kaggle | A collection of Kaggle solutions. Not very polished. | Machine Learning library

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X-Ray Key Features Code Snippets(3)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | kaggle Summary

kaggle is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Neural Network applications. kaggle has no bugs, it has no vulnerabilities and it has high support. However kaggle build file is not available. You can download it from GitHub.

I've been using Kaggle as an excuse to learn techniques in machine learning/artificial intelligence.

Support

Quality

Security

License

Reuse

Support

kaggle has a highly active ecosystem.

It has 680 star(s) with 133 fork(s). There are 40 watchers for this library.

It had no major release in the last 6 months.

kaggle has no issues reported. There are 1 open pull requests and 0 closed requests.

It has a positive sentiment in the developer community.

The latest version of kaggle is current.

Quality

kaggle has 0 bugs and 2 code smells.

Security

kaggle has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

kaggle code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

kaggle 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.

Reuse

kaggle releases are not available. You will need to build from source code and install.

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

kaggle saves you 89 person hours of effort in developing the same functionality from scratch.

It has 227 lines of code, 20 functions and 3 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Dump the submission to a directory
Build image submission for given model
Expand ary of ary
Load test images
Extracts neighbors from an image
Return a flattened version of the given size
Convert a value from a range
Convert an array to a range
Train a model
Build a model
Split training
Load training images
Convert an image into a list of neighbors
Returns cleaned path
Extracts patches from an image
Generate an image from an array
Save model to file
Load a model from a pickle file

Get all kandi verified functions for this library.

kaggle Key Features

No Key Features are available at this moment for kaggle.

kaggle Examples and Code Snippets

Main function of the kaggle .

python

Lines of Code : 32

License : No License

Copy

def main(loadfile=None, savefile=None):
    Xtrain, Ytrain, Xtest, Ytest = getKaggleMNIST()
    if loadfile:
        dbn = DBN.load(loadfile)
    else:
        dbn = DBN([1000, 750, 500, 10]) # AutoEncoder is default
        # dbn = DBN([1000, 750, 5

Generates a plot of the kaggle MNIST .

python

Lines of Code : 20

License : No License

Copy

def main():
    Xtrain, Ytrain, Xtest, Ytest = getKaggleMNIST()

    pca = PCA()
    reduced = pca.fit_transform(Xtrain)
    plt.scatter(reduced[:,0], reduced[:,1], s=100, c=Ytrain, alpha=0.5)
    plt.show()

    plt.plot(pca.explained_variance_ratio

Runs kaggle .

python

Lines of Code : 14

License : No License

Copy

def main():
    Xtrain, Ytrain, Xtest, Ytest = getKaggleMNIST()

    # same as autoencoder_tf.py
    Xtrain = Xtrain.astype(np.float32)
    Xtest = Xtest.astype(np.float32)
    _, D = Xtrain.shape
    K = len(set(Ytrain))
    dnn = DNN(D, [1000, 750,

Community Discussions

Trending Discussions on kaggle

how to calculate model accuracy in rstudio for logistic regression

Colab pro does not provide more than 16 gb of ram

what if the size of training set is not the integer multiple of batch size

Why flatten() is not working in co-lab whereas it worked in kaggle-notebook posted by other user?

Selecting rows based on status

Error "Unknown label type: 'continuous'" when I use IterativeImputer with KNeighborsClassifier

Streamlining cleaning Tweet text with Stringr

how to create columns based on same date

TypeError: slice indices must be integers or None or have an __index__ method (Albumentations/NumPy)

How to input user images to predict with Tensorflow?

QUESTION

how to calculate model accuracy in rstudio for logistic regression

Asked 2021-Jun-15 at 22:26

How do you calculate the model accuracy in RStudio for logistic regression. The dataset is from Kaggle.

...

ANSWER

Answered 2021-Jun-15 at 21:39

use the package ML metrics

Source https://stackoverflow.com/questions/67993693

QUESTION

Colab pro does not provide more than 16 gb of ram

Asked 2021-Jun-09 at 19:00

Today i upgraded my account to Colab pro. Although it prints the ram as:

...

ANSWER

Answered 2021-Jun-09 at 19:00

Looking at your error, the 16 GB are referring to the graphics card, not the ram.

As far as I know, using colab-pro enables you to use a graphics card with up to 16GB of VRAM.

You can check the VRAM amount by running the following code.

Source https://stackoverflow.com/questions/67872054

QUESTION

what if the size of training set is not the integer multiple of batch size

Asked 2021-Jun-09 at 05:18

I am running the following code against the dataset of PV_Elec_Gas3.csv, the network architecture is designed as follows

...

ANSWER

Answered 2021-Jun-09 at 05:18

NO!!!!

In your forward method you x.view(-1) before passing it to a nn.Linear layer. This "flattens" not only the spatial dimensions on x, but also the batch dimension! You basically mix together all samples in the batch, making your model dependant on the batch size and in general making the predictions depend on the batch as a whole rather than on the individual data points.

Instead, you should:

Source https://stackoverflow.com/questions/67896539

QUESTION

Why flatten() is not working in co-lab whereas it worked in kaggle-notebook posted by other user?

Asked 2021-Jun-07 at 20:58

I am working on a project for pneumonia detection. I have looked over kaggle for notebooks on the same. there was a user who stacked two pretrained model densenet169 and mobilenet. I copies whole kaggle notebook from the user where he didn't get any error, but when I ran it in google colab I get this error in this part:

part where error is:

...

ANSWER

Answered 2021-Jun-07 at 20:58

You have mixed up your imports a bit.

Here is a fixed version of your code

Source https://stackoverflow.com/questions/67877688

QUESTION

Selecting rows based on status

Asked 2021-Jun-06 at 17:48

I have this dataframe: https://www.kaggle.com/mpwolke/cusersmarildownloadsallcsv

I want to select only those countries whose status has changed over the year. I am clueless as to how can I to achieve this. Can someone please help me.

Thank you.

...

ANSWER

Answered 2021-Jun-06 at 15:33

Try with groupby filter.

Source https://stackoverflow.com/questions/67860775

QUESTION

Error "Unknown label type: 'continuous'" when I use IterativeImputer with KNeighborsClassifier

Asked 2021-Jun-05 at 18:31

I want to do a multiple imputation with IterativeImputer.

Here is the dataset (the original is from https://www.kaggle.com/jboysen/mri-and-alzheimers) :

alz_df_imp_categorical

The variables to impute are "educ" and "ses". As they are categorical I've choose to use a classifier (KNeighborsClassifier from sklearn). Predictors are continuous (except "sex").

This is the code :

...

ANSWER

Answered 2021-Jun-05 at 18:31

I just understood why it does not works. It's because IterativeImputer works only for continuous variables. So, apparently you can't apply multiple imputation for continuous variables with IterativeImputer. There is discussion about this here.

I saw it's possible to do simple imputation with categorical variables in python. However, it does not seem possible to do multiple imputation with this type of variables (anyway, I did not find).

Source https://stackoverflow.com/questions/67851934

QUESTION

Streamlining cleaning Tweet text with Stringr

Asked 2021-Jun-05 at 11:17

I am learning about text mining and rTweet and I am currently brainstorming on the easiest way to clean text obtained from tweets. I have been using the method recommended on this link to remove URLs, remove anything other than English letters or space, remove stopwords, remove extra whitespace, remove numbers, remove punctuations.

This method uses both gsub and tm_map() and I was wondering if it was possible to stream line the cleaning process using stringr to simply add them to a cleaning pipe line. I saw an answer in the site that recommended the following function but for some reason I am unable to run it.

...

ANSWER

Answered 2021-Jun-05 at 02:52

To answer your primary question, the clean_tweets() function is not working in the line "Clean <- tweets %>% clean_tweets" presumably because you are feeding it a dataframe. However, the function's internals (i.e., the str_ functions) require character vectors (strings).

cleaning issue

I say "presumably" here because I'm not sure what your tweets object looks like, so I can't be sure. However, at least on your test data, the following solves the problem.

Source https://stackoverflow.com/questions/67845605

QUESTION

how to create columns based on same date

Asked 2021-Jun-03 at 15:33

I have the dataset having columns....

...

ANSWER

Answered 2021-Jun-03 at 15:33

Might not be the most efficient solution, but this works.

First, you groupby the date and concatenate all the tweets for one date:

Source https://stackoverflow.com/questions/67823278

QUESTION

TypeError: slice indices must be integers or None or have an __index__ method (Albumentations/NumPy)

Asked 2021-Jun-03 at 05:20

Hi everyone can you please help me i'm getting this bug with random crop augmentation. TypeError: slice indices must be integers or None or have an index method

Code is below.

...

ANSWER

Answered 2021-Jun-03 at 05:20

I think the error is in this line:

Source https://stackoverflow.com/questions/67812484

QUESTION

How to input user images to predict with Tensorflow?

Asked 2021-Jun-03 at 03:15

For my project, I am using tensorflow to predict handwritten user input.

Basically I used this dataset: https://www.kaggle.com/rishianand/devanagari-character-set, and created a model. I used matplotlib to see the images that were being produced by the pixels.

My code essentially works with training data, but i want to up it up a little. Through CV2, I created a GUI that allows users to draw a Nepali Letter. After this, I have branching that tells the program to save the image inside the computer.

This is a snippet of my code for it:

...

ANSWER

Answered 2021-Jun-03 at 03:15

Understand the dataset:

the size of the image is 32 x 32
there are 46 different characters/alphabets

Source https://stackoverflow.com/questions/67795896

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

Vulnerabilities

No vulnerabilities reported

Install kaggle

You can download it from GitHub.
You can use kaggle 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 .

Find more information at: