Know about these 10-machine learning-as-a-service providers

Machine learning as a service or MLaaS is a set of cloud services that machine learning providers can offer as a part of cloud computing services. The services that MLaaS offers include face recognition, application programming interface (APIs), data visualization, predictive analytics, deep learning, and natural language processing. The unique feature of this application is that users can get started with a machine learning system without any need to install software or provision the servers. With the help of MLaaS, the infrastructural concerns such as model training, model evaluation, data pre-processing, and predictions can be alleviated. Here are the top 10 machine learning-as-a-service providers to know in 2021.

1 Microsoft Azure Machine Learning Studio

Microsoft Azure provides machine learning services for all sizes. It is suitable for all artificial intelligence and data scientist beginners and experts supporting a collection of a framework, databases, programming languages, operating systems, and services. The platform also helps with cross-device experience with support for all major mobile platforms.

2 AWS Machine Learning

Amazon Web Services has a high level of automation that is helpful for beginners. It helps businesses to build machine learning models without writing the code. It makes machine learning obtainable to developers without going through a learning process of ML algorithms and technology. The AWS ML services are based on the pay-as-you-go pricing model.

3 IBM Watson Machine Learning

WML runs on IBM's Bluemix, even the developers and data scientists can use the WML to get themselves trained. WWL is created to answer the questions of deployment, operationalization, and deriving business values from ML models. WML also skits visual modeling tools that help users to gain understanding, quickly identify patterns, and make faster decisions.

4 Google Cloud Machine Learning

Google's scope of Software-as-a-Service is nearly endless. Google's cloud machine learning is based on TensorFlow, this ML engine is integrated with all other Google's services such as Google Cloud Storage, Google BigQuery, and Google Cloud Dataflow.

5 BigML

BigML is easy and flexible to use and deploy services. Many features are integrated into BigML that allow importing data from Google Drive, Microsoft Azure, Google Storage, and AWS. It is also helpful in clustering algorithms and visualizations.

6 Domino

Domino assists in the latest data analysis workflow. It supports Python, R, MATLAB, Julia, Shell Scripts, and Perl languages. Data science managers, IT executives, data scientists, and leaders can use this platform and gain knowledge management with all the projects that are searchable and stored.

7 HPE Haven

Using Haven machine learning solutions extract, analyze, and index multiple data formats such as video, audio, or email. That includes attributes like face detection, speech recognition, media analysis, object recognition, image classification, speech recognition, and scene change detection.

8 Arimo

Arimo can crunch massive amounts of data in seconds using large computing platforms and machine learning algorithms. It also can anticipate future actions by learning from past experiences. The service provider works upon time-series data to discover patterns of behavior that are based on deep learning.

9 Dataiku Data Science Studio

Dataiku supports programs such as R, Spark, Hive, Scala, Python, and Pig. It provides machine learning solutions such as H2O, MLlib, Scikit-Learn, Xgboost. It delivers, builds, explores, and prototypes data products efficiently.

10 MLJAR

MLJAR provides its services for development, prototyping, and deploying a pattern recognition algorithm. To start working with MLJAR, a user first needs to upload the dataset, after selecting the dataset there is a need to select input and target attributes.