The market for AI technology is flourishing by leaps and bounds. The AI community is so strong, open and helpful that you can find the code, blog or library for almost anything. If not already done, now is the type to make use of AI solutions to meet your business needs.
To build AI solutions, you may have to use various capabilities like machine learning(ML), natural language processing(NLP), deep learning, speech and so on. Such projects require the perfect set of AI software development tools. The expertise of a custom software development company can be leveraged here to utilize these tools and work towards developing path-breaking products. Coming years it is expected that AI tools will play a major role in business.
H2O: H2O is an open-source machine learning and AI platform that permits developers to build and productionize machine learning models. The code can be written using different languages like Python, Java and R. These familiar languages help developers create mobile apps using predictive analysis and machine learning.
H2O comes with a set of supervised, unsupervised and other miscellaneous algorithms that users can utilize. H2O can easily integrate with the tools belonging to the Hadoop ecosystem including Spark. The financial, healthcare, insurance and many other industries use H2O to create ML models and gain better insights.
TensorFlow: TensorFlow is an open-source machine learning library that can be used by experts as well as newbies. TensorFlow can carry out various kinds of intuitive and language understanding. Newbies can just plug the blocks together to build new models. Experts can leverage the define-by-run interface for further analysis. TensorFlow helps to bring new understanding to existing problems and identify new problems that weren’t considered before.
It is one of the best machine learning tools available and developers can do a lot more with TensorFlow. TensorFlow allows APIs in almost all important languages. Since Keras is much easier to execute, you can apply TensorFlow in the backend without the need of being well-versed in it.
Microsoft Azure Machine learning Studio: The AI capabilities of Microsoft Azure is quite impressive. The Microsoft Azure AI platform is one of the most popular choices for AI development. It makes machine learning easier for businesses through advanced analytics. The Microsoft Azure Machine Learning Studio is a collaborative drag-and-drop machine learning tool.
This tool helps you to create, test and implement predictive analytics solutions on your data. You can drag-and-drop datasets and analysis modules, linking them together to launch an experiment. You can run this in the Machine Learning Studio without any programming.
Infosys NIA: Infosys NIA is an enterprise-grade AI platform that simplifies your AI adoption in business and IT. NIA offers best-in-class AI capabilities that empower your enterprise to deliver business value and ROI through data management across sources, use of computer vision to extract information from images or scanned documents and Natural Language Processing (NLP) to understand, interpret and analyze human language. The AI workbench simplifies the creation of machine learning and deep learning models.
NIA also features an ontology toolkit to capture and structure information into semantic representations. Other features include model operations, conversational AI, cognitive search and so on. NIA offers built-in AI solutions to accelerate the time-to-market and drive document digitization. These enterprise-grade features make NIA the preferred solution for enterprises.
IBM Watson: This is another platform that helps data scientists and developers build AI applications. Watson is a cognitive system that processes both structured and unstructured data at massive speed and scale. Watson is primarily an NLP tool that can understand language just like a human. IBM Watson provides tailored solutions for various industries like healthcare, advertising, IoT, media, law and so on.
Watson can identify new insights or patterns locked away in the information. It helps you build AI and machine learning models on any cloud. The pre-built Watson applications give you a faster time-to-value regardless of where you are on your AI journey. Watson APIs such as Watson Speech to Text, Watson Natural Language Understanding, Watson Personality Insights aim to empower your enterprise apps with AI capabilities.
As AI continues to make the world smarter and faster, businesses are looking for ways to put AI to work at scale. The above list of tools and frameworks can help you resolve business problems and be more productive. They enable you to enrich your customer interactions and make recommendations with confidence.
Before embarking on such projects, it is crucial to ensure that your team has the right set of AI and ML skills. Collaborating with a proficient software development team can put you at ease. Fingent’s team of experts can help you unleash the full potential of AI and reinvent your business. Contact us now to know more!
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Trending AI software development tools are transforming how developers build, train, and deploy AI models with greater efficiency and precision. Tools like TensorFlow and PyTorch lead the way for deep learning, while Google AutoML and IBM Watson Studio simplify the creation of machine learning models without extensive coding knowledge. OpenAI’s Codex, used in GitHub Copilot, is revolutionizing code generation by assisting developers in real time. Additionally, Jupyter Notebooks remain popular for interactive coding and data visualization. Just as GTPL Saathi simplifies managing broadband services, these AI tools make developing complex models more accessible, fostering innovation and speeding up AI deployment across industries.