Hello and welcome to AutoML, in which we talk about applications of AutoML technology for deep learning. This installment covers the available AutoML platform.

The author & edit | there are three

Since Google first announced AutoML, industry and academia have been quick to catch on, and over the years, what platforms are available for AutoML? Here are some of the most important ones. \

1 Google Cloud AutoML

As the proposal and early adoptor of AutoML, Google Cloud AutoML is the earliest and most mature AutoML system at present, covering three fields of image classification, text classification and machine translation. In addition, it also launched the beta version of video-related services, supporting transfer learning, model structure search and hyperparameter search.

Using vision as an example, when we want to use a service, there are only three steps:

(1) Upload pictures to Google Cloud Storage.

(2) Create a CSV file with images and corresponding labels.

(3) Format the dataset using AutoML Vision, and then train and deploy the model.

Cloud AutoML offers API calls and graphical interfaces, so if you want to try it out, try it yourself.

2 EasyDL

EasyDL is baidu’s AutoML platform. As the enterprise with the most abundant AI technology accumulation in China, Baidu is also in the field of AutoML. Currently, it contains classic version, professional version and retail version, supporting transfer learning and model structure search.

Supported task types include image classification, object detection, image segmentation, text classification, video classification, and sound classification. PaddlePaddle is dismal, but EasyDL has hope.

The usage process consists of four steps:

(1) Data uploading and data annotation

(2) Training task configuration and parameter tuning

(3) Evaluation of model effect

(4) Model deployment \

3 Aliyun PAI

Alibaba Cloud Machine Learning Platform PAI (Platform of Artificial Intelligence) is a machine learning service Platform launched by Alibaba. It contains three sub-products, namely, machine learning visual development tool PAI-Studio, cloud interactive code development tool Pai-DSW, Pai-eas, an online model service, provides a one-stop shop for data processing, model training, service deployment and prediction.

Business scope includes text classification, financial risk control, product recommendation and so on.

4 Azure Machine Learning

Azure Machine Learning is Microsoft’s AutoML platform, which supports model structure search and hyperparameter search.

Azure Machine Learning supports a number of deep Learning frameworks and is very easy to use in conjunction with Microsoft’s many development tools.

5. Some startups

In addition to large companies with strong research strength, many start-up companies also flood into the field of AutoML to develop relevant frameworks. The typical foreign representatives are H2O Driverless AI, R2. AI and so on.

The typical model in China is AI Prophet AutoML and so on. \

However, compared with Google and Baidu and other big manufacturers, the availability of tools and services are still a gap.

Some open source projects

There are many open source projects for AutoML, so here’s a quick summary for those interested to explore.

Github.com/tensorflow/…

Github.com/keras-team/…

Github.com/Tencent/Poc…

Github.com/automl/auto…

Github.com/h2oai/h2o-3…

For more information, check out this GitHub project.

Github.com/hibayesian/…

conclusion

AutoML is one of the most advanced machine learning/deep learning technologies that will further reduce the cost of designing models manually. There are many solutions available, but they are not yet commercially available on a large scale.

Next: AutoML and model structure search.

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