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Scikit-learn VS Kissflow

Compare Scikit-learn VS Kissflow and see what are their differences

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Contents:
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  3. » Reviews
  4. » Alternatives

Scikit-learn logo Scikit-learn

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

Kissflow logo Kissflow

Kissflow is a workflow tool & business process workflow management software to automate your workflow process. Rated #1 cloud workflow software in Google Apps Marketplace.
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Kissflow Landing page
    Landing page //
    2023-08-28

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

Kissflow features and specs

  • User-Friendly Interface
    Kissflow offers an intuitive, drag-and-drop interface that is easy for users of all skill levels to navigate and use, reducing the learning curve and need for extensive training.
  • Versatile Workflow Automation
    It supports the automation of a wide range of workflows, from simple approval processes to complex, multi-step operations, enhancing productivity and efficiency.
  • Integration Capabilities
    Kissflow integrates seamlessly with a variety of other tools and platforms such as Google Workspace and Microsoft Office 365, allowing for a more streamlined work environment.
  • Customizable Templates
    The platform provides many customizable templates, helping users quickly set up processes tailored to their specific needs, thereby saving time.
  • Mobile Accessibility
    Kissflow offers mobile applications that enable users to manage and monitor workflows on the go, ensuring that important tasks are not delayed.
  • Scalability
    The platform can scale with your business, making it suitable for companies of all sizes, from small businesses to large enterprises.

Possible disadvantages of Kissflow

  • Pricing Structure
    The pricing can be relatively high, especially for smaller businesses or startups, and may not offer the best value for money for all types of users.
  • Limited Customization Beyond Templates
    While customizable templates are available, the platform may not offer sufficient flexibility for highly specialized or bespoke workflows.
  • Complexity in Advanced Features
    Some users may find the advanced features complex and difficult to configure without significant technical knowledge, potentially necessitating specialist help.
  • Support Limitations
    Customer support may sometimes be slow or inadequate, which can be frustrating when dealing with urgent issues or technical difficulties.
  • Performance Issues
    Users have reported occasional performance issues such as lagging or slow loading times, which can hinder productivity.
  • Limited Analytics
    Analytics and reporting features may not be as robust as those offered by some other workflow management tools, limiting insights into process performance.

Analysis of Scikit-learn

Overall verdict

  • Yes, Scikit-learn is generally regarded as a good library for machine learning, especially for beginners and intermediate users who need reliable tools with efficient implementation of numerous algorithms.

Why this product is good

  • Scikit-learn is considered a good machine learning library because it provides a wide range of state-of-the-art algorithms for supervised and unsupervised learning. It is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. The library is well-documented, easy to use, and has a consistent API that simplifies the integration of different algorithms. Furthermore, there's a strong community and continuous development, which means it is well-maintained and updated regularly with new features and improvements.

Recommended for

  • Beginners learning machine learning concepts and application.
  • Data scientists and engineers looking for a robust and efficient toolkit to build and deploy machine learning models.
  • Researchers who need an easy-to-use library that facilitates the experimentation of various algorithms.
  • Developers who require a seamless, Python-based machine learning library that integrates well with other data analysis tools and environments.

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Kissflow videos

+ Add

Getting Started and Review of Kissflow - Automating Your Business Processes

More videos:

  • Review - Kissflow Product Spotlight
  • Demo - KiSSFLOW Demo

Category Popularity

0-100% (relative to Scikit-learn and Kissflow)

Scikit-learn

Kissflow

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Workflow Automation
0 0%
Workflow Automation
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Project Management
0 0%
Project Management
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Scikit-learn and Kissflow

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...
Source: searchbusinessanalytics.techtarget.com

Kissflow Reviews

Kissflow and Pneumatic: Data Centric vs Process Centric BPM
When all is said and done, Kissflow really delivers if you already have a business process in place that relies on paper forms and you want to digitize it. The downside is, of course, that at the end of the day you simply get a digitized version of the exact same process with all the same limitations and caveats. Kissflow isn’t really conducive to improvising new business...
Source: www.pneumatic.app
Top 9 Procurement Tools for SMBs (2024)
Do you want to have control over the procure-to-pay process but with sufficient flexibility? Kissflow lets you have that with its simple and customizable solution. For purchase requisitions, it offers fluid forms so that you can collect, approve and track the purchase requests.
Source: geekflare.com
Top 9 MuleSoft Alternatives & Competitors in 2024
Kissflow, one of the best MuleSoft competitors, is a powerful IT process automation tool that empowers your team to streamline IT operations, enhance efficiency, and drive innovation within your organization. Automating workflows, simplifying task management, and providing valuable insights enable your team to focus on essential tasks and improve productivity.
Source: www.zluri.com
10 Best Procurement Management Software Tools in 2023
Kissflow prides itself on being both simple and customizable. Use this platform to track purchase requests, automatically generate purchase orders, and approve invoices on the go in the mobile app.
Source: clickup.com
Top Workflow Management Systems on the Market
In terms of workflow management, Kissflow ticks all the boxes and offers agile management as a bonus. The only downside is that Kissflow deliberately aims for a bit of a “walled-garden” experience with regard to users: there is no support for guest users or external user interaction as of the time of this writing.
Source: www.pneumatic.app

Social recommendations and mentions

Based on our record, Scikit-learn seems to be a lot more popular than Kissflow. While we know about 31 links to Scikit-learn, we've tracked only 1 mention of Kissflow. 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.

Scikit-learn mentions (31)

  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 12 months ago
  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / about 1 year ago
  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / almost 2 years ago
View more

Kissflow mentions (1)

  • Bugs‌ ‌found‌ ‌in‌ Kissflow SaaS. Bug‌ ‌Crawl‌
    Kissflow is a well-rounded tool that bridges workflow & business process management in a single operating environment. This platform takes out the pain of work tracking by introducing tools and functions that simplify much of the work through automation. Source: about 4 years ago

What are some alternatives?

When comparing Scikit-learn and Kissflow, 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.

Pipefy - Pipefy is a process management software that empowers anyone to create and automate efficient workflows on their own without code.

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

Process Street - Create beautiful rich process documents in a simple to follow checklist format. Fast, free and incredibly simple to use.

NumPy - NumPy is the fundamental package for scientific computing with Python

Nintex - Cloud-based digital workflow management automation platform

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