Learn-Python | To make the users familiar with the syntax of Python | Reactive Programming library

by lugnitdgp Python Version: Current License: No License

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kandi X-RAY | Learn-Python Summary

Learn-Python is a Python library typically used in Programming Style, Reactive Programming applications. Learn-Python has no bugs, it has no vulnerabilities and it has low support. However Learn-Python build file is not available. You can download it from GitHub.

To make the users familiar with the syntax of Python.

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Learn-Python has a low active ecosystem.

It has 11 star(s) with 21 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 2 have been closed. On average issues are closed in 5 days. There are 16 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Learn-Python is current.

Quality

Learn-Python has no bugs reported.

Security

Learn-Python has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Learn-Python does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

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Learn-Python releases are not available. You will need to build from source code and install.

Learn-Python has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed Learn-Python and discovered the below as its top functions. This is intended to give you an instant insight into Learn-Python implemented functionality, and help decide if they suit your requirements.

Make a bear room .
helper function to find a power set in original sets
Prompt for gold room .
Start a cthulu room .
Start a room .
Calculates fatorial .
Find a city in the map .
Creates a color generator .
Prints a dead job
Multiply a .

Get all kandi verified functions for this library.

Learn-Python Key Features

No Key Features are available at this moment for Learn-Python.

Learn-Python Examples and Code Snippets

No Code Snippets are available at this moment for Learn-Python.

Community Discussions

Trending Discussions on Learn-Python

Scikit-learn cross_val_score throws ValueError: The first argument to `Layer.call` must always be passed

python naive Bayes tutorial - what is two_obs_test[continuous_list]?

Is there a way to do transformation on features X based on true labels in y?

How to use LSTM for sequence classification using KerasClassifier

What is the exact term for 'argv' in python?

AssertionError when trying to assert return value from two dictionaries with py.test

Why isn't `model.fit` defined in scikit-learn?

QUESTION

Scikit-learn cross_val_score throws ValueError: The first argument to `Layer.call` must always be passed

Asked 2021-Apr-06 at 09:24

I'm working on a deep learning project and I tried following a tutorial to evaluate my model with Cross-Validation.

I was looking at this tutorial: https://machinelearningmastery.com/use-keras-deep-learning-models-scikit-learn-python/

I started by first splitting my dataset into features and labels:

...

ANSWER

Answered 2021-Apr-06 at 06:08

model = KerasClassifier(build_fn=create_model(), ...)

Source https://stackoverflow.com/questions/66963373

QUESTION

python naive Bayes tutorial - what is two_obs_test[continuous_list]?

Asked 2021-Feb-11 at 20:39

I'm following a tutorial on Naive Bayes at https://towardsdatascience.com/why-how-to-use-the-naive-bayes-algorithms-in-a-regulated-industry-with-sklearn-python-code-dbd8304ab2cf but I'm stuck on interpreting the reference in the third code block to two_obs_test[continuous_list]

The full code listing is ...

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ANSWER

Answered 2021-Feb-11 at 19:52

The tutorial has too many gaps. I think a view of the insides of Naive Bayes without reading a whole book is better found at https://machinelearningmastery.com/naive-bayes-classifier-scratch-python/ . I am not persisting with the tutorial and I advise others to avoid it.

Source https://stackoverflow.com/questions/66094143

QUESTION

Is there a way to do transformation on features X based on true labels in y?

Asked 2020-May-27 at 13:08

I have checked other questions covering the topic such as this, this, this, this and this as well as some great blog posts, blog1, blog2 and blog3 (kudos to respective author) but without success.

What I want to do is to transform rows whose values are under a certain threshold in X, but only those that correspond to some specific classes in the target y (y != 9). The threshold is calculated based on the other class (y == 9). However, I have problems understanding how to implement this properly.

As I want to do parameter tuning and cross-validation on this I will have to do the transformation using a pipeline. My custom transformer class looks like below. Note that I haven't included TransformerMixin as I believe I need to take into account for y in the fit_transform() function.

...

ANSWER

Answered 2020-May-27 at 13:08

In the comments I was talking about this:

Source https://stackoverflow.com/questions/61975829

QUESTION

How to use LSTM for sequence classification using KerasClassifier

Asked 2019-Aug-31 at 11:43

I have a binary classification problem where I need to predict the potential future trendy/popular products based on customer interactions during 2010-2015.

Currently, my dataset includes 1000 products and each product is labelled as 0 or 1 (i.e. binary classification). The label was decided based on customer interactions during 2016-2018.

I am calculating how centrality measures changed over time for each product during 2010-2015 as the features for my binary classification problem. For example, consider the below figure that shows how degree centrality changed over time for each product.

More specifically, I analyse the change of following centrality measures as the features for my binary classification problem.

how degree centrality of each good changed from 2010-2016 (see the above figure)
how betweenness centrality of each good changed from 2010-2016
how closeness centrality of each good changed from 2010-2016
how eigenvector centrality of each good changed from 2010-2016

In a nutshell, my data looks as follows.

...

ANSWER

Answered 2019-Aug-31 at 05:11

There are many types of cross validation similar to how there are many types of neural networks. In your case you are trying to use kfold cross validation.

In the question you linked, it correctly states that kfold cross validation should not be used with time series data. You can’t accurately evaluate your model if you are training on data and then testing on data that occurred before the training data.

However, other forms of cross validation (such as the mentioned sliding window or expanding window) will still work with your time series data. There is a function in sklearn that splits the data using the expanding window method. https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html

With all that said, I am not sure if you are really using time series data. If you simply have the centrality scores for each year as a separate feature, then the order of your data does not matter since each item is only one data point (assuming that the scores of one item don’t impact another). In that case you can use kfold cross validation and other networks that work with iid data. You could even use non neural networks such as SVMs or decision trees.

Source https://stackoverflow.com/questions/57734955

QUESTION

What is the exact term for 'argv' in python?

Asked 2018-May-19 at 07:45

I am currently trying to grasp the exact name of argv function (if it can be called a function) that can be imported from sys or system-specific parameters. I found 3 definitions:

So which one is it? Perhaps it doesn't matter how one calls it? Does it even have an accepted name?

Thanks everyone!

...

ANSWER

Answered 2017-Oct-18 at 12:45

It doesn't really matter. It's a list (not a function), and the name argv is just borrowed from the conventional name used in C. Most of the time, you are better off using a library like argparse to process the command line arguments, in which case you won't even be using sys.argv directly.

Source https://stackoverflow.com/questions/46810439

QUESTION

AssertionError when trying to assert return value from two dictionaries with py.test

Asked 2017-Jul-26 at 09:44

I'm testing a text-based game I've been making to learn Python. The last few days I have been busy finding a solution for a problem I keep encountering. I have tried multiple test methods, but they all end up giving me the same error.

The problem is the following AssertionError (using py.test):

...

ANSWER

Answered 2017-Jul-25 at 15:28

You need to be able to identify each instance:

Source https://stackoverflow.com/questions/45307457

QUESTION

Why isn't `model.fit` defined in scikit-learn?

Asked 2017-Jan-06 at 19:51

I am following step 3 of this example:

...

ANSWER

Answered 2017-Jan-06 at 19:25

fit(x,y) is a method that can be used on an estimator.

In order to be able to use this method on model you would have to create model first and make sure its of an estimator class.

Documentation

Source https://stackoverflow.com/questions/41512715

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Learn-Python

You can download it from GitHub.
You can use Learn-Python like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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