Using model in view/api functions bad practice?
Is using say, the User model like this:
User.query.filter_by(id=0).first()
In the functions which define the endpoints bad practice? Should I make methods in the model to get the things I need?
/r/flask
https://redd.it/5ja1j8
Is using say, the User model like this:
User.query.filter_by(id=0).first()
In the functions which define the endpoints bad practice? Should I make methods in the model to get the things I need?
/r/flask
https://redd.it/5ja1j8
reddit
Using model in view/api functions bad practice? • /r/flask
Is using say, the User model like this: User.query.filter_by(id=0).first() In the functions which define the endpoints bad practice? Should...
Bayesian Survival Analysis in Python with pymc3
http://austinrochford.com/posts/2015-10-05-bayes-survival.html
/r/pystats
https://redd.it/4f6fnp
http://austinrochford.com/posts/2015-10-05-bayes-survival.html
/r/pystats
https://redd.it/4f6fnp
Austin Rochford
Bayesian Survival Analysis in Python with pymc3
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.datafram
.dataframe th{background: #eee;}
.dataframe td{
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min-width:5em;
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/* Format summary rows */
.datafram
Creating tables of values with python
###edit
id like to use this in ipython notebook if that makes a difference
******
I'm not sure if this is the best place for this question or not but I figured it
might be pandas related or something and someone here would know...
Basically I'm wondering what the best way to generate and display something such
as
t : 1, 2, 3, 4...
-----------------------
x = 2t : 2, 4, 6, 8...
-----------------------
y = 5/t : 5, 5/2, 5/3, 5/4...
Hopefully that's clearly a table of values :)
cheers
/r/pystats
https://redd.it/4f70co
###edit
id like to use this in ipython notebook if that makes a difference
******
I'm not sure if this is the best place for this question or not but I figured it
might be pandas related or something and someone here would know...
Basically I'm wondering what the best way to generate and display something such
as
t : 1, 2, 3, 4...
-----------------------
x = 2t : 2, 4, 6, 8...
-----------------------
y = 5/t : 5, 5/2, 5/3, 5/4...
Hopefully that's clearly a table of values :)
cheers
/r/pystats
https://redd.it/4f70co
reddit
Creating tables of values with python • /r/pystats
###edit id like to use this in ipython notebook if that makes a difference ****** I'm not sure if this is the best place for this question or...
[R] Yes you should understand backprop
https://medium.com/@karpathy/yes-you-should-understand-backprop-e2f06eab496b
/r/MachineLearning
https://redd.it/5ja7nq
https://medium.com/@karpathy/yes-you-should-understand-backprop-e2f06eab496b
/r/MachineLearning
https://redd.it/5ja7nq
Medium
Yes you should understand backprop
When we offered CS231n (Deep Learning class) at Stanford, we intentionally designed the programming assignments to include explicit…
Build Marvin the Depressed Reddit Bot in Python
http://pythonforengineers.com/build-marvin-the-depressed-reddit-bot-in-python/
/r/Python
https://redd.it/5j98z0
http://pythonforengineers.com/build-marvin-the-depressed-reddit-bot-in-python/
/r/Python
https://redd.it/5j98z0
Wagtail CMS on Divio Cloud, complete with live and test servers and Dockerised local development environment
https://www.youtube.com/watch?v=MVnK1xn4H9M
/r/django
https://redd.it/5jcx63
https://www.youtube.com/watch?v=MVnK1xn4H9M
/r/django
https://redd.it/5jcx63
YouTube
Wagtail on Divio Cloud
In just a few minutes, you can launch a new Django Wagtail CMS website on the Divio Cloud, including live and test servers and a Dockerised local development...
No programming experience. Big ideas. How to get started?
I've got some "big data" ideas that I want to begin to explore, but my last programming experience was building HTML-based web-pages in high school. I've fooled around with "R" a little bit as well.
What is the best way to teach myself how to be a iPython ninja?
/r/IPython
https://redd.it/4u8o21
I've got some "big data" ideas that I want to begin to explore, but my last programming experience was building HTML-based web-pages in high school. I've fooled around with "R" a little bit as well.
What is the best way to teach myself how to be a iPython ninja?
/r/IPython
https://redd.it/4u8o21
reddit
No programming experience. Big ideas. How to get started? • /r/IPython
I've got some "big data" ideas that I want to begin to explore, but my last programming experience was building HTML-based web-pages in high...
Does anyone know how to set specific vim-bindings in Ipython 5.0.0?
I have activated vim-like bindings in the profile configuration file, but I would like to set specific keybindings (like 'jk' for escape). Any ideas?
/r/IPython
https://redd.it/4tq7te
I have activated vim-like bindings in the profile configuration file, but I would like to set specific keybindings (like 'jk' for escape). Any ideas?
/r/IPython
https://redd.it/4tq7te
reddit
Does anyone know how to set specific vim-bindings in... • /r/IPython
I have activated vim-like bindings in the profile configuration file, but I would like to set specific keybindings (like 'jk' for escape). Any ideas?
Tutorial: working with missing data in Python
http://nbviewer.jupyter.org/github/ResidentMario/python-missing-data/blob/master/missing-data.ipynb
/r/pystats
https://redd.it/4eh4va
http://nbviewer.jupyter.org/github/ResidentMario/python-missing-data/blob/master/missing-data.ipynb
/r/pystats
https://redd.it/4eh4va
BuzzFeedNews/Detecting Match Fixing in Tennis Matches (Open Data Journalism)
https://github.com/BuzzFeedNews/2016-01-tennis-betting-analysis/blob/master/notebooks/tennis-analysis.ipynb
/r/JupyterNotebooks
https://redd.it/4d2ouo
https://github.com/BuzzFeedNews/2016-01-tennis-betting-analysis/blob/master/notebooks/tennis-analysis.ipynb
/r/JupyterNotebooks
https://redd.it/4d2ouo
GitHub
2016-01-tennis-betting-analysis/tennis-analysis.ipynb at master · BuzzFeedNews/2016-01-tennis-betting-analysis
Methodology and code supporting the BuzzFeed News/BBC article, "The Tennis Racket," published Jan. 17, 2016. - 2016-01-tennis-betting-analysis/tennis-analysis.ipynb at master · Bu...
JupyterLab: the next generation of the Jupyter Notebook
http://blog.jupyter.org/2016/07/14/jupyter-lab-alpha/
/r/IPython
https://redd.it/4szoix
http://blog.jupyter.org/2016/07/14/jupyter-lab-alpha/
/r/IPython
https://redd.it/4szoix
Project Jupyter
JupyterLab: the next generation of the Jupyter Notebook
Learning the lessons of the Jupyter Notebook It's been a long time in the making, but today we want to start engaging our community with an early (pre-alpha) release of the next generation of the Jupyter Notebook application, which we are calling JupyterLab.…
Kalman and Bayesian Filters in Python
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python
/r/JupyterNotebooks
https://redd.it/4aw2wh
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python
/r/JupyterNotebooks
https://redd.it/4aw2wh
GitHub
GitHub - rlabbe/Kalman-and-Bayesian-Filters-in-Python: Kalman Filter book using Jupyter Notebook. Focuses on building intuition…
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filt...
What's everyone working on this week?
Tell /r/python what you're working on this week! You can be bragging, grousing, sharing your passion, or explaining your pain. Talk about your current project or your pet project; whatever you want to share.
/r/Python
https://redd.it/5jdewv
Tell /r/python what you're working on this week! You can be bragging, grousing, sharing your passion, or explaining your pain. Talk about your current project or your pet project; whatever you want to share.
/r/Python
https://redd.it/5jdewv
reddit
What's everyone working on this week? • /r/Python
Tell /r/python what you're working on this week! You can be bragging, grousing, sharing your passion, or explaining your pain. Talk about your...
[D] What are current relations between (algebraic) topology and deep learning?
I am a graduate student in AI with an undergrad in pure math (algebraic topology, abstract algebra, PDEs). Currently I am working a lot on deep learning - especially manifold learning and nonlinear embeddings. Since finding a mapping on a nonlinear sub manifold and the normally unknown network architecture are closely linked I asked myself, if there is a connection between the topological properties of the map/diffeomorphism generated by a DNN and it's capabilities to learn certain things. I found this introduction on colah's blog and I also started to read on the methodology of Gunnar Carlson's topological data analysis. However, colah's blog gives me the idea where the journey could head to and Carlson's way is not really connected to research on DNN (in terms of learning diffeomorphism of your data) - as far as I see it. But I am stuck finding deeper literature on that. Can you give any recommendation for papers or introductory work on this boundary? Everything bringing together the topology of neural networks, group theory and algebraization (e.g. using functors such as chain complexes or homotopy) would really interest me.
/r/MachineLearning
https://redd.it/5jfaox
I am a graduate student in AI with an undergrad in pure math (algebraic topology, abstract algebra, PDEs). Currently I am working a lot on deep learning - especially manifold learning and nonlinear embeddings. Since finding a mapping on a nonlinear sub manifold and the normally unknown network architecture are closely linked I asked myself, if there is a connection between the topological properties of the map/diffeomorphism generated by a DNN and it's capabilities to learn certain things. I found this introduction on colah's blog and I also started to read on the methodology of Gunnar Carlson's topological data analysis. However, colah's blog gives me the idea where the journey could head to and Carlson's way is not really connected to research on DNN (in terms of learning diffeomorphism of your data) - as far as I see it. But I am stuck finding deeper literature on that. Can you give any recommendation for papers or introductory work on this boundary? Everything bringing together the topology of neural networks, group theory and algebraization (e.g. using functors such as chain complexes or homotopy) would really interest me.
/r/MachineLearning
https://redd.it/5jfaox
reddit
[D] What are current relations between... • /r/MachineLearning
I am a graduate student in AI with an undergrad in pure math (algebraic topology, abstract algebra, PDEs). Currently I am working a lot on deep...
Top 10 Python libraries of 2016
https://tryolabs.com/blog/2016/12/20/top-10-python-libraries-of-2016/
/r/Python
https://redd.it/5jf64k
https://tryolabs.com/blog/2016/12/20/top-10-python-libraries-of-2016/
/r/Python
https://redd.it/5jf64k
Tryolabs
Top 10 Python libraries of 2016
JupyterLab Building Blocks for Interactive Computing | SciPy 2016 | Brian Granger
https://www.youtube.com/watch?v=Ejh0ftSjk6g
/r/IPython
https://redd.it/4t0due
https://www.youtube.com/watch?v=Ejh0ftSjk6g
/r/IPython
https://redd.it/4t0due
YouTube
JupyterLab: Building Blocks for Interactive Computing | SciPy 2016 | Brian Granger
Project Jupyter provides building blocks for interactive and exploratory computing. These building blocks make science and data science reproducible across o...
Statistics for Software: Instrumenting Code for Reliability and Performance
https://www.paypal-engineering.com/2016/04/11/statistics-for-software/
/r/pystats
https://redd.it/4ecj6q
https://www.paypal-engineering.com/2016/04/11/statistics-for-software/
/r/pystats
https://redd.it/4ecj6q
Solving a nonlinear ordinary differential equation
http://nbviewer.jupyter.org/github/Jabberwockyll/NumericalODE/blob/master/numerical_ode.ipynb
/r/JupyterNotebooks
https://redd.it/4awf63
http://nbviewer.jupyter.org/github/Jabberwockyll/NumericalODE/blob/master/numerical_ode.ipynb
/r/JupyterNotebooks
https://redd.it/4awf63
nbviewer.jupyter.org
Notebook on nbviewer
Check out this Jupyter notebook!
Jupyter Events Calendar
This calendar contains the dates and locations of Jupyter Developer talks and workshops.
[Jupyter Events](https://calendar.google.com/calendar/embed?src=p51j0ac1iccmj44tae12hq4dk0%40group.calendar.google.com&ctz=America/Los_Angeles)
/r/IPython
https://redd.it/4t2g9y
This calendar contains the dates and locations of Jupyter Developer talks and workshops.
[Jupyter Events](https://calendar.google.com/calendar/embed?src=p51j0ac1iccmj44tae12hq4dk0%40group.calendar.google.com&ctz=America/Los_Angeles)
/r/IPython
https://redd.it/4t2g9y
Causal Discovery Software Available for Big Data Analysis
The Center for Causal Discovery (CCD) (www.ccd.pitt.edu) has released the Fast Greedy Search (FGS) algorithm (an optimized version of Chickering's Greedy Equivalence Search algorithm) for use by biomedical investigators who are searching for causal associations in large sets of continuous data. A technical paper describing the optimization is available at http://arxiv.org/abs/1507.07749. It is available as free and open source software. This release is just the first step toward providing a suite of algorithms that will assist biomedical researchers in analyzing their data to obtain causal insights.
Using simulated data, FGS was able to learn a causal network on data containing 50,000 variables and 1,000 samples in about 15 minutes on a laptop computer. While FGS does not model hidden variables that cause two or more measured variables, an upcoming release of another algorithm will do so.
FGS is available as a command line implementation (Causal-cmd) that calls a local Java library or as a Java web application (Causal-web) that runs the analysis at the Pittsburgh Supercomputing Center; the API’s can also be run through R (R-causal) or Python (Py-causal). Additional details and instructions for downloading both these versions of the software are available at
http://www.ccd.pitt.edu/wiki/index.php?title=Tools_and_Software.
Our goal is to help the biomedical community use causal modeling to gain novel insights and drive innovative research, so we hope to make these tools as usable and useful as possible. We welcome any and all feedback that you might have, which will help us improve this and future releases.
/r/pystats
https://redd.it/4cqctx
The Center for Causal Discovery (CCD) (www.ccd.pitt.edu) has released the Fast Greedy Search (FGS) algorithm (an optimized version of Chickering's Greedy Equivalence Search algorithm) for use by biomedical investigators who are searching for causal associations in large sets of continuous data. A technical paper describing the optimization is available at http://arxiv.org/abs/1507.07749. It is available as free and open source software. This release is just the first step toward providing a suite of algorithms that will assist biomedical researchers in analyzing their data to obtain causal insights.
Using simulated data, FGS was able to learn a causal network on data containing 50,000 variables and 1,000 samples in about 15 minutes on a laptop computer. While FGS does not model hidden variables that cause two or more measured variables, an upcoming release of another algorithm will do so.
FGS is available as a command line implementation (Causal-cmd) that calls a local Java library or as a Java web application (Causal-web) that runs the analysis at the Pittsburgh Supercomputing Center; the API’s can also be run through R (R-causal) or Python (Py-causal). Additional details and instructions for downloading both these versions of the software are available at
http://www.ccd.pitt.edu/wiki/index.php?title=Tools_and_Software.
Our goal is to help the biomedical community use causal modeling to gain novel insights and drive innovative research, so we hope to make these tools as usable and useful as possible. We welcome any and all feedback that you might have, which will help us improve this and future releases.
/r/pystats
https://redd.it/4cqctx