As the demand for machine learning and artificial intelligence continues to increase, leading technology giants are aware of the need to give developers access to tools to build and deploy models. From an industrial perspective, there are not enough skilled programmers and data scientists in the industry to develop these systems. Tech giants are now opening up their platforms and development tools to lower the barriers to entry into AI/ML.
In this article, we have listed 5 tools that can access ML and AI:
Lobe: Lobe is an easy-to-use visualization mechanism that allows users to build custom deep learning models, train them in time, and send them immediately in the application the user needs without writing any code.
Users can start by dragging the training example folder on the desktop. Lobe automatically builds custom deep learning models for its users and starts training. Users can export the trained model and send it directly in their application.
The tool also allows users to use audio files, which enables them to create tools such as music visualization tools, but the company hopes to extend support for voice and allow the creation of generated images.
Google AutoML
Google’s sophisticated machine learning solution is Cloud AutoML, which is a point-and-click method to generate machine learning models without any coding background. Google provides a neural network that can be pre-trained through the API and can complete certain tasks, but this is only useful when you need to use the model specifically. The essence of Cloud AutoML is that almost anyone can bring image catalogs, import tags for images, and create operational machine learning models based on this.
Google does all the complex operations behind the scenes, so customers don’t need to know anything about the complexity of neural network design. AutoML uses a simple graphical interface that allows users to drag image collections. Then, the platform needs to know how to represent these images. Google has indeed played its charm, and the user finally got a model running in the cloud that can recognize the specified course in the photo.
Speaking of AI, Google’s AIY Projects (AIY Projects), the full name is Artificial Intelligence Yourself, which means to create your artificial intelligence by hand. The project was launched by Google in 2017, and the goal is to allow every Maker (maker) to DIY its own AI products. Google launched two sets of kits, Voice Kit and Vision Kit, represented by the project in May and December respectively.
Voice Kit uses Google assistant to add voice control to your Raspberry Pi, while Vision Kit turns on image recognition and introduces neural networks to makers. It can detect thousands of common objects, but it can also detect your facial expressions and show your emotions, such as anger, happiness, etc.
According to reports, Google AIY series development kits have set up an exclusive distributor in Hong Kong. Interested makers and developers can pay attention to the Gravitylink Store. The price is the same as the official one.
Data Robot
The tool is able to automate machine learning and transform machine learning and AI projects in minutes or days instead of months without hiring and mentoring data science teams, resulting in world-class modeling capabilities that are coming.
The tool uses traditional methods to develop and deploy predictive models without any previous programming knowledge. It provides many cutting-edge open source machine learning prototypes to discover the most realistic user data models.
This feature puts data science and predictive modeling within the scope of the organization and helps them implement ML at scale. In addition, the tool can also be used for predictive modeling problems, providing the best combination of machine learning and human experience.
Orange (available in Anaconda)
Orange is a program developed for GUI-based workflow mining and analysis. This means that users do not need to have any programming knowledge, nor do they need to use Orange and mine data, test data and gain insights. Users can complete tasks ranging from main visual objects to data management, conversion and data mining.
It combines all the functions of the entire process into one workflow. The best feature of Orange is that it supports wonderful visual effects. Users can try silhouettes, heat maps, geographic maps and various visualizations.
KNIME
Konstanz Information Mining (KNIME) is an open source data analysis, reporting and integration program that combines various parts of machine learning and data mining through its modular data pipeline concept.
JDBC's graphical user interface and applications enable the combination of nodes to mix different data sources, including preprocessing, for modeling, data analysis and visualization, without or with minimal programming. To some extent, the advanced analysis tool KNIME can also be seen as an alternative to SAS.