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I'm new to machine learning and I'm trying to create a machine learning classifier using python & Jupyter to match textual advertisements to websites that they will be displayed on. Is there any dataset that I could make use of?
You could get a lot of datas to train your NN e.g. on the U.S. government site
Or you load datasets from sklearn: e.g.:
from sklearn import datasets (link to sklearn)
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Are there specific python libraries which we can use to generate audio files?
What is the noise that we provide in this case
Which external libraries are useful
Basic Research
Got to know that we have to use vectors to generate audio signals rather than tensors in case of images
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Please share a link to a dataset that is effective for practicing NLP (Natural Language Processing).
I am beginner level and would like to improve my skills.
NLP is a very broad field, so if you want a specific dataset, you need to name a specific NLP problem (such as NER, sentiment analysis, summarization, etc.), and probably a specific language in which you want to solve this problem.
But still, there are places to look for NLP datasets and problems in general:
the NLP tag on Kaggle: https://www.kaggle.com/tags/nlp
a list of NLP datasets: https://github.com/niderhoff/nlp-datasets
a similar question on DS StackExchange: https://datascience.stackexchange.com/questions/6798/list-of-nlp-challenges
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I am wondering is there any polish language or Slavic language model on the base of which I could build a new model with my training set?
There're a lot of pretrained embedders, like LASER from Facebook. There's unofficial pypi lib, but it works just fine. If you want to reach seminal-like scores, there's no point in doing this all by hand. Embedders usually covers dozens of languages, so you can feed training data in any language you want. Your models will also work for those language out-of-the-box, even if you trained them on other languages.
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I am doing a dissertation on data visualization of land prices in Tanzania.
My intendants want me to use a GIS software to map the data on a map and use python code to visualize it.
My question is how can i use python to draw the maps ?
If you want to perform data visualisation, you can use the python library called matplotlib
To perform the mapping of data on geographical maps using matplotlib, here are the examples which helps you to get started.
I hope this helps you.
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I am looking for a python package that supports Monte Carlo Cross Validation (Repeated random sub-sampling validation). SkLearn has k-fold, but this will not allow me to specify the ratio of training/testing.
I have seen a package in R that will supposedly achieve this (Caret), but is there an equivalent for python?
The package you're after is in fact available in Scikit learn, but is called ShuffleSplit.
Check also the user guide here, where the function is referred to as Random permutations cross-validation.