Two easy steps

Thank you to everyone that has already activated their DAI on Give Together. Today we made needed changes to the contract. There was a bug that did not forward rDAI to the charities when sent to the contract. This has been fixed in this commit. In addition to the fix, a few new methods have been added, including one to transfer ownership of the contact is necessary.

If you have activated your DAI on Give Together you will need to withdraw it and then activate it again. This is due to how rDAI works. When you activate your DAI it begins to wear a “hat” which specifies the beneficiary of the interest generated. You can read more about rDAI here. In the past the Give Together’s hat was #61. …


No Loss Charitable Donations powered by rDAI

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Give Together

Give Together allows you to donate to a new charity each week all at no loss to you!

Each week an Ethereum Smart Contract determines a new charity currently from this list (although we are open to adding more!). This week’s charity is Code for America and later today the interest generated will be redeemed to them (the contract became live on the mainnet last week). The interest accrues from the Compound Protocol and is redeemed to the smart contract using rDai. …


IPFS + ENS

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unsplash.com/photos/Q1p7bh3SHj8

When hosting a website usually you use a dedicated VPS like Digital Ocean, Linode, Google, or Amazon. After setting up your server you can register a domain at Google Domains or NameCheap. The last step is editing your DNS records to point your domain at your server. Now you can access your website by navigating to your domain name. However, there is a problem with this. Your VPS controls the hosting of your site and the domain name service you went with maintains control of your domain. What happens if your VPS goes down or the company you are using is suddenly blacklisted in your country? What if ICANN takes your domain from you? …


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Sentence parsing can be helpful in understanding the meaning, structure, and syntactical relationships in sentences. Two common types are dependency and constituency parsing which is also known as syntactical parsing. Dependency parsing is the process of defining the grammatical structure of a sentence by listing each word as a node and displaying links to its dependents. A constituency parsed tree displays the syntactic structure of a sentence using context-free grammar. Unlike dependency parsing which relies on dependency grammar. Both types of parsing are important in computational linguistics but there is much debate over which is better. …


In 100 lines of code

Investing in the stock market used to require a ton of capital and a broker that would take a cut from your earnings. Then Robinhood disrupted the industry allowing you to invest as little as $1 and avoid a broker altogether. Robinhood and apps like it have opened up investing to anyone with a connected device and gave non-investors the opportunity to profit from the newest tech start-up.

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“space gray iPhone X turned on” by rawpixel on Unsplash

However, giving those of us who are not economists or accountants the freedom to invest our money in the “hottest” or “trending” stocks is not always the best financial decision.

Thousands of companies use software to predict the movement in the stock market in order to aid their investing decisions. The average Robinhood user does not have this available to them. Primitive predicting algorithms such as a time-sereis linear regression can be done with a time series prediction by leveraging python packages like scikit-learn and iexfinnance. …


I recently read an article in the Washington Post titled, “Ranking the media from liberal to conservative, based on their audiences”. Inspiring me to rank news sites based on their subjectivity and polarity on a given subject, in this case, Donald Trump.

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Photo by rawpixel on Unsplash

I used Python to pull the following news sites for their 30 most recent articles that contained the keyword “Trump” (ranging from the liberal side of the Washington Post article to the conservative side):

  1. New Yorker
  2. NPR
  3. CNN
  4. Fox News
  5. Drudge Report
  6. Breitbart

Then performed a text analysis on the description of the article to return a list of how subjective (or opinionated) an article was and the polarity (whether the author felt positively or negatively about the Trump). By doing this I could come up with a (very basic) ranking of the News Sites on how biased they are about our President and what their opinions of him are. With this, I could compare with the Post article to what political affiliation the news source is most associated with and which is the most biased. …


After creating the Free Wtr bot using Tweepy and Python and this code, I wanted a way to see how Twitter users were perceiving the bot and what their sentiment was. So I created a simple data analysis program that takes a given number of tweets, analyzes them, and displays the data in a scatter plot.

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Image credit.

Setup

I had to install a few packages to create this: Tweepy, Tkinter, Textblob and matplotlib. You can install each of these with the pip package manager. For example:

pip install tweepy

or you can clone into the Github repository like this.

git clone https://github.com/sloria/textblob
cd textblob
python setup.py …


The information age has revolutionized the way we interact, communicate and are perceived. In the United States, approximately 90 percent of the population is on the internet, using Facebook and Google to catch up with high school friends and to answer their questions. Companies such as Google constantly collect data on search habits of the user and what they like, in order to provide more personalized results and to improve their company.

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Data collection and the selling of this personal data has been a topic of controversy lately, primarily due to the Facebook and Cambridge Analytica scandal. In the 2017 hit Sci-Fi movie The Circle, the main character Mae obtains a job at a company eerily similar to Google, called the Circle. The company created a social network paralleled to Facebook called True You, and is constantly creating new software and products that revolve around collecting copious amounts of data because “Knowing is good; Knowing everything is better.” As the film nears the end, the Circle knows everything about anyone and can track a person down in under 20 minutes. While being greatly exaggerated this shows the potential of what improper use of data can lead to, and begs the question should we allow access to people’s private data in order to improve our personalization of services we use or even to the government in order to increase national security? The proper use of data can greatly improve products and make our lives easier, however, we, as consumers, deserve the right to know how our information is being collected and used. …


After creating the Free Wtr bot using Tweepy and Python and this code, I wanted a way to see how Twitter users were perceiving the bot and what their sentiment was. So I created a simple data analysis program that takes a given number of tweets, analyzes them, and displays the data in a scatter plot.

Image for post
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Image credit.

Setup

I had to install a few packages to create this: Tweepy, Tkinter, Textblob and matplotlib. You can install each of these with the pip package manager. For example:

pip install tweepy

or you can clone into the Github repository like this.

git clone https://github.com/sloria/textblob
cd textblob
python setup.py …


With about 15% of Twitter being composed of bots, I wanted to try my hand at it. I googled how to create a Twitter bot and was brought to a cleanly laid out web app. It allowed you to create a bot that would like, follow, or retweet a tweet based on a keyword. The problem was that you could only create one bot for one function.

So I decided to code a bot myself with Python and the Tweepy library.

Setup

First, I downloaded Tweepy. You can do this using the pip package manager.

pip install tweepy

You can also clone the GitHub repository if you do not have pip installed. …

About

Lucas Kohorst

@rit @foundryservices

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