NumPy Reviews

Google Forms Reviews

1. ✓ Adrian | Mobile Forms - Digital Inspections - Enterprise Checklists - Data collection

   | Marketing at Mobile Forms | about 4 years ago
   A good beginners tool to start your digital transformation.

   One of our customers said: Our small mining operation needed to go from paper based process to digital forms. At first, Google forms allowed us to use this Web-based platform that lets individuals and businesses of all sizes build customizable forms to conduct surveys and generate real-time response charts.

   We saw that a small sample of our field workers quickly adopted the new way of working.

   Step 1: accomplished.

   Now unto step 2.

   How do we deploy this unto our whole team? We needed email notifications, offline response collection when without wifi on the field. Our CIO and his director of operations needed deep data and trends analysis as well. Our inspectors, when doing their audits, needed to capture approx. 25 high definition pictures, some audio notes and a video which wasn't really possible with google forms.

   So, we can 100% credit the use of google forms to our transition towards a paperless process, but as we navigated saashub.com a little more, we were able to discover a world of alternatives. We strongly suggest to start using google forms before undergoing a big implementation plan towards such enterprise level inspection tools like nspek or even cheaper solutions like prontoforms.

   I am not sure if we would start with google's solution first if we would to do this digital transformation all over, but it did allow us to discover it's limits pretty quickly.

   At some point, we needed custom fields and functions, and none of us was able to code, so the nSpek training that comes with the application definitely sets it's self apart, giving us full autonomy.

   🏁 Competitors: nSpek, ProntoForms

   👍 Pros:    No sign up cost

   👎 Cons:    Customization|Customer support|Data protection and security|No video|No pictures

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 / 19 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 / 20 days ago

• Awesome List

  NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 25 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 / 27 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

Google Forms mentions (0)