Machine Learning is not rocket science! But it may appear like it for smaller inexperienced companies that are not familiar with the demands and requirements of a machine learning model. But for these companies, Cloud Computing comes to the rescue. In fact, most companies these days use some sort of cloud computing web services to use Machine Learning for a fee so that they can focus on their core business and not spend many finances on cultivating their own machine learning infrastructure from scratch.
There are many cloud computing platforms that provide these web services for machine learning. The most popular of these are Amazon Web Services, Microsoft Azure, Google Cloud, and IBM Cloud. These are the oldest and most mature platforms that provide various products for Machine Learning ranging from natural language processing, service bots, and even deep learning. So in this article, we will check out all these cloud computing platforms. But before that, let’s see why cloud computing has become so important in machine learning these days.
Why is Cloud Computing Important in Machine Learning?
Machine Learning is the most in technology in these times. Naturally, all companies these days want to use Machine Learning to improve their business. Machine Learning and Data Analytics are used by companies to better understand their target audience, automate some of their production, create better products according to market demand, etc. All of these things in return increase the profitability of a company which in turn gives them an edge over their competitors. After all, the bottom line in most cases is profit!
However, for a long time in the past, companies needed to invest a lot of money in Machine Learning to get this profit. Machine Learning required a lot of infrastructures, programmers who were familiar with ML, and data analytics were expensive and there was very little data available to feed these machine learning algorithms! While this was not that big a deal for large multinational corporations, it was very difficult for small and mid-level companies. But the popularity and advancement of cloud services have made everything much easier. Now companies can access Machine Learning algorithms and technologies from a third-party vendor, made a few changes according to their custom requirements are start getting the benefits with a much smaller initial investment.
This is why Cloud Computing is so important in Machine Learning! This is the solution for many smaller and mid-level companies that don’t want to build, test, and implement their own machine learning algorithms from scratch. These companies can focus on their core business and obtain value addition from Machine Learning without needing to become experts. So they get increasing profits while decreasing their risk of investment which means it’s a win-win situation for all!
What are the Cloud Computing platforms for Machine Learning?
As already specified, Amazon Web Services, Microsoft Azure, Google Cloud, and IBM Cloud are the most popular Cloud Computing platforms for Machine Learning. Now let’s check them out in detail:
1. Amazon Web Services
Amazon Web Services is a cloud computing platform that is a subsidiary of Amazon. It was launched in 2006 is currently one of the most popular cloud computing platforms for machine learning. AWS provides various products for Machine Learning like:
- Amazon SageMaker – This is used to create and train machine learning models
- Amazon Augmented AI – This is used to implement a human review of the machine learning models
- Amazon Forecast – This uses machine learning to increase the forecast accuracy
- Amazon Translate – This uses machine learning and natural language processing for language translation
- Amazon Personalize – This creates personal recommendations in machine learning systems
- AWS Deep Learning AMI’s – This is used for Deep Learning solutions
- Amazon Polly – This is used to convert text into life-like speech
2. Microsoft Azure
Microsoft Azure is a cloud computing platform created by Microsoft. It was initially released in 2010 and is a popular cloud computing platform for machine learning and data analytics. Some of the Microsoft Azure products for machine learning are:
- Microsoft Azure Cognitive Service – This provides smart cognitive services for applications.
- Microsoft Azure Azure Databricks – This provides Apache Spark-based analytics
- Microsoft Azure Bot Service – This provides smart and intelligent bot services that can be scaled
- Microsoft Azure Cognitive Search – This is a Machine Learning based service for mobile and web applications
- Microsoft Azure Machine Learning – This is used to create and deploy machine learning models on the cloud
3. Google Cloud
The Google Cloud Platform is a cloud computing platform that is provided by Google. It was launched in 2008 and it provides the same infrastructure for companies that Google also uses in its internal products. Google Cloud provides various products for machine learning such as:
- Google Cloud AutoML – This is used for training an AutoML machine learning model and its development
- Google Cloud AI Platform – This is used for creating, training, and managing ML models
- Google Cloud Speech-to-Text – This is a speech recognition system for transmitting from speech to text and it supports 120 languages.
- Google Cloud Vision AI – This is used to create machine learning models for cloud vision that detect text, etc.
- Google Cloud Text-to-Speech – This is a speech creation system for transmitting from text to speech
- Google Cloud Natural Language – This is for natural language processing for analyzing and classifying text
4. IBM Cloud
The IBM Cloud Platform is a cloud computing platform offered by IBM. It provides various cloud delivery models that are public, private, and hybrid models. IBM Cloud provides various products for machine learning such as:
- IBM Watson Studio – This is used to build machine learning and artificial intelligence models as well as preparing and analyzing data
- IBM Watson Speech-to-Text – This is a speech recognition system for converting speech and audio into written text
- IBM Watson Text-to-Speech – This is a speech creation system for converting text into natural-sounding audio
- IBM Watson Natural Language Understanding – This is for natural language processing for analyzing and classifying text
- IBM Watson Visual Recognition – This uses machine learning to search visual images and classify them
- IBM Watson Assistant – This is used for creating and managing virtual assistants
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