As the demand for machine learning and artificial intelligence goes up, leading tech giants realised the need to give developers access to tools to build and deploy models. From the industrial perspective, there aren’t enough skilled programmers and data scientists within the industry to develop these systems. Tech giants are now open sourcing their platforms and developer tools to lower the barrier for entry in AI/ML.
In this article, we list down 5 such tools that are making ML and AI accessible:
Lobe:Lobe is an easy-to-use visual mechanism that lets users to build custom deep learning models, promptly train them, and ship them immediately in a user desired app without writing any code. Users can begin by dragging in a folder of training examples from there desktop. Lobe automatically builds its users a custom deep learning model and starts training. User can export the trained model and ship it directly in their app.
The tool also lets users work with audio files, which empowers them to create tools like music visualizers, but that company hopes to extend support voice. And allows creating generative images.
Google’s solution for complex machine learning is Cloud AutoML, a point-and-click method for generating machine learning models without any coding background. Google offers pre-trained neural networks available through APIs that can accomplish certain tasks, but that’s only useful if you need specifically what that model does. The essence of Cloud AutoML is that almost anyone can bring a catalogue of images, import tags for the images, and create an operative machine learning model based on that. Google does all the complicated operations behind the scenes, so the client doesn’t require to comprehend anything about the complexities of neural network design. AutoML uses a simple graphical interface, enabling the user to drag in a collection of images. Then, the platform needs to know how to represent those images. Google does its charm, and users end up with a model running in the cloud that can recognise the specified courses in photos.
This tool is capable of producing world-class imminent modelling capabilities with automated machine learning, transforming machine learning and AI projects in minutes or days instead of months without having to hire and instruct a data science team. The tool develops and deploys predictive patterns employing traditional methods without any former programming knowledge. It provides numerous cutting-edge open source machine learning prototypes to discover the most authentic model for user data.
This feature brings data science and predictive modelling within the reach of organisations and helps them achieve ML at scale. Additionally, the tool can also be used for predictive modelling problems, providing the optimal combination of machine learning and human experience.
Orange is a program developed for mining and analysis on a GUI based workflow. This implies that users are not required to have any knowledge of programming and for using Orange and mine data, test numbers and obtain insights. Users can accomplish tasks ranging from primary visuals to data administrations, conversions, and data mining. It combines all the functions of the entire process into a single workflow. The best feature of Orange is that it supports wonderful visuals. Users can try silhouettes, heat-maps, geo-maps and all kinds of visualizations are possible.
Konstanz Information Miner(KNIME), is an open-source data analytics, reporting and integration program which combines various segments for machine learning and data mining through its modular data pipelining notion. A graphical user interface and application of JDBC enables assembly of nodes blending different data sources, including preprocessing, for modelling, data analysis and visualization without, or with only minimal, programming. To some degree an advanced analytics tool KNIME can also be considered as a SAS alternative.