Artificial intelligence (AI) is fast becoming the go-to technology for digital transformation, enhancing customer experience and reducing operational costs across industries. And while most developers of AI will never have to build an AI platform, there are advantages to curating an integrated stack of tools and repositories for building, deploying, and securing your applications of AI—whether you’re doing it for an organization or for yourself. Thanks to open-source tools, you don’t need a degree in computer science or any prior experience developing AI applications to put together a model that you can run on your laptop.
Reasons to Choose Open-Source Tools for Building AI
In a sea of possibilities, collaboration among a diverse, global community lifts everyone’s boat. There are a growing number of tools available for building AI, and the open-source community offers a rich and diverse ecosystem of tools, techniques, and repositories that you can leverage to do it. This is the power of open source: It combines the individual’s expertise and innovation with the community’s power in numbers. There are many reasons to choose open-source tools for building AI over proprietary tools, which are owned by the individual or the company who published them:
- Open-source tools are often more flexible and easily integrated with other solutions than proprietary tools. With proprietary tools, only the owners can modify the code.
- Using open-source tools can help you avoid vendor lock-in, as you don’t have to worry about moving files from one cloud platform to another.
- Open-source tools typically have significantly lower upfront costs than proprietary tools. Keep in mind that with open source, you may need professional help navigating the maintenance and security aspects of your AI tech stack; Anaconda’s professional services offerings exemplify options for organizations that require enterprise support.
- Using open-source tools built and maintained by a community applies the power of the crowd when it comes to both troubleshooting and fostering innovation.
Enterprise AI platform providers like Google Cloud Platform (GCP) and Amazon Web Services (AWS) have embedded open-source technologies in their solutions because open source allows users to access the best tools available for their use cases and unique business requirements.
3 Open-Source Tools for Building AI
Tool 1: Anaconda
Anaconda originated the use of Python for data science back in 2012. Anaconda’s platform offers one-stop access to open-source packages, code repositories, and models that are shared with the community. Anaconda’s cloud notebooks make it easy for individual users to share and collaborate with other users. Anaconda is a cross-language platform that is interoperable with all of the tools featured in this article. Practitioners use Anaconda to build, deploy, and secure Python solutions faster.
Today, Anaconda has 35 million users who share their models, tools, and code repositories inside the platform. Users and organizations build and maintain the ~7,500 open-source packages Anaconda’s platform makes available. To learn more about what users and organizations are building with Anaconda, check out the maker’s series on the Anaconda blog.
Tool 2a: PyTorch
PyTorch is one of the most popular open-source machine learning frameworks. It is used by researchers and developers worldwide to create cutting-edge models for a variety of tasks, including natural language processing (NLP), computer vision, and time-series prediction.
PyTorch offers many advantages over other frameworks, such as its easy-to-use API, its flexibility, and its ability to scale to large data sets. PyTorch also supports a number of advanced features, such as dynamic graphs and automatic differentiation.
Tool 2b: TensorFlow/Keras
TensorFlow is a machine learning tool that helps create production-grade machine learning models. TensorFlow can be used for a variety of tasks, including data preprocessing, training models, and debugging. Whether it’s on servers, edge devices, or the web, TensorFlow allows you to train and deploy your models easily, no matter what language or platform you use.
You can use Keras, a high-level neural networks API that allows for fast prototyping and experimentation, directly with TensorFlow via tf.keras. Keras allows you to quickly create models with just a few lines of code. It also provides clear and actionable feedback during the training process so you can easily identify problems and correct them. Keras is a great choice if you want to get up and running with deep learning quickly.
Tool 3: 🤗Transformers
🤗Transformers is an open-source library built by Hugging Face on top of PyTorch and TensorFlow. It provides a consistent API to easily download and train state-of-the-art pretrained models for a variety of tasks including NLP, computer vision, audio, and multimodal.
Combined, all of these open-source tools provide a virtual platform for building, training, deploying, and securing your applications that use machine learning or deep learning.
Get Support From the Open-Source Community As You Build AI
If you’re new to AI development, you may be wondering how to get started and where to find support. Good news: There’s a thriving open-source community that can help you every step of the way! Here are some tips as you get started:
1. Join an online forum, mailing list, or Discord community related to your area of interest; this is a great way to ask questions, get advice, and connect with other developers.
2. Attend a local meetup or conference related to AI development; this is a great way to network and learn from more experienced developers.
3. Check out resources from some of the best tools and providers in the industry, including GitHub, Stack Overflow, HuggingFace, and Kaggle. These resources can help you find valuable building blocks: code examples, tutorials, and collaboration tools.
Most importantly, just get started! Great AI solutions are built with creative ideas and a variety of top-notch tools. You can get started with Anaconda today by simply creating your free account.
Learn More About Anaconda for Developing AI
Anaconda is powered by the open-source community, giving you access to more than 35 million tool builders and maintainers, model makers, and user-practitioners. To learn more about how you can use Anaconda to build, deploy, and secure Python solutions faster, schedule a demo today.