Machine Learning 2: Machine Learning Solutions

There are two ways machine intelligence can be part of your applications.

As a Service:

Machine intelligence requires three ingredients: computing power, algorithms, and data. If you’re new to business, i would suggest not to invest in researching these topics or building a team, instead focus on application development using machine intelligence API from companies like Microsoft, IBM, Google, Amazon, and others.

Example: Azure Cognitive Services, Amazon Translate, Amazon Polly,
Amazon Lex, etc.

Find the detailed comparison for Machine Learning as a Service here.

https://www.altexsoft.com/blog/datascience/comparing-machine-learning-as-a-service-amazon-microsoft-azure-google-cloud-ai-ibm-watson/

Custom Solution:

Real business problems are complex and solutions for those can’t be achieved using machine intelligence as a service. In this case, build your own machine learning solutions. Though machine learning frameworks and sdks are available in almost all programming language, But I’d recommend python, JavaScript, and .Net due the support from open source communities. These are some important platforms where you can deploy your solutions:

Azure Machine Learning and Azure ML Studio

Amazon SageMaker

IBM Watson Machine Learning

Google Cloud Machine Learning