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Krish Singh

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#Python for Data Science and Machine Learning Bootcamp
codequs.com/a/HJ9LSanh
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Streaming Live! Game development - Seven Card Game with #C-C++ #Python #Lua
Watch Now!
What is the name of this project? Sevens What will it be used for? Creating playing card library How many weeks are you already working on it? 0 weeks Programming language being used for this project? C++ Which packages, libraries and APIs are you using? STL Is it a fun or commercial project? Just for fun On which website can people test it and give feedback? Currently too early to run program Where do you need support? No real support needed Are...
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Get your hands on this cheatsheet to various codes and steps while performing exploratory data analysis in #Python using NumPy, Pandas & Matplotlib, and building a healthy predictive model. #analytics  
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Ümit Seren

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Good news
"Python 2.x versus Python 3.x": this is by now an old question. In the eyes of some people Python 2 is here to stay, and in the eyes of others Python has long been 3 only. PyPy's own position is that PyPy will support Python 2.7 forever---the RPython language in which PyPy is written is a subset ...
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Approaching (Almost) Any Machine Learning Problem | Abhishek Thakur http://blog.kaggle.com/2016/07/21/approaching-almost-any-machine-learning-problem-abhishek-thakur/
An average data scientist deals with loads of data daily. Some say over 60-70% time is spent in data cleaning, munging and bringing data to a suitable format such that machine learning models can b…
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From +Blake Girardot
For anyone interested a research group at nasa is working on automated
landslide detection and have released their python code.

The link can be found in the article:
http://earthobservatory.nasa.gov/IOTD/view.php?id=88319&src=eoa-iotd

"The Sudden Landslide Identification Product (SLIP) combs through
Earth imagery and analyzes consecutive images of the same location to
spot changes in soil moisture, muddiness, and other surface features.
The program also compares the hill slopes with topographic information
derived from digital elevation models, such as those built from the
Shuttle Radar Topography Mission (SRTM) and the Advanced Spaceborne
Thermal Emissions and Reflection Radiometer (ASTER). By combining this
information, SLIP can automatically pinpoint the locations of possible
landslides each time a new, cloud-free land image is acquired."
New open-source software called SLIP-DRIP uses satellite images and rainfall data to help identify otherwise overlooked landslides.
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Nelson Brown's profile photo
 
Isn't there also an effort to find landslides on Mars in MRO imagery?
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John Cook
owner

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Special functions in Sage use the Arb library described in these slides.
 
"Hypergeometric functions in Arb" - slides from my talk today at the FastRelax meeting in Toulouse: http://fredrikj.net/math/laas20160525.pdf
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`Detect roads and features in satellite imagery, by training neural networks with OpenStreetMap (OSM) data. This code lets you:

Download a chunk of satellite imagery
Download OSM data that shows roads/features for that area
Generate training and evaluation data
Running the code is as easy as install Docker, make dev, and run a script.

Contributions are welcome.`
DeepOSM - Train a deep learning net with OpenStreetMap features and satellite imagery.
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microelly's profile photoDaniel Kerkow's profile photo
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Very interesting. I was working on something similar some months ago for detecting ground structures like mining pits. Sadly, we had to drop the project. 
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Ross Hartshorn's profile photoudhay prakash pethakamsetty's profile photo
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I agree. But, in elimination type of interview, you can expect.
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Eric Lebigot

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Now the uncertainties Python package can sum tens of thousands (or much more) of numbers with uncertainty quite fast. I am proud to have finally found a way of massively speeding up the previous version of the package!

The uncertainties package can also be used to quickly obtain for instance cumulative sums of a large number of values with uncertainties (in addition to most mathematical operations on numbers, and even some operations on matrices).

100,000 numbers with uncertainty are summed about 5,000 times faster with version 3.0, compared to the previous version. Going from quadratic to linear time complexity does wonders. :) Finding a way to do it required quite a lot of thinking, even if I wonder why I did not find my current solution earlier!
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Eric Lebigot's profile photoPetter Strandmark's profile photo
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It does not know that sin takes values in [-1, 1]. It only does linear estimation.
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You must explore these wonderful and very useful Python talks and tutorials shared at PyCon 2016 Portland, Oregon. Catch up on what global experts talked about and whats the current trend in Python.
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Here is a cheat sheet to help you with various codes and steps while performing exploratory data analysis in Python using NumPy, Pandas & Matplotlib.
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Nelson Brown

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Took a while for the tutorials, but as far as I can tell, all of them should be up now :)
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A look at how Python's Dask can be useful when looking at a large dataset - in this case, the full extracted points of interest from OpenStreetMap.

In recent months, a host of new tools and packages have been announced for working with data at scale in Python. For an excellent and entertaining summary of these, I'd suggest watching Rob Story's Python Data Bikeshed talk from the 2015 PyData Seattle conference. Many of these new scalable data ...
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#SciPy2016 initial list of talks and posters is announced! Check out the lineup of fantastic presentations. Early bird registration ends Sunday 5/22! http://ow.ly/KXAh300fxA0 #Python
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`In this tutorial competition, we dig a little "deeper" into sentiment analysis. Google's Word2Vec is a deep-learning inspired method that focuses on the meaning of words. Word2Vec attempts to understand meaning and semantic relationships among words. It works in a way that is similar to deep approaches, such as recurrent neural nets or deep neural nets, but is computationally more efficient. This tutorial focuses on Word2Vec for sentiment analysis.`
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