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NumPy VS Google Cloud Dataproc

Compare NumPy VS Google Cloud Dataproc and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

NumPy videos

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Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Google Cloud Dataproc videos

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Dataproc

Category Popularity

0-100% (relative to NumPy and Google Cloud Dataproc)

NumPy

Google Cloud Dataproc

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Dashboard
38 38%
Data Dashboard
62% 62
Data Science Tools
100 100%
Data Science Tools
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using NumPy and Google Cloud Dataproc. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare NumPy and Google Cloud Dataproc

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Google Cloud Dataproc Reviews

We have no reviews of Google Cloud Dataproc yet.
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Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Google Cloud Dataproc. While we know about 112 links to NumPy, we've tracked only 3 mentions of Google Cloud Dataproc. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

NumPy mentions (112)

  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Develop a script that iterates over the image database, preprocesses each image according to the model's requirements (e.g., resizing, normalization), and feeds them into the model for prediction. Ensure the script can handle large datasets efficiently by implementing batch processing. Use libraries like NumPy or Pandas for data management and TensorFlow or PyTorch for model inference. Include... - Source: dev.to / 8 days ago
  • Documenting my pin collection with Segment Anything: Part 3
    NumPy: This library is fundamental for handling arrays and matrices, such as for operations that involve image data. NumPy is used to manipulate image data and perform calculations for image transformations and mask operations. - Source: dev.to / 8 days ago
  • Awesome List
    NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 13 days ago
  • NumPy for Beginners: A Basic Guide to Get You Started
    This guide covers the basics of NumPy, and there's much more to explore. Visit numpy.org for more information and examples. - Source: dev.to / 15 days ago
  • 2 Minutes to JupyterLab Notebook on Docker Desktop
    Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 9 months ago
View more

Google Cloud Dataproc mentions (3)

  • Connecting IPython notebook to spark master running in different machines
    I have also a spark cluster created with google cloud dataproc. Source: about 1 year ago
  • Why we don’t use Spark
    Specifically, we heavily rely on managed services from our cloud provider, Google Cloud Platform (GCP), for hosting our data in managed databases like BigTable and Spanner. For data transformations, we initially heavily relied on DataProc - a managed service from Google to manage a Spark cluster. - Source: dev.to / about 2 years ago
  • Data processing issue
    With that, the best way to maximize processing and minimize time is to use Dataflow or Dataproc depending on your needs. These systems are highly parallel and clustered, which allows for much larger processing pipelines that execute quickly. Source: over 2 years ago

What are some alternatives?

When comparing NumPy and Google Cloud Dataproc, you can also consider the following products

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

OpenCV - OpenCV is the world's biggest computer vision library

HortonWorks Data Platform - The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly...

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