Phantombuster VS NumPy

Phantombuster

A marketplace of simple to use no-code APIs

NumPy

NumPy is the fundamental package for scientific computing with Python

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2023-07-03

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2023-05-13

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NumPy videos

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Learn NUMPY in 5 minutes - BEST Python Library!

Category Popularity

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User comments

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Reviews

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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

Social recommendations and mentions

Based on our record, NumPy should be more popular than Phantombuster. It has been mentiond 112 times since March 2021. 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.

Phantombuster mentions (15)

I challenged myself to get 10K+ weekly post impressions on Linkedin
There are some tools available to automate this part for you like phantom buster and LinkedIn helper. Source: 10 months ago
Retargeting Linkedin connections/visits by email
Https://phantombuster.com/ is also a very good option/tool. Source: 12 months ago
Los Angeles job boards, future brands will include marketing hospitality marketing
We are in pre-launch and are marketing the CuratedLA Collective through various channels, including a ProductHunt launch, our access to AngelList Talent (now Wellfound) sourcing, niche subreddits, PhantomBuster drip campaigns, personal and professional circles of the CuratedLA audience, LinkedIn and cross-platform recommendations. Source: over 1 year ago
Just tried connecting with someone for the first time this week, it's only Monday, and I got the weekly invitation limit reached message. Is there another reason why I am getting this message?
Source: I used to work at a LinkedIn automation company and I'm working on another LinkedIn networking tool now. Source: over 1 year ago
Best lead generator for a web design/Seo company?
There are scrapers like Apollo.io that you can use. There is also phantombuster.com. Source: over 1 year ago

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 / 18 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 / 18 days ago
Awesome List
NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 23 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 / 25 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 / 10 months ago