Software Alternatives, Accelerators & Startups
Register | Login

NumPy VS Freshservice

Compare NumPy VS Freshservice and see what are their differences

EcholoN
Holistic service management: service, support + customer care. From Ticketing to Helpdesk, Service Desk, ITSM to Enterprise Service Management, Service Technician and Field Service Management (FSM)... featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Freshservice logo Freshservice

Freshservice: the one-stop cloud solution for all your IT management needs.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Freshservice Homepage
    Homepage //
    2024-05-06

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Freshservice features and specs

  • User-friendly Interface
    Freshservice offers an intuitive and clean interface that makes navigation simple for users of all skill levels.
  • Robust Automation
    Allows for workflow automation that can save time on repetitive tasks, increasing efficiency.
  • Customizable
    Highly customizable to adapt to the unique needs of various organizations, including custom workflows and ticket fields.
  • Strong Integrations
    Integrates seamlessly with a wide range of third-party applications, enhancing its functionality.
  • Comprehensive Reporting
    Provides detailed reports and analytics that help track performance and identify areas for improvement.
  • Asset Management
    Includes IT asset management features to track and manage hardware and software assets efficiently.
  • Scalability
    Scalable to meet the needs of both small businesses and large enterprises.

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

NumPy videos

+ Add

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

Freshservice videos

+ Add

Freshservice - A Quick Overview

More videos:

  • Demo - Freshservice Demo
  • Demo - Freshservice - End user demo
  • Review - Freshservice Review 2020: Great Overall SASS for IT
  • Review - Freshservice vs SysAid: Why I switched from SysAid to Freshservice
  • Review - Freshservice vs Jira Service Management: Which ITSM is for You
  • Review - Freshservice Review - Pros and Cons Revealed
  • Tutorial - Freshservice Tutorial 2024: How To Use Freshservice (Step-By-Step)

Category Popularity

0-100% (relative to NumPy and Freshservice)

NumPy

Freshservice

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Project Management
0 0%
Project Management
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
IT Management
0 0%
IT Management
100% 100

User comments

Share your experience with using NumPy and Freshservice. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

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

Freshservice Reviews

12 Best Asset Management Software For IT Teams In 2023
Freshservice is one of the leading IT asset management platforms (ITAMs) in the world. The ITAM helps CTOs keep their IT assets under control, such as hardware and software, including fixed assets like vehicles and machines
Source: thectoclub.com
20 Best IT Asset Management Software in 2023: ITAM Tools and Solutions
Freshservice is an ITSM and ITAM software that provides asset discovery and inventory, software and hardware tracking, and license management capabilities. Its cloud-based platform is easy to use and offers real-time visibility into asset usage and costs. Freshservice also offers automation features, including automated asset discovery and tracking, to help organizations...
Source: infraon.io
29 Best Alternatives to Dapulse (Now Monday.com)
Freshservice is a web-based application that focuses on IT service management. The software is specifically designed to help IT teams improve the way they perform every task that they might need to perform in the process of project management.
Source: www.proofhub.com

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Freshservice. While we know about 119 links to NumPy, we've tracked only 3 mentions of Freshservice. 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 (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 8 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 10 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
View more

Freshservice mentions (3)

  • Outlook Helpdesk Form
    If you're fine with writing emails instead of filling in an Outlook form (as a user), then https://freshservice.com/ might work. Source: over 3 years ago
  • Low Hanging Fruit - Recommendations for Ticketing System????
    FreshService is pretty good and ticks all the boxes you're looking for (https://freshservice.com/). Source: over 3 years ago
  • SchoolDude as a help desk / ticketing system.
    If you're not capable of hosting the solution yourself, there are solutions that have per-agent models that will cost you much less than SchoolDude, all while being substantially more feature rich. osTicket and FreshService are both great examples. A cloud hosted instance of osTicket is only $9/agent/month. FreshService is a more polished solution, but costs more at $19/agent/month. Source: about 4 years ago

What are some alternatives?

When comparing NumPy and Freshservice, 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.

Asana - Asana project management is an effort to re-imagine how we work together, through modern productivity software. Fast and versatile, Asana helps individuals and groups get more done.

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

Basecamp - A simple and elegant project management system.

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

Redmine - Flexible project management web application

Loading...