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Piktochart VS Scikit-learn

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

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Piktochart logo Piktochart

Piktochart for Business Storytelling

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Piktochart Landing page
    Landing page //
    2022-11-10

Piktochart is an infographic tool to help you present your presentations, pitches, proposals, data visualizations, charts, timelines, structure, process related visuals and diagrams in a compelling way.

  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Piktochart features and specs

  • Maps
    Chloropleth

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.

Piktochart videos

+ Add

Review: Using Piktochart in the Classroom (great for Infographics!)

More videos:

  • Review - Canva vs. Piktochart
  • Tutorial - Piktochart Tutorial: A Simple Guide to Piktochart for Beginners

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

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

Category Popularity

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

Piktochart

Scikit-learn

Design Tools
100 100%
Design Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Graphic Design Software
100 100%
Graphic Design Software
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Piktochart and Scikit-learn. 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 Piktochart and Scikit-learn

Piktochart Reviews

The Top 10 Alternatives to Marq in 2024
While each of these design tools offers unique features and benefits, Piktochart stands out for its AI-powered capabilities and ease of use. Whether you're a business, educator, or marketer, Piktochart can help you transform complex data into visually appealing content effortlessly. If you're looking for a reliable alternative that combines advanced features with...
Source: piktochart.com

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

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Piktochart. It has been mentiond 31 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.

Piktochart mentions (4)

  • 9 Best Tools to Make Infographics in 2023
    Piktochart: Piktochart is another powerful tool for infographic creation, offering a range of customizable templates and easy-to-use design features. It provides an intuitive interface for adding charts, maps, icons, and more. - Source: dev.to / over 1 year ago
  • Ask HN: Who is hiring? (October 2021)
    Frontend Tech Lead, Senior Frontend Developer | Remote in Europe | 4-day work week SaaS |Visual communications app https://piktochart.com/ Here's a little information about our culture. - Source: Hacker News / over 3 years ago
  • Content & Community- A Cheatsheet for Open Source projects. ( Part 1: Content 🎨)
    Picktochart - Data visualizations are always helpful when you're trying to communicate certain aspects of product usage in relation to something else. - Source: dev.to / about 4 years ago
  • Bugs‌ ‌found‌ ‌in‌ Piktochart SaaS. ‌Bug‌ ‌Crawl‌
    Piktochart is a graphic design platform helping brands deliver visually appealing content. With Piktochart, one can create beautiful infographics, on-point presentations, as well as easily digestible reports. Source: about 4 years ago

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 / 3 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 / 11 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
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What are some alternatives?

When comparing Piktochart and Scikit-learn, you can also consider the following products

Canva - Canva is a graphic-design platform with a drag-and-drop interface to create print or visual content while providing templates, images, and fonts. Canva makes graphic design more straightforward and accessible regardless of skill level.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

PicMonkey - PicMonkey is a feature-rich online photo editor that works right in your browser; no downloads...

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

Marq - Marq (formerly Lucidpress) is a web-based design and layout application that enables anyone to create beautiful creatives

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

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