Top 10 of the best tools to use AI without knowing how to code – LeBigData.fr

Do you want to use Machine Learning and AI in your business or for a project, but you do not have the expertise of a Data Scientist or an engineer? Discover the top 10 best tools to create machine learning and artificial intelligence applications without computer code.

Artificial intelligence and machine learning are opening up new possibilities for businesses in all industries. However, these technologies require the expertise of Data Scientists and other specialists with programming knowledge.

However, on a global scale, there is a real shortage of such experts. Fortunately, to facilitate the adoption of AI in business, several technology giants offer open source platforms and tools making it possible to exploit this innovation without expertise in computer code. Here is a selection of ten such tools.

TeachableMachine

The Teachable Machine is a web-based tool. From a simple browser, the user can create Machine Learning models accessible to all.

He just feed the computer with examples to allow him to learn. These examples can be files, or live captures. Once downloaded, the examples are categorized into images or audio.

The models can then be tested instantly to check if the new examples have been correctly classified. Thus, it is possible to teach models to classify images, sounds or even body postures.

What-If-Tool

The What-If Tool stands out above all for its ease of use. User can easily run two models on same data set to compare differences via visualization features.

The data points can be edited as desired adding or removing features. Finally, it is possible to perform a test before putting the model into production.

Another strong point of this tool is the use of confusion matrices and ROC curves to determine the accuracy of the models.

Google AI Platform

The Google AI Platform is Google’s artificial intelligence platform. It is distinguished by its affordable price and ease of use.

With this solution, Data Scientists can easily bring their ideas to life through an integrated tool chain for running a Machine Learning application.

This platform is compatible with Kubeflow, Google’s open source platform. This allows the user to design portable pipelines that can be run on Google Cloud or on premises.

The data is first stored on the Cloud or on BigQuerythen tagged to classify them in different categories: images, videos, audio, text…

The data can then be imported to train a model. A Machine Learning application can then be created on the Google Cloud Platform (GCP). It supports different machine learning frameworks using a virtual machine deep learning image. The AI ​​Platform and GCP Console make it easy to manage models.

Data Robot

With Data Robots, you can create AI projects in minutes instead of several months. This solution allows you to use predictive models without needing the expertise of a Data Scientist.

The tool offers access to various open source Machine Learning models. You will thus be able to obtain models whose accuracy will depend on the data available.

Thus, a company is able to take advantage of predictive models without the need to develop its own set of proprietary models. In addition, this platform offers a balance between machine learning and human experience to solve predictive modeling problems.

RapidMiner Studio

The RapidMiner Studio offers you a very intuitive “drag and drop” interface. After collecting all available data, the platform will choose from a collection of over 1500 algorithms to determine the best model.

The company’s databases, data warehouses and social networks are quickly connected to allow the user to share data with anyone who needs it.

When the model is ready, the tool explains why it is the best choice and what benefits it will bring to the business. Additionally, visualizations make it easy to explain the workflow to anyone inside or outside the company.

Accelerite ShareInsights by Amazon Web Services

Offered by AWS, ShareInsights is a tool for design ETL pipelines (extraction, transformation, loading) of data without the need for computer code.

A drag and drop interface allows you to easily create the pipeline based on the various Amazon Cloud services. Cloud-native technologies like Glue and Arena can be leveraged to create interactive dashboards in minutes.

A data analytics platform for S3 and Redshift is also offered, as well as automated service selection and hit management features for AWS serverless services. There are also functions for data preparation, OLAP and Machine Learning.

Create ML By Apple

Create ML is a very easy to use application. It allows the user to ddeploy machine learning modelswithout the need for technical knowledge in Machine Learning.

The user can visualize the model creation workflow in real time. It can also develop its own models for object detection, activity or sound classification.

Many models can be trained using different data sets simultaneously. Models can then be tested before being deployed. The application is designed to work without a dedicated server. He is possible to improve performance using an external GPU.

Microsoft Azure Automated Machine Learning

Microsoft Azure cloud-based automated machine learning tool enables companies to deploy machine learning models much faster.

Its user interface does not require codingand the tool automatically deploys predictive models using existing data filtered by algorithms and hyperparameters.

Inconsistencies and errors in the data are automatically detected and rectified. This saves time and avoids erroneous results. Thanks to a detailed visualization, it is possible to make a comparison between two models and their respective performances.

BigML

The main advantage of BigML is that it can be exported to any local server or can be deployed instantly as a real-time application.

Thanks to the “Partial Dependence Plots”, users benefit from a clear and intuitive interface allowing to have a good understanding of predictive models.

Its easy-to-use web interface and REST API provide immediate access to users. Additionally, the tool is available in multi-user version, and in cloud or on-site version.

Google ML Kit

Creating Machine Learning applications on mobile is possible. Google ML Kit is a software development kit available on iOS and Android operating systems for smartphones and tablets.

This tool makes it easy to add machine learning functions to an application, without the need for machine learning or programming expertise.

Among the features offered are, for example, text recognition, face detection, landscape identification or barcode scanning. The APIs also make it possible to use TensorFlow Lite models on the smartphone app.

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Top 10 of the best tools to use AI without knowing how to code – LeBigData.fr


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