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AnyChart VS machine-learning in Python

Compare AnyChart VS machine-learning in Python and see what are their differences

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AnyChart logo AnyChart

Award-winning JavaScript charting library & Qlik Sense extensions from a global leader in data visualization! Loved by thousands of happy customers, including over 75% of Fortune 500 companies & over half of the top 1000 software vendors worldwide.

machine-learning in Python logo machine-learning in Python

Do you want to do machine learning using Python, but you’re having trouble getting started? In this post, you will complete your first machine learning project using Python.
  • AnyChart Home Page of AnyChart JS Charts
    Home Page of AnyChart JS Charts //
    2025-03-10

Founded in 2003, AnyChart is one of the global leaders in interactive data visualization, offering award-winning, flexible JavaScript (HTML5) charting libraries with numerous chart types and features, great API & documentation, and enterprise-grade support.

Cross-browser JS charts and graphs, maps, stock charts, and Gantt charts powered by AnyChart have helped thousands of companies including industry leaders — from startups to corporate giants such as AT&T, Bosch, BP, Citi, ExxonMobil, Lockheed Martin, Merck, Novartis, Oracle, Reuters, Samsung, Tencent, UBS, Volkswagen, Yahoo, 3M & many others — gain better insight, make right decisions, and improve their enterprise performance based on robust, insightful data visualization.

Whether you need to enhance your website with better reporting, embed dashboards into your on-premises and SaaS systems, or build an entirely new product, AnyChart covers all your data visualization needs. The company's products include massive out-of-the-box capabilities, combined with flexibility & simplicity.

Loved by thousands of happy customers, including more than 75% of Fortune 500 companies across all industries and over half of the top 1,000 software vendors worldwide.

In 2019, AnyChart launched a technology alliance partnership with Qlik, adding three new product extensions for Qlik Sense. The partnership enables the Qlik community to be provided with more than 30 new chart types and many valuable features natively in the Qlik environment.

  • machine-learning in Python Landing page
    Landing page //
    2020-01-13

AnyChart

Website
anychart.com
Pricing URL
Official AnyChart Pricing
$ Details
freemium $49 / One-off (Next Unicorn license for startups)
Platforms
JavaScript Web Qlik Windows Mac OSX Linux Android iOS TypeScript PHP Google Chrome Safari Opera Firefox Java iPhone Mobile Laravel ReactJS React Native Angular Python Node JS Cross Platform
Release Date
2003 May
Startup details
Country
United States
State
Florida
City
St. Augustine
Founder(s)
Anton Baranchuk
Employees
10 - 19
Edit details

machine-learning in Python

Website
machinelearningmastery.com
Pricing URL
-
$ Details
-
Platforms
-
Release Date
-
Edit details

AnyChart features and specs

  • Chart types
    70+ (bar, line, Gantt, candlestick, waterfall, sunburst...)
  • Data formats
    Multiple (JavaScript API, XML, JSON, CSV, HTML table, Google Sheets...)
  • Integrations
    Seamlessly runs with any language, framework, and database (multiple integration templates are available)
  • Docs
    The documentation and API reference are very detailed and everything is explained in detail in a simple and clear way, with numerous readymade chart samples
  • Browser support
    Supports all browsers, including IE6+ along with mobile browsers
  • Dependencies
    None
  • Product history
    AnyChart has been operating from 2003 and the team is very experienced with a long history of releasing high-quality products.
  • Open source
    The open source code is hosted on GitHub under different licenses depending on the library
  • Flexibility
    Extremely flexible and customizable Any part of a chart can be changed and customized.
  • Interactivity
    Events can be distributed to chart elements which respond to user actions. Event listeners are simple JavaScript functions which are very easy to use and understand

machine-learning in Python features and specs

  • Ease of Use
    Python has a simple and clean syntax, which makes it accessible for beginners and efficient for experienced developers to implement fundamental concepts of machine learning quickly.
  • Rich Ecosystem
    Python boasts a vast collection of libraries and frameworks such as scikit-learn, TensorFlow, and PyTorch that provide extensive functionalities for machine learning tasks.
  • Community Support
    Python has a large and active community that contributes to continuous improvement, support, and readily available resources like tutorials, forums, and documentation for troubleshooting.
  • Integration Capabilities
    Python can easily integrate with other languages and technologies, enabling seamless deployment of machine learning models in diverse environments.
  • Visualization Tools
    Python supports various visualization libraries like Matplotlib and Seaborn which are crucial for data analysis and understanding the performance of machine learning models.

Possible disadvantages of machine-learning in Python

  • Performance Limitations
    Python is an interpreted language and can be slower compared to compiled languages like C++ or Java, which might be a consideration for performance-intensive tasks.
  • Global Interpreter Lock (GIL)
    The GIL in Python can be a bottleneck for multi-threaded applications, limiting parallel execution and performance in CPU-bound machine learning tasks.
  • Dependency Management
    Managing dependencies can be complex in Python projects, especially when handling different versions of libraries required for specific machine learning projects.
  • Memory Consumption
    Python can require more memory for large datasets when compared with more memory-efficient languages, which might affect scalability and the ability to process very large datasets.

AnyChart videos

+ Add

Heatmap Chart using AnyChart with Python

More videos:

  • Tutorial - Creating Interactive Charts with AnyChart library for Your Android App
  • Tutorial - How to Create a Gantt Chart in Qlik Sense using AnyGantt Extension by AnyChart

machine-learning in Python videos

No machine-learning in Python videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to AnyChart and machine-learning in Python)

AnyChart

machine-learning in Python

Data Dashboard
92 92%
Data Dashboard
8% 8
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Charting Libraries
100 100%
Charting Libraries
0% 0
Data Visualization
100 100%
Data Visualization
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare AnyChart and machine-learning in Python

AnyChart Reviews

  1. alairedeforest
    Fast, effective charts

    Probably the best JS chart library on the market right now.

    Competitors: CanvasJS
    Pros:    Extremely simple|Fast|Affordable
    Cons:    Not free
15 JavaScript Libraries for Creating Beautiful Charts
AnyChart is a lightweight and robust JavaScript charting library with charts designed to be embedded and integrated. AnyChart allows you to display 68 charts out-of-the-box and provides features to create your own chart types. You can save a chart as an image in PDF, PNG, JPG or SVG format.
Source: www.sitepoint.com
Top 10 Visual Analytics Provider For 2021
AnyChart provides products for those who are slightly well-versed with HTML and JavaScript. Their products provide robust JavaScript charting libraries with APIs, documentation, and enterprise-grade support. Developers can integrate a variety of charts into their mobile, desktops, or web products. Their component is compatible with any database and runs on any platform....
Source: analyticsindiamag.com
Top 10 JavaScript Charting Libraries for Every Data Visualization Need
AnyChart is a robust, lightweight and feature-rich JS chart library with rendering in SVG/VML. It actually gives web developers a great opportunity to create any different charts that will help to make decisions based on what is seen.
Source: hackernoon.com

machine-learning in Python Reviews

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Social recommendations and mentions

Based on our record, machine-learning in Python seems to be more popular. It has been mentiond 7 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.

AnyChart mentions (0)

We have not tracked any mentions of AnyChart yet. Tracking of AnyChart recommendations started around Mar 2021.

machine-learning in Python mentions (7)

  • Data science and cybersecurity with python project
    After that you should probably look at some very basic ML tutorials. I just googled it, I have no idea if this is good https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: over 3 years ago
  • Ask HN: How can I learn ML in 6 months as a teenager?
    Few different approaches based on search engine 'ml with python': Work though use cases / examples : https://www.databricks.com/resources/ebook/big-book-of-machine-learning-use-cases On-line class(es) / step by step projects: * https://bootcamp-sl.discover.online.purdue.edu/ai-machine-learning-certification-course * https://www.w3schools.com/python/python_ml_getting_started.asp *... - Source: Hacker News / over 3 years ago
  • Are these CS courses enough CS knowledge for ML engineer?
    MLE: ALL OF THE ABOVE (this is important - pure machine learning skills generally won’t make you hireable unless you’re doing a PhD and/or are a genius) Plus: 1. https://machinelearningmastery.com/machine-learning-in-python-step-by-step/ 2. https://www.coursera.org/learn/machine-learning 3. https://www.3blue1brown.com/topics/neural-networks. Source: over 4 years ago
  • how to do i train an AI
    Have you seen this? https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: over 4 years ago
  • Python Data Science Project Ideas (+References)
    Machine learning models Fine-tune existing machine learning models for improved accuracy, or create your own custom models. - Source: dev.to / over 4 years ago
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What are some alternatives?

When comparing AnyChart and machine-learning in Python, you can also consider the following products

Chart.js - Easy, object oriented client side graphs for designers and developers.

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

Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application

BigML - BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.

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