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Showing posts with the label NLP

downloading folders from google drive.

I wanted to download some course material on RL shared by the author via Google drive using the command line.  I got a bunch of stuff using wget a folder in google drive was a challenge. I looked it up in SO which gave me a hint but no solution. I installed gdown using pip and then used: gdown --folder --continue https://drive.google.com/drive/folders/1V9jAShWpccLvByv5S1DuOzo6GVvzd4LV if there are more than 50 files you need to use --remaining-ok and only get the first 50. In such a case its best to download using the folder using the UI and decompress locally. Decompressing from the command line created errors related to unicode but using the mac UI I decompressed without a glitch.
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Building a OCR using NLI Ephermera and manuscripts.

Image
The OCR task can be broken down as follows. Acquire the image. Segment it into regions according to the following labels:  Image,  Text Areas with optional rotation Tabular Data with optional rotation Scale down very large text to  suitable size glyphs Improve results by adding terms to better model the noise extant on page. Improve results by using lexical and grammatical knowledge into classifier. Ideally all this should be done by an end to end system. A common complex layout of Hebrew sacred texts with non rectangular columns with related but independent  sequences Once text area are detected requires a page segmentation algorithm to break down text areas into lines and glyphs.  Looking at some samples from the NLI ephemera database one would wish to add steps to clean up and rescale some elements whose fonts are too small. Also if one had a suitable model, perhaps add details to text that is too small. The challenges are...
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downloading folders from google drive.

I wanted to download some course material on RL shared by the author via Google drive using the command line.  I got a bunch of stuff using wget a folder in google drive was a challenge. I looked it up in SO which gave me a hint but no solution. I installed gdown using pip and then used: gdown --folder --continue https://drive.google.com/drive/folders/1V9jAShWpccLvByv5S1DuOzo6GVvzd4LV if there are more than 50 files you need to use --remaining-ok and only get the first 50. In such a case its best to download using the folder using the UI and decompress locally. Decompressing from the command line created errors related to unicode but using the mac UI I decompressed without a glitch.
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Random Thoughts on Linear Regressions

Regression Analysis TLDR Regression is the oldest and most powerful tool in a data scientist's toolbox. Under ideal conditions multiple linear regression would be the best and only tool a data scientist would want to use... In reality you would use a modern nonparametric variant or a different algorithm. Still, the main ideas I . discuss here  will pop up in many other models and algorithms. This post is my brain dump on regression - I'll update it as time allows to cover the many aspects of this technique.
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SQL - Selection v.s. Projection

Selection and projection are two high level processes taking place when SQL queries are executed. Selection is choosing some records (rows) from a table and leaving others out. e.g. rows having name='oren'. Projection is the choosing some columns from each record and leaving others out. e.g. only name. So the select keyword performs projection while the where and keyword performs selection. Clearly the choice of using the keyword select for projection (choosing columns) rather than choosing rows, is an unfortunate flaw in the design of SQL, but this oversight is too well established to be fixed.
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