How Machine Learning and cloud is entwined with each other?

Cloud Computing and Machine Learning

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How Cloud Computing and Machine Learning is entwined with each other?

Cloud Computing and Machine Learning, both are quite effective in their own way but when they entwined with each other, the resultant benefits astonish us for sure. Regardless of size, every business around the globe strives to adopt these technologies to leverage their ROI. In this article, you will understand why it is a nonpareil combo for tech industry. 

What is Machine Learning? – The Quick Intro 

There is an interesting correlation between humans and machine learning technology. Yes! We have inbuilt brain and ML technology have algorithms. We naturally use our memory and past experiences to make decisions. Similarly, Machine learning uses past data and insights to take decisions.  

In machine learning, there is no need to deploy the pre-defined program every time, ML itself modifies the algorithms depending upon the data ingested. The more the data, the more precise the result will be. It is categorized into four types as 

  • Supervised 
  • Unsupervised 
  • Semi-supervised 
  • Reinforcement 

What is Cloud Computing? 

Cloud computing is the obvious term for many. The very specific usage of cloud is to store all  kind of data which does not occupies any space in your computer hardware and not even requires software installation. Everything is accessible via internet; you just need to log in and fetch the data you want. It is quite a vast domain. Businesses can pick up the features and services entirely based upon their needs and requirements. Cloud Services are broadly classified as 

  • Infrastructure as a Service (IaaS) 
  • Platform as a Service (PaaS) 
  • Software as a Service (SaaS) 

The Reason Behind the Binding of Two Giant Technologies 

Thus, Machine learning promotes extraordinary intelligence and cloud provides abundant storage along with security. Perfect, right? Machine learning generates algorithms purely based upon the data provided. Multiple machine learning algorithms like Gradient Boosting algorithms, Logistic Regression, SVM, Decision Tree, Linear Regression, Naïve Bayes, K-Means, random forest, etc., occupies wide space and consumes heavy computational power. Data scientists and ML engineers struggles a lot with this. Cloud comes as a rescuer and let them work without worrying about the computational power and storage. This combination is also called as intelligent cloud. 

Adding additional servers and managing computational power manually is such a heavy task for ML professions. With cloud, one can add any number of servers based upon the need. 

 Key Benefits 

  • Cloud uses “Pay-as-you-go” model for billing. This comes an added advantage for ML; thus, they only have to pay for the storage and computational power used. 
  •  It promotes flexibility, one can add additional servers if required based upon the requirements. 

Top Cloud computing platforms for Machine Learning 

There are so many cloud solutions providers are available over the globe. Yet some of the big sharks in this domain are AWS, Azure, Google, IBM, Alibaba. Each provides specific features and tools exclusively for machine learning. To retain their users and to rely with the trend they keep on working with enhancing the provided features. Let’s have a look at them.

#1 Amazon Web Services (AWS) 

 AWS is the most popular and commonly used cloud computing platform which is commenced in the year 2006. They provide the below services for machine learning. 

 Amazon SageMaker: it facilitates developing and practicing machine learning models 

Amazon Forecast: It aids in improving ML models’ forecast accuracy. 

Amazon Translate: In NLP and ML, it is used to translate languages. 

Amazon Personalize: In the ML system, it generates various personalized recommendations. 

Amazon Polly: It is employed to convert text to speech 

AWS Deep Learning AMI’s: The main purpose of this solution is to address ML issues related to deep learning. 

Amazon Augmented AI: In ML models, human review is implemented. 

#2 Microsoft Azure 

 Azure is founded by the tech giant Microsoft in the year 2010. It is very popular among data scientists and ML professionals. Some of the services available for ML are listed below 

 Azure Cognitive Service: It enables you to offer sophisticated cognitive services for ML applications. 

Azure Bot Service:  The main objective of this solution is to develop intelligent and clever bot services for ML applications. 

Azure Databricks: This service offers Apache Spark based analytics 

Azure Cognitive Search: It is used in building web and mobile applications for machine learning 

Azure Cognitive Search: It is in charge of cloud-based deployment of ML models. 

 #3 Google Cloud 

 Google does not require any introduction. it started google cloud services in the year 2008. here is the list of services offered for machine learning  

 Google Cloud Vision AI: With the help of this solution, vision detection features like image labelling, text identification, face detection, tagging, etc. may be simply integrated into machine learning applications. 

Google Cloud AI Platform: It aids in the creation, management, and sampling of machine learning models. 

Google Cloud Text-to-Speech: This solution transmits text format into speech format. 

Google Cloud Speech-to-Text: It converts the voices into the text format. 

Google Cloud AutoML: It helps out to train and generate automatic machine learning models. 

Google Cloud Natural Language:  It is used in Natural Language Processing to classify and analyze the text. 

#4 IBM Cloud 

IBM has started the IBM Cloud in the year 2011. Let’s have a look at the solutions provided for machine learning. 

IBM Studio: It is used to develop and run Machine learning models 

IBM Natural Language Understanding: It helps to analyze the text in natural language processing 

IBM Speech-to-Text: Which is used to convert the speech to the text format 

IBM Assistant: It is a kind of personal virtual assistant useful for multiple purpose 

IBM Visual Recognition: It helps out in identifying visual images and analyze them 

IBM Text-to-Speech: It is used to transform text format to speech.

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Top Applications of Machine Learning Algorithms with Cloud. 

 Cognitive Computing: 

 Cognitive computing is the perfect combination of machine learning and cloud. It is a self-learning cloud designed to perform like human without any human intervention. It adopts various Machine Learning algorithms like pattern recognition, neutral networks, data mining, etc,  

 Business Intelligence: 

 The prominent focus of Business Intelligence is to take efficient business decisions for the growth of the organization.  It uses various formats of data and processes them to take decisions. 

 Internet Of Things: 

The Internet of Things (IoT) is a platform that provides cloud services, including online data processing and storage. The popularity of cloud-based ML models has recently increased. It begins by requesting input data from the client end, using cloud servers to execute machine learning algorithms utilizing artificial neural networks (ANN), and then sends back output to the client. In this situation, the server may hold sensitive client data, posing privacy concerns and discouraging consumers from using the services. 

 Virtual Personal Assistant: 

The perfect example for virtual assistant is google assistant, there it recognizes and analyze speech format as well as text format and provides highly personalized experience to each user based upon the data stored. 

 AI -as-a-Service: 

 When used in the cloud, open-source AI features are considerably less expensive. These services offer AI and machine learning capabilities, enhancing the system’s intelligence by increasing the capacity for cognitive calculations. It contributes to the system being quite quick and effective. 

Conclusion 

Machine learning and cloud computing are hopefully the finest technologies for the future. The demand in the tech world and the mass adoption of these technologies will upgrade it to the next level.  

Who We Are? 

We ContinuumInnovations, strives to bring innovations in the cloud technology. We always follow up the foot print of the trends and latest technologies to serve the best to our clients. Our proficient cloud engineers provide the best out of the best solutions to the clients’ requirements.   

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