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machine-learning in Python VS Appian

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

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machine-learning in Python logo machine-learning in Python

Do you want to do machine learning using Python, but youโ€™re having trouble getting started? In this post, you will complete your first machine learning project using Python.

Appian logo Appian

See how Appian, leading provider of modern low-code and BPM software solutions, has helped transform the businesses of over 3.5 million users worldwide.
  • machine-learning in Python Landing page
    Landing page //
    2020-01-13
  • Appian Landing page
    Landing page //
    2023-10-20

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.

Appian features and specs

  • Low-Code Development
    Appian allows users to create applications with minimal hand-coding, catering to business analysts and developers alike. Its drag-and-drop interface simplifies development and accelerates time-to-market.
  • Process Automation
    Appian excels in automating complex business processes, improving operational efficiency, and reducing human error. Its powerful BPM tools streamline workflows effectively.
  • Integration Capabilities
    Appian provides strong integration capabilities with various third-party systems, databases, and cloud services. This ensures that applications can seamlessly communicate with existing enterprise systems.
  • Enterprise-Grade Security
    Appian offers robust security features, including role-based access control and data encryption, making it suitable for businesses with stringent security requirements.
  • Scalability
    As a cloud-native platform, Appian is highly scalable, supporting the needs of growing enterprises by easily handling increased loads and more complex applications.
  • User Experience
    The platform provides a user-friendly interface, both for developers building the applications and end-users interacting with them, enhancing overall user satisfaction.

Possible disadvantages of Appian

  • Cost
    Appian can be expensive, particularly for small to medium-sized businesses. Its pricing model might not be feasible for organizations operating on a limited budget.
  • Learning Curve
    Although it simplifies development, mastering Appian still requires a learning curve. Users need to invest time in training, which can slow down the initial development phase.
  • Complex Customization
    Highly tailored or very specific customizations can be challenging to implement within Appian. Some complicated functionalities may require extensive workarounds.
  • Limited Offline Functionality
    Appian's offline capabilities are limited, which can be a disadvantage for field services or users who need to access the application without a reliable internet connection.
  • Vendor Lock-In
    Due to its proprietary technology, organizations may face vendor lock-in, making it challenging to migrate applications or data to another platform if needed.
  • Performance Issues at Scale
    While Appian is scalable, some users report performance issues when running extremely large and complex applications, which can impact user experience and overall efficiency.

machine-learning in Python videos

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Appian videos

Appian CEO: Delivering โ€˜Mission-Criticalโ€™ Software | Mad Money | CNBC

More videos:

  • Review - This is Appian
  • Review - Appian Application Designer: Build Applications in Days, not Years

Category Popularity

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Data Science And Machine Learning
BPM
0 0%
100% 100
Data Dashboard
100 100%
0% 0
Workflow Automation
0 0%
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 machine-learning in Python and Appian

machine-learning in Python Reviews

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Appian Reviews

Top 10 Microsoft Power Apps Alternatives and Competitors 2024
Strengths: A powerful low-code platform, Appian caters to large enterprises with complex business process automation needs. It offers robust workflow management capabilities, allowing you to automate intricate business processes with decision-making logic and case management features. Appian excels in industries like finance, insurance, and healthcare, where complex...
Source: medium.com
7 Best Business Process Management Tools (2023)
Appian is used by companies to automate their routine tasks, integrate with other enterprise tools, and create custom workflows. It offers a wide range of features such as mobile app development, chatbots, AI assistants, etc.
11 Business Process Management (BPM) Software for SMBs
Experience the power of business workflow automation with Appian and accelerate your business governance, results, and efficiency. Appian simplifies your workflow design to empower users and pro developers to draw processes, such as a flowchart.
Source: geekflare.com
10 Best Low-Code Development Platforms in 2020
Verdict: Appian is the provider of the software development platform. The Appian low code development platform is a combination of intelligent automation and low-code development.
Best Google App Maker alternatives in 2020
Appian excels when used to create form-based apps. The product does allow building custom UI components, but only by using Appianโ€™s in-product customization tools. Appianโ€™s reasoning for this is security and to ensure JS compliance across browsers and devices.
Source: retool.com

Social recommendations and mentions

Appian might be a bit more popular than machine-learning in Python. We know about 7 links to it since March 2021 and only 7 links to machine-learning in Python. 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.

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 wonโ€™t make you hireable unless youโ€™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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Appian mentions (7)

  • AI Coding Adoption at Enterprise Scale Is Harder Than Anyone Admits
    AI coding adoption at enterprise scale is hard because the real project is not installing a tool. It is redesigning trust, review, ownership, and delivery discipline around a new source of code generation. That's where platforms like Retool, ToolJet, Appian, etc. shine. - Source: dev.to / 5 months ago
  • Enterprise App Builders That Are Actually Enterprise-Ready (Top 5)
    You are process-heavy and regulated, and your app is basically a workflow engine: Appian. - Source: dev.to / 5 months ago
  • Low-Code tools & Frontend
    Does any of you use a low-code tool like Retool or Appian? If so, what is the most common use case? Source: over 3 years ago
  • Appian Associate Developer Certification help
    Look for use case inspiration in the Solutions area of appian.com and within the AppMarket. See if you can build proof of concepts of some of these. Source: almost 4 years ago
  • What is best way to create an online responsive database driven website to help manage my small orchard?
    There are low code database driven website creation systems out there at the moment e.g. OutSystems and Appian however they have very limited free trials (e.g. auto-disable after a few days of no use), and then the paid options are again too expensive. Although I will note that they seem to be great in terms of their usability and would be perfect for creating a simple interface without too much diving into code. Source: about 4 years ago
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What are some alternatives?

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

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

Camunda - The Universal Process Orchestrator

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

Kintone - Build business apps and supercharge your company's productivity with kintone's all-in-one...

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

Bizagi - Bizagi is a Business Process Management (BPMS) solution for faster and flexible process automation. It's powerful yet intuitive BPM Suite is designed to make your business more agile.