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NumPy VS Amazing Marvin

Compare NumPy VS Amazing Marvin and see what are their differences

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Amazing Marvin logo Amazing Marvin

Customizable personal productivity tool
  • NumPy Landing page
    Landing page //
    2023-05-13
Not present

Amazing Marvin is a customizable and feature-rich personal task/project manager that includes lots of unique features designed to help with procrastination and overwhelm. You can enable and disable individual features based on your unique needs: Calendar sync, dependencies, deadlines, dashboards etc.

Amazing Marvin

$ Details
paid Free Trial
Platforms
Browser Windows Android iOS Web Mac OSX Linux Cross Platform
Release Date
2017 June

NumPy features and specs

No features have been listed yet.

Amazing Marvin features and specs

  • Time Tracking: Yes
  • Time Blocking: Yes
  • Calendar and Scheduler: Yes
  • Calendar sync: Yes
  • Calendar View: Yes
  • Task management: Yes
  • Project Management: Yes
  • Planner: Yes
  • Task dependencies: Yes
  • Task Board View: Yes
  • Task dasboard: Yes

NumPy videos

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

Amazing Marvin videos

ADHD Productivity Tools - Amazing Marvin Review

More videos:

  • Review - Amazing Marvin Productivity and Time Management Tracker

Category Popularity

0-100% (relative to NumPy and Amazing Marvin)
Data Science And Machine Learning
Task Management
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Project Management
0 0%
100% 100

User comments

Share your experience with using NumPy and Amazing Marvin. 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 Amazing Marvin

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.
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

Amazing Marvin Reviews

  1. Extremely powerful todo list manager

    I used Remember the Milk for years, but they were slow to fix bugs and new features hardly ever appeared. Marvin is, as the name says, Amazing. Very powerful 'smart' lists of tasks, searching, customisation. It does take a while to get to grips with the huge range of features.

    🏁 Competitors: Remember The Milk

Social recommendations and mentions

Based on our record, NumPy should be more popular than Amazing Marvin. 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.

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 / 13 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 / 13 days ago
  • Awesome List
    NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 19 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 / 21 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
View more

Amazing Marvin mentions (29)

  • Struggling with life, infp struggle the most? Please help?
    Again there are many great free ones out there, but my personal recommendation is definitely this one. It is paid, but the cost is not far off a pint of beer these days and you can customise it however you want (you could think of it as an investment in terms of the value it brings into your life vs the cost). Source: about 1 year ago
  • How do you get over the hurdle of desperately wanting to start using a task manager but feel totally overwhelmed and panicked about trying to remember and input all the many things that should go into it, not to mention deciding which one? (AuDHD)
    I have recently realized that there will be no perfect tool you will find just by looking things up. You literally do have to try around w a few apps (or more traditional methods) and see which one you enjoy. It took me a while but I found smth called Amazing Marvin. I love it because it’s very customizable. I think when we try to look for the “perfect” tool, we really are looking for tons of customizability so we... Source: about 1 year ago
  • My workspace. Not pictured: walking treadmill that I slide out from under my bed while monitors and keyboard are in standing mode.
    Amazing Marvin: https://amazingmarvin.com/. I love it. Super steep learning curve, but once you get it, it's so smooth. Source: over 1 year ago
  • How do you track goals and projects?
    I'm a big fan of Amazing Marvin]. Goals, projects, tasks, habits and a lot more. Extremely powerful smart lists. It's an excellent app, but it does have a learning curve. Source: over 1 year ago
  • [request] To-do app w click-drag of cards in 2x2 or 3x3 matrix?
    Https://amazingmarvin.com/ has a matrix feature. Source: over 1 year ago
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What are some alternatives?

When comparing NumPy and Amazing Marvin, 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.

Todoist - Todoist is a to-do list that helps you get organized, at work and in life.

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

Things - Things is an easy to use task manager.

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

Remember The Milk - Remember The Milk is a task and time management application for mobile devices.