As a developer, it can be difficult to keep up with the latest in technology. But with artificial intelligence (AI) becoming more and more prevalent in our lives, it's important to familiarize yourself with the tools that are available to you.

That's why we've compiled a list of the 10 best AI tools for developers. These tools are simple and easy to use and can help you become more proficient in AI development. So whether you're just starting out or you're looking for an upgrade, we have something for you.

In a gist, these are the tools. 

• Infosys Nia
• Google Cloud Platform
• AWS Machine Learning
• Microsoft Cognitive Services
• spaCy
• Rainbird
• Keras
• Wipro Holmes
• H20.ai
• Oracle Cloud Machine Learning

Infosys Nia

Infosys Nia is a cognitive computing platform that helps you automate the transformation of data into insights. It offers services in machine learning, natural language processing, and image recognition.

What I like about it is that it's really easy to use. You don't need any coding skills to get started, and there's a wide range of tutorials and support materials available online.

Plus, it's scalable so you can easily add more users or resources as your business grows.

Google Cloud Platform

Google Cloud Platform is a suite of cloud computing services offered by Google. It provides users with a range of tools to develop, deploy, and manage applications and websites.

One of the key benefits of using Google Cloud Platform is that it integrates seamlessly with other Google products and services. This makes it easy for developers to use and combine different services to create powerful applications.

AWS Machine Learning

The next AI tool we are discussing in this article is the AWS Machine Learning. This comprehensive cloud platform from Amazon Web Services gives developers access to a wide range of ML capabilities. It allows developers to build, deploy, and manage machine learning models with ease and flexibility.

The platform also enables them to use pre-built models or trained models to develop applications tailored to their needs.

Additionally, with its secure and resilient infrastructure, developers can quickly deploy machine learning solutions without worrying about server availability or downtime.

In a nutshell, AWS Machine Learning is an ideal choice for developers who are looking for an efficient and cost-effective way to create ML applications.

Microsoft Cognitive Services

Microsoft Cognitive Services is a powerful AI toolkit allowing developers to create applications with intelligent features such as facial recognition, object recognition, speech synthesis, and more. This toolkit simplifies the development process, allowing developers to quickly create applications with the power of AI.

With its easy-to-use API and wide range of supported languages, it's no wonder Microsoft Cognitive Services is becoming increasingly popular for developers looking to add smart features to their projects. Plus its Azure subscription plans make it attractive for teams of any size.

All in all, this powerful tool brings AI into the palm of your hands!

spaCy

spaCy is another great AI tool for developers looking to build natural language processing applications. It has a wide range of features for pre-processing, tokenizing, and parsing text, making it easy and fast to get the job done. Even better, spaCy can also be used to create custom entities and labels for specific use cases.

Overall, if you're looking for an AI tool that is simple and fast to use, spaCy could be the answer. It's great for prototyping applications quickly and provides detailed information on text analysis.

Plus, with its custom entity features, you can create sophisticated models in no time at all!

Rainbird

Rainbird is a cognitive automation platform that helps developers with decision-making processes. It has powerful features that let you model the decisions accurately, build machine learning models effortlessly, and enable users to control the outcomes.

Rainbird is easy to use and provides a real-time understanding of your decisions, helping you to make better judgments without getting overwhelmed.

You can also use Rainbird in various scenarios such as customer service automation, the credit assessment, fraud identification, and more. Best of all, it can be deployed both on and off-premises with ease.

If you’re looking for an AI tool for decision-making processes, consider giving Rainbird a try.

Keras

One of the most popular AI tools for developers is Keras. This open-source library makes it easy to develop and train deep-learning models. It supports multiple back-end engines and runs seamlessly on both CPU and GPU.

With its intuitive design, it allows developers to quickly prototype and build powerful neural networks using just a few lines of code.

Additionally, Keras is used by many major companies including Google, Netflix, Microsoft, and Amazon which makes it a great choice for any serious developer. 

With its wide array of advanced features combined with a simple-to-use interface, Keras is ideal for any AI project.

Wipro Holmes

Wipro Holmes is a comprehensive suite of AI applications which enables enterprises to build intelligent solutions. Wipro Holmes features use-case-driven, industry-ready AI solutions for various sectors such as healthcare, finance, retail etc.

It also provides APIs for developers to embed AI capabilities into their applications. The best part is that you can customize the API to your needs, making it super flexible and easy to use.

It’s a great tool if you’re looking to add AI capabilities to your application quickly and easily without having to build it yourself from scratch.

H2O.ai

H2O.ai is a fast, scalable, and open-source platform for deep learning, machine learning, and AI. 

It provides an artificial intelligence platform that enables businesses to easily build, deploy, and manage predictive analytical models – no matter the complexity of the data.

H2O.ai is particularly useful for developers looking to use a powerful yet accessible tool for machine learning and data analysis. 

The platform's graphical user interface allows users to interact with the algorithms and understand how they work in order to optimize their performance. 

Additionally, H2O is highly scalable and can be used for either small or large projects. Plus, its open-source nature gives developers access to tons of helpful resources from other users in the community.

Oracle Cloud Machine Learning

Our last AI tool for developers is Oracle Cloud Machine Learning (OCML). It provides all the sophisticated AI-powered capabilities you need to quickly, securely, and cost-effectively build and deploy AI models. 

With OCML, you can easily extend your existing Oracle Cloud applications without re-engineering them. You also get access to prebuilt models, automated data preparation, and integration with MLOps. 

Best of all, you can track your projects end-to-end with Oracle’s built-in governance and operations system. 

If you’re looking for a comprehensive AI platform that will help streamline your development process, OCML is a great choice.

Conclusion

So, there you have it: our top 10 picks for AI tools for developers. While this is by no means an exhaustive list, these tools should give you a good starting point for boosting your productivity and expanding your skillset. We hope you find them as useful as we have!

Special thanks to Rahul for creating this well-researched article, he is a Developer Advocate himself, and he loves to code, write blogs and build side projects

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