David Kennedy

David Kennedy

1549943250

Thought Crime is here.

A free and open dialogue is critical to the success of any civilisation. History shows that whenever free speech is oppressed, tyranny ensues.


I have just received another 30 day ban from FaceBook for sharing an image of the Hindu symbol for peace and unity, because either somebody flagged it or perhaps their algorithms mistakenly identified it as a Swastika, which is illegal in some countries.


Either way, the oppression of expression is the first step toward tyranny. We should all be wary of any attempts to suppress opinion, no matter how inane or offensive they may seem to some. The marketplace of ideas relies on this; good ideas will be encouraged and built upon, while bad ideas will eventually die out through a cultural form of natural selection.


Only those with invested interests seek to silence others who disagree with them. The truth will always emerge if open dialogue is allowed.

#image

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Uriah  Dietrich

Uriah Dietrich

1617985620

17 Open Crime Datasets for Data Science and Machine Learning Projects

For those looking to analyze crime rates or trends over a specific area or time period, we have compiled a list of the 16 best crime datasets made available for public use.

The datasets come from various locations around the world and most of the data covers large time periods.

#crime #crime-data #datasets #data #data-science #open-data #machine-learning #artificial-intelligence

Exploring Chicago’s Crime Rates

Taking a deep dive into Chicago’s crimes from 2012–2017

PHASE 1: Exploring the shape & structure of the data

Step 1: Gaining a higher-level understanding of the data

To begin, I looked at the shape of my data. I see there are 1456714 rows and 23 columns. These columns left to right are Unnamed, ID, Case Number, Date, Block, IUCR, Primary Type, Description, Location Description, Arrest, Domestic. Beat, District, Ward, Community Area, FBI Code, X Coordinate, Y Coordinate, Year, Updated On, Latitude, Longitude, and Location.

Step 2: Finding data quality issues

**ISSUE ONE: **The first column was unnamed and contained random digits for each row. As there was already an index, I deleted this column.

ISSUE TWO: Near the right end of the data frame, there was Latitude, Longitude, and Location. This Location column was just a repeat of the Latitude and Longitude values. I removed this and kept the separate Latitude and Longitude columns to ease processing.

**ISSUE THREE: **Several column names were composed of two words with spaces in between. To ease processing, I renamed these columns to have an underscore instead of the space.

#chicago #pandas-dataframe #data #sql #crime #exploring chicago’s crime rates

Anastasia soda

Anastasia soda

1624572000

My Thoughts on Losing A Million Dollars. DO NOT MISS!!!

My thoughts on losing a million dollars with the new tax plan
In this video I want to explain how investors may lose money with the new plan. Whether you’re invested in crypto, stocks, or real estate, this affects everyone. The new tax plan is targeted toward the richest 1% however, raising taxes always has ripple consequences. I personally have nothing against paying higher taxes, I’m very fortunate to make a high income and I need to pay my fair share.

WHAT IS A FAIR SHARE?

A study back in 2018 looked at the top 1% of earners which are people making more than $540,000 a year - that 1% of people represented 21% of all the income that was made that year. Now as far as taxes go, they paid 40% of the all the federal income taxes.

If we zoom out and look at the top 10% of people, which is anyone making more than $145,000 a year - which most people would still consider to be high income earners, they earned 48% of all the income. Hold on, that doesn’t sound fair - 10% earned nearly half of all the money? However they also paid 71% of all the federal income taxes. So if rich people pay more in taxes - the question becomes, why is there a myth about rich people not paying their fair share of taxes? Here’s the truth.

A lot of the wealthiest people make most of their money not through an active incomes like most people do from their job, but from the interest of their investments or the sale of stocks or other assets. And the sale of those assets get taxed at different, more favorable rates than incomes. So their incomes that they get from their jobs as CEOs means they still get taxed much more. So the rich do pay more, but they also pay less when it comes to investments because the majority of their money doesn’t come from an active income, it comes from the sale of assets - so it kind of makes sense why the rumor was started.

The interesting part about the myth that the rich get favorable taxes, is that its actually true for anyone who chooses to live like the rich do - which is to be an investor - so if you want to be rich that means spending less on fancy cars and watches, and spending more on assets like real estate, stocks or crypto - and then those tax rates will apply to you as well. So now let’s take a look at the changes.

THE CHANGES:

Long term capital gains taxes will go up from 20% to 39.6% (taxed for investments held longer than a year). Income taxes going up from 37% to 39.6% and corporate taxes going up from 21% to 28%. We’re told most of these changes affect only the richest 1% or anyone making over $400,000 a year. The truth however is a little more nuanced. Here are my thoughts on how each of these tax changes will affect regular investors.

HOW IT AFFECTS YOU:

When it comes to income taxes, I don’t think it’s going to change much of anything, it’s going up from 37% to 39.6% - that’s hardly anything, a very small increase that any rich person can afford - who cares.

When it comes to capital gains taxes for example - the sale of assets - here’s how it would affect someone like me - if hypothetically at the end of the year my stocks are worth a million dollars, and I sell that plus my entire crypto portfolio, and I lived in a state that had income taxes on top of it like California where I would pay an additional 12.3% on top of that, I could in theory end up paying a million dollars in taxes. Another downside is less revenue: https://bit.ly/3tfrFyD

The biggest change is a potential change to corporate taxes. If you make it more expensive to operate a business, they’ll increase the cost of their products. To what degree prices will go up - we’ll have to wait and see. At the end of the day, this proposed tax plan is not necessarily what will become law.

📺 The video in this post was made by Andrei Jikh
The origin of the article: https://www.youtube.com/watch?v=NHGz2VGk27M
🔺 DISCLAIMER: The article is for information sharing. The content of this video is solely the opinions of the speaker who is not a licensed financial advisor or registered investment advisor. Not investment advice or legal advice.
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#bitcoin #blockchain #million dollars #thoughts #my thoughts on losing a million dollars. do not miss!!!

Elton  Bogan

Elton Bogan

1602444720

Artificial Intelligence & Crime

Introduction

Purdue professors are trying to eliminate a return to prison for recently released criminals by _using _artificial intelligence to uncover risky behaviors which could then help identify when early intervention opportunities could be beneficial.

Study and Results

Results of a U.S. Department of Justice study indicated more than 80 percent of people in state prisons were arrested at least once in the nine years following their release. Almost half of those arrests came in the first year following release.

Marcus Rogers and Umit Karabiyik of Purdue Polytechnic’s Department of Computer and Information Technology, are leading an ongoing project focused on using AI-enabled tools and technology to reduce the recidivism rates for convicted criminals who have been released.

#data-science #crime #artificial-intelligence #machine-learning #ai

Paula  Hall

Paula Hall

1619438580

Analysis of NYC Reported Crime Data Using Pandas

Introduction

While I was learning Data Analysis using Pandas in Python, I decided to analyze the open data about New York City — the largest and most influential American metropolis. New York City is in reality a collection of many neighborhoods scattered among the city’s five boroughs: Manhattan, Brooklyn, the Bronx, Queens, and Staten Island. New York is the most populous and the most international city in the country.

Pandas is a high-level library for doing practical, real-world data analysis in Python. It is one of the most powerful and flexible open-source tools to analyze and manipulate data. In this article, my goal is to explore the wide range of opportunities for visual analysis with Pandas.

#crime #exploratory-data-analysis #data-visualization #pandas #nyc