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Best Python modules for data mining

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Best Python modules for data mining

Getting Started with Deep Learning

  • That said, TensorFlows easy ability to build upon its InceptionV3 model and Torchs great CNN resources including easy-to-use temporal convolution set these two technologies apart for CNN modeling capability.
  • RNN Modeling Capability: Recurrent neural networks (RNNs) are used for speech recognition, time series prediction, image captioning, and other tasks that require processing sequential information.
  • As prebuilt RNN models are not as numerous as CNNs, it is therefore important if you have a RNN deep learning project that you consider what RNN models have been previously implemented and open sourced for a specific technology.
  • For instance, Caffe has minimal RNN resources, while Microsofts CNTK and Torch have ample RNN tutorials and prebuilt models.
  • For instance, for an image recognition application with a Python-centric team we would recommend TensorFlow given its ample documentation, decent performance, and great prototyping tools.

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Getting Started with Deep Learning

12 Python Resources for Data Science

  • About 8,300 articles related to Python have been posted on Data Science Central, according to Google.
  • Below is a small sample — the 12 most useful and popular articles to get started with Python and data science.
  • The Guide to Learning Python for Data Science has been moved here.
  • To receive updates about Python and any other data science topics,sign-up with DSC

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12 Python Resources for Data Science

Chapter 15: Learning Model Building in Scikit-learn : A Python Machine Learning Library

  • Given below is an example of how one can load an exemplar dataset: – – – – – – # load the iris dataset as an example from sklearn.datasets import load_iris – iris = load_iris() – – # store the feature matrix (X) and response vector (y) – X =…
  • Note: The CSV file used in example below can be downloaded from here: – weather.csv – – import pandas as pd – – # reading csv file – data = pd.read_csv(‘weather.csv’) – – # shape of dataset – print(Shape:, data.shape) – – # column names – print(\nFeatures:, data.columns) – -…
  • Now, in order to determine their accuracy, one can train the model – using the given dataset and then predict the response values for same dataset – using that model and hence, find the accuracy of model.
  • A better option is to split our data into two parts: first one for training our – machine learning model, and second one for testing our model.
  • As we approach to end of this article, here are some benefits of using – scikit-learn over some other machine learning libraries(like R): – – – – Consistent interface to machine learning models – – – – – Provides many tuning parameters but with sensible defaults – – – -…

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Chapter 15: Learning Model Building in Scikit-learn : A Python Machine Learning Library

seatgeek/fuzzywuzzy

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seatgeek/fuzzywuzzy

Comparison of top data science libraries for Python, R and Scala [Infographic]

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Comparison of top data science libraries for Python, R and Scala [Infographic]

10 Selection Python Machine Learning Library

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10 Selection Python Machine Learning Library

Twitch

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Twitch

Open Census

  • Specs – – – – – – – – – – – – – – – – – – – – – – SSL Support – Yes – – – – – – – – – – – – – Authentication Model – Unspecified – – – – – -…
  • Yes – – – – – – Type – Web/Internet – – – – – Scope – Single purpose API – – – – – Device Specific – No – – – – – – – – – – – – Architectural Style – Indirect – – – – -…
  • API Mashups (0) – – – – – – – – – Sorry, no mashups for this API.
  • Related Articles (1 ) – – – – – – – – – – – – – – – – – – – – – Twenty APIs have been added to the ProgrammableWeb directory in categories including Marketing, Mapping, and Weather.
  • View all 415 RELATED APIS

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Open Census

Github Tutorial for Beginners

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Github Tutorial for Beginners

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