Artificial intelligence is not a thing of the past anywhere, it is the future now and its applications have been in circulation and are being used constantly. It is shaping our automotive industry, the internet is a less complicated place and new developments are being carried out by the digital enterprises who rely heavily on the working of Artificial Intelligence. Many people around the world are using the applications of artificial intelligence at a constant rate but they get their version of AI pre-made or pre-ordered. Developers and creators need a more subtle approach that can help them with their on-going projects and create a lively medium which they can use to make their work a little bit easier.
If you are one of such creators or developers then you already know the importance of having a great AI-based tool at your side, the following is a list of top five best AI tools that you can try for your own projects;
- Amazon Web services
Amazon web services are singlehandedly the most complex and far-fetched network when it comes to taking care of the IT-related tasks. It has so many tools, applications, and useful links integrated into one complete system that the users can use. You can have any AI-based tool for your business and have your developers and designers working on it at an elevated pace. Many digital businesses even a few startups only choose AWS solutions for their day to day AI needs.
The first thing that makes AWS such a vibrant choice is the overall customization that it is willing to bring on the table. You can customize the tools that you want to use and add them into a specific category, pay for what you use, and skip the rest. Other than that it is extremely cost-effective, you are only charged for the services that you use and it also helps you to cut down on the in-house facilities that you have at your disposals such as data centers and management teams. Other than that the processing power/boost that you get with AWS is immense.
Don't have that latest operating system to work out the magic with deep learning and machine learning? Don't worry AWS has got you covered, increase/decrease the number of cores, speed of the RAM, or GPU intensive workload according to the requirements of your projects. AWS already comes with plenty of AI toolkits for developers such as the AWS Rekognition utilizes AI to incorporate image interpretation and facial recognition into the apps being created which is a great overall approach, to begin with for the development of the biometric systems.
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- Google Cloud ML engine
It is almost a universal AI model for every developer and AI enthusiast to go to. The basic working of this tool involves teaching other machines various learning models so they can take on various complex tasks. It can help applications with training in predictive skills and is extremely suitable for deep learning. All of these tasks can either be implemented separately or simultaneously.
Accuracy of the predictions with the AI models can also be improved extremely with the help of this tool such as configuring a hyperparameter that determines the accuracy of the predictions. If this function is not available to a developer then they would have to determine and test various values and then at the end make a final run for the values that showed desired results, which is a long and hefty process. But it can be cut short with the help of a Google cloud ML engine by your side. A set of python-based tool is used to create them, but the main value of this software is ready-made predictive models. These will allow you to get the result of the predictions in two ways which are online and batch forecasting.
- Apple’s core ML
If you are currently working on applications that are meant to be released on the OS systems then you surely need the works of Apple's core ML program. It allows the integration of machine learning models into your applications that are created for the iOS systems. In simpler words, it is a machine learning tool that allows you to perform fast real-time forecasting.
The working of this tool is also extremely straightforward as it brings into account the use of a machine learning model that is pre-trained in the cloud, can be converted rather easily into Core ML format, and directly added into your project without further integration and processing requirements. If you are creating applications for the iOS or other related devices that run on a similar app interface then this is the best framework for you to work with. It supports the use of other technologies that will be extremely useful when creating applications for iOS systems.
It helps in the preparation of speech recognition, name recognition, and game development models where solutions are arbitrary and need to be perceived by the thought process of the user which brings into account the use of complex algorithm systems. These systems are already provided by Apple’s core ML framework for you.
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- Azure machine learning studio
All the impossible tasks of training and creating artificial intelligence systems at one platform can become a reality with the help of Azure machine learning studio. Developers get access to a large number of algorithm based libraries that can be modified, customized, and adapted to the specific needs of the users. You can work on the development of the algorithm online as it doesn't require any specific operating systems or tools, to begin with. Models created or worked on with the help of this tool can be released on the internet for the sake of receiving new insightful data from the end-users.
For the sake of improving the cognitive algorithms and transforming the cause of artificial intelligence, developers can have access to various distinctive API systems. Following are some of the features provided by this amazing AI-based tool;
- Drag and Drop function
- Datasets
- Modules
- Trained Models
- Experiments
- Experiment Conversion
- Web Service Publishing
- APIs
Data required for the building of application and software systems must be of high quality and suitable for subsequent analysis. Therefore the availability of the above-mentioned features and tools would be enough for working on complex AI-based applications, worrying about their integration and deploying them to reach a much larger audience.
Read more: How to become an AI engineer?
- OPENNN
Open neural network library is a software-based library written in C++ which implements a neural network which is the main area of deep learning research. It is an open-source library which means that anyone can have access to this tool and they can integrate it according to their own requirements. With the help of this tool, you will be able to implement the neural networks that are usually characterized by high performance and deep architecture.
There is always going to be a more diverse number of tools targeting AI and ML but nothing would be as compatible and driven as OPENNN library as it provides access to some of the most sophisticated neural networks developed and tested by the professionals who are at the top of their game.
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