-series and concepts has drastically increased. Besides, in this website we have not travelled past the very introductory concepts in time-series ecnnometrics. Therefore in this blog post we are going to introduce the concepts of simple returns, log returns and realized volatility. In … Read more
This post is a write up on sklearn pipeline with multiple regression models using traditional and established libraries like numpy, pandas, scipy and sklearn. In this post we are making a model for time-series data which we introduced in this post: Some of the ideas for this post came from researching for machine learning competition … Read more
Many programming languages have an asynchronous (async) feature that improves their concurrency primitives. In 2015 Python 3.5 introduced coroutines with async and await syntax. Since then the async capability of Python has improved dramatically with the rise of libraries such as asyncio, library to write concurrent code using the async/await syntax, and AIOHTTP, an asynchronous HTTP Client/Server for asyncio and Python. … Read more
To conduct the data analysis, for example during the market research, we first need to determine the scope and collect the necessary data. Some websites and companies provide easier and more convenient way to access the data than others. However, many limit the number of requests from one IP address. Therefore in order to scrape … Read more