Some link :
QI dao create stable coin by collateral method. What make QI compete with other stable coin is it built on Polygon (Matic) network which is L2 solution for Eth.
User could mint stable coin miToken by collateral token. Some thing like user create DAI with ETH collateral on Marker DAO
Currently QI Dao support for MATIC token. But in near future, it could support many other token like ETH, BTC as collateral
QI is governor token which user could vote for QI Dao improvement.
In near future it QI holder and stake could get reward…
Try to understand some main dapps running on polygon
Iron is Partially-collateralised stablecoin on the Polygon network and on the Binance Smart Chain. At time of writing this, it has 1.6b total value locked
Suppose we have one sample training with input is 1 and target is 2. Using a simplified neuron with only one weight. What is value of weight so the model best fit with our (input, target) pair ?.
From input and weight, we calculated output. Then from target and output we could calculate error use mean square error formula.
Now the problem become find weight so we could minimize error. Of course in this simplified neuron, we could easily find out w=2 then minimum error = 0. In real, error or loss function contain thousands to millions of weight and…
In this post we will explain how to do web scraping with beautiful soup and selenium.
Any data scraping task start with a url to page which contain data need to be scraped. Selenium web driver will take input url and produce content in html.
Some people will ask, why we need selenium ? because we could simply use package like
requests to download html from input url.
For example if…
Pandas provide great tool to working with time series data. Time series data is data which have time related to it. Example of time series data like bitcoin price, stock market, weather.
Let load whole time bitcoin history data from coinmarketcap. Data contain columns
Date, Open*, High*, Low, Close**, Volume, Market Cap.Here we have data from 2013 to recently 2019.
Merge in pandas means combine data from 2 data tables to create a new table.
Let’s load some data for our demo. Suppose we have 2 tables,
order, and the tables are linked by a column
customer_id as below.
With data analysis, filtering data is a crucial task. This post will help you understand how to do filtering with pandas.
First, let’s load some data for our demo. This is movie data set which contains 5 columns ‘movie_title’, ‘director_name’, ‘imdb_score’, ‘duration’, ‘genres’.