uncleflo
Registered since September 28th, 2017
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Coronavirus chart: see how your country compares | Free to read | Financial Times
Saved by uncleflo on January 12th, 2022.
Financial Times one pager for overviewing the growth of the Corona Virus. Governments’ stark daily figures on the spread of coronavirus are difficult to compare across countries, and may be significant undercounts. But the data needed to analyse the more reliable and comparable excess mortality metric are only available in a few jurisdictions, leaving these official case and death counts the best available data for much of the world. Deaths are somewhat more reliable, but remain problematic because countries have different rules for what deaths to include in their official numbers. The most notable difference between countries’ Covid mortality figures is whether or not they include deaths outside hospitals, particularly in care homes. Some countries like France and the UK have even changed which deaths they include during the course of the epidemic. For either measure, we use a seven-day rolling average to adjust for the impact of administrative delays to reporting new data over weekends.
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How TF-IDF algorithm determines keyword importance - arbitrue Blog
Saved by uncleflo on December 23rd, 2018.
There are many tools in the developer’s toolbox when it comes to automatic data extraction. A good example is TF-IDF algorithm (Term Frequency – Inverse Document Frequency) which helps the system understand the importance of keywords extracted using OCR. Here’s how TF-IDF can be used for invoice and receipt recognition. In this article we focus on other techniques in order to make this text file “understandable” to a computer. For this purpose, we must delve into the world of NLP or Natural Language Processing. We will focus mainly on how we can transform our file of raw text into a format that will easily be understandable by our algorithm. In a nutshell, TF-IDF is a technique for understanding how important a word is in a document which is often used as a weighting factor for numerous use cases. TF-IDF takes under consideration how frequent a word appears in a single document in relation to how frequent that word is in general. Search engines can use TF-IDF to determine which results are the most relevant for a search query.
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Count number of lines in a file using DOS
Saved by uncleflo on May 29th, 2018.
Every once in a while I get on a computer and I need to count the number of lines in a file. My first instinct is to open my text editor (editplus) and hit ctrl+end to get to the bottom of the document. Then I can view the status bar which will tell me the line number. This works fine when I am on my computer but not when I am on another computer that does not have editplus installed. My next option might be to open this file in notepad and do the exact same thing. This will work fine if the file is not to large. The problem is I often deal with very large files. I need a quicker way to produce the same results. This is where DOS comes into play. I can use the following command and let DOS quickly tell me the number of lines in the file.
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Find Out How Much Traffic a Website is Getting
Saved by uncleflo on February 8th, 2014.
Do you want to spy (or ‘research’) on your competitors to know how much traffic their sites are getting? Now there are a bunch of traffic estimation services (like Alexa, Compete, Quantcast, etc.) from where you can obtain statistics (page views + unique visitors) of almost any website for free but is the data accurate? I did a rough comparison using actual data from Google Analytics data and here are the results
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How to create a random string using PHP? - Stack Overflow
Saved by uncleflo on February 4th, 2013.
The basic algorithm is to generate <length> times a random number between 0 and <number of characters> − 1 we use as index to pick a character from our set and concatenate those characters. The 0 and <number of characters> − 1 bounds represent the bounds of the $charset string as the first character is addressed with $charset[0] and the last with $charset[count($charset) - 1].
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