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How can I find the Bayesian network (of a survey data that I have) using python. I am planning to use the pgmpy library and test different structure learning algorithms (like: PC, Hill climbing, Tabu, K2.....) to find the network and dependencies of the variables. Can someone help me on how to start with that.
You could also try pyAgrum (https://agrum.gitlab.io, https://pyagrum.readthedocs.io). Many notebooks can be found from http://webia.lip6.fr/~phw/aGrUM/docs/last/notebooks/.
The bnlearn library can be useful in this case. There are many examples and a Colab notebook notebook. Disclaimer: I am the author of this library.
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I'm looking to start building a database with python so I can make more dynamic web pages and just as a project and I want it to just be stored as a file like a .db file but I can't find any intermediate friendly tutorials or tutorials that arent online cloud options.
A relatively powerful option for Python is sqlite3 from the stdlib.
You can find tutorials for this in places like YouTube and sqlitetutorial.net
And for better understanding of how the library was intended to be used, visit the official documentation on Python's website
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I need to learn how to use databricks, using the Python programming language. Does anyone have any introductory course tips that teach how to use the Databricks community (which is free), where I can use the Python language?
Any tips swill be appreciated!
There's a lot of tutorials, you can find many stuffs googling some keywords, like databricks community, python, ....
Here are some options, that in my opinion is friendly:
https://medium.com/analytics-vidhya/beginners-guide-on-databricks-spark-using-python-pyspark-de74d92e4885;
https://towardsdatascience.com/getting-started-with-databricks-analyzing-covid-19-1194d833e90f;
https://hevodata.com/learn/databricks-python/.
In these tutorials an easy-to-understand language is used. The first steps are also detailed here.
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Any resources to learn Python and using Python to learn linear programming.
at that time the Harvard Edu can be provided free python course. this is best time to learn python. I hope this link helps you...
https://online-learning.harvard.edu/catalog?keywords=&paid%5B1%5D=1&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
I found it very helpful to get started with PuLP.
Following two links provide a basic insight into the topic IMO:
https://towardsdatascience.com/linear-programming-and-discrete-optimization-with-python-using-pulp-449f3c5f6e99
and
https://hackernoon.com/linear-programming-in-python-a-straight-forward-tutorial-a0d152618121
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I've found only two:
http://splinter.cobrateam.info/
http://lettuce.it/index.html
I'd like to know you practices and experiences with these (or other) tools.
In my experience, Robot Framework (http://robotframework.org/) is an amazing framework which can be combine with RIDE to write acceptance tests in a BDD way.
It supports many libraries (including selenium) and lets you extend it by creating your own, everything in a very simple way.
This is where I started from a couple of years ago: http://www.wallix.org/2011/07/26/how-to-use-robotframework-with-the-selenium-library/
I would suggest you to take a look also to Selenium IDE:
http://seleniumhq.org/download/
It worked well for a small set of test I need to write years ago
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Someone could point out sites/books where I can find introductory documentation about the architecture of the Python VM?
I'm interested in the C version, but if there are easy-to-follow references about other implementations it could be helpful too.
I'm trying to find any kind of resources of higher level than plain source code (however, UML diagrams or something like that would be nice) And also, information about the design decisions involved, including tradeoffs between the different factors (performance, stability, simplicity).
You should be able to find the information you need at https://github.com/python/cpython/blob/HEAD/Python/ceval.c
If that's too low level for you, try
http://www.python.org/dev/peps/pep-0339/
http://codespeak.net/pypy/dist/pypy/doc/interpreter.html
http://thermalnoise.wordpress.com/2007/12/30/exploring-python-bytecode/
https://docs.python.org/library/dis.html#python-bytecode-instructions
http://wiki.python.org/moin/ByteplayDoc
http://peak.telecommunity.com/DevCenter/BytecodeAssembler
http://nedbatchelder.com/blog/200804/wicked_hack_python_bytecode_tracing.html
https://jasonleaster.github.io/2016/02/21/architecture-of-python-virtual-machine/
Inside The Python Virtual Machine by Obi Ike-Nwosu.