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A machine learning and AI guide for enterprises in the cloud

AI and machine learning could drive the next wave of cloud adoption. But businesses need to know their provider options and advance their skills to succeed with these technologies.

Introduction

AI technologies, including machine learning, give enterprises more insight into their data, streamline IT management tasks and provide a number of other benefits. Machine learning achieves these benefits by finding patterns in enterprise data sets and predicting possible outcomes -- all without the need for human intervention, which frees up admins for other tasks.

Machine learning and AI services from major public cloud providers, such as Amazon Web Services (AWS), Azure and Google, make these technologies more accessible to enterprises. But before jumping in, organizations need to ensure that they have the necessary IT skill sets, carefully evaluate their service options and then implement them effectively.

Use this guide to tackle some of those challenges and to get started with machine learning and AI cloud services in your organization.

1Adoption trends-

Cloud AI services emerge in the enterprise

On-premises machine learning and AI implementations can be costly and complex. These technologies require lots of storage and computing power to analyze large amounts of data. Enterprises might need to purchase more hardware and software, as well as pay for more maintenance in their data center. New public cloud services can reduce some of this complexity and cost and make machine learning and AI more readily available to modern enterprises. Even still, some organizations struggle to realize exactly how they can or should apply these technologies.

Feature

Public cloud providers, users set their sights on AI

The public cloud has become a popular destination for AI deployment and experimentation, enabling enterprises to test machine learning algorithms and other technologies more easily than they could on premises. Continue Reading

Tip

Machine learning implementations take to the cloud

Public cloud providers offer their own flavor of machine learning services that are simpler and, in some cases, more cost-effective than on-premises alternatives. Still, it's best not to rush a deployment. Continue Reading

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Enterprises seek real-world machine learning use cases

The public cloud might facilitate enterprise access to machine learning services, but some business and IT teams still question exactly how and when to use the technology. Continue Reading

2Training options-

Advance your machine learning and AI skills

As enterprise adoption rises, IT pros need to update their skill sets and seek training for machine learning and AI in the cloud. Some admins might need to rethink their management processes, and some CIOs will struggle to identify the right business problems for machine learning to solve. Top public cloud providers offer training programs and certifications for their respective platforms, as well as foundational knowledge. There are also vendor-neutral training options from third-party vendors and universities.

Tip

Cloud admins prepare for machine learning, AI technology

Major cloud providers and third-party vendors see the need for more education related to machine learning and AI. Strengthen your skills with some of these training options. Continue Reading

Tip

Add machine learning skills to your IT resume

Alongside containers and vendor-specific skills, machine learning expertise is one of the hottest items a cloud admin can add to a resume. Check out training options from universities such as Harvard, Princeton and others. Continue Reading

Video

Machine learning adoption puts CIOs to the test

While machine learning can bring many benefits to an enterprise, there are still obstacles to overcome. CIOs face numerous challenges, such as finding the right algorithms and evolving their data science skills. Continue Reading

Feature

How AI challenges application development teams

To build an AI application, developers need to expand into new disciplines, such as deep learning and advanced mathematics. Here are three ways to prepare for app development in the age of AI. Continue Reading

3AI services in the cloud-

Navigate cloud service options for machine learning and AI

Major cloud providers are battling for the top spot in the machine learning and AI market. Offerings such as as Amazon Machine Learning, Microsoft Cognitive Services and Google Cloud Machine Learning continue to expand to lure in enterprises. Each platform delivers a different flavor of machine learning and AI to meet the unique needs of enterprises. Break down their key features to determine which best meets your goals.

Feature

Explore Google's cloud machine learning lineup

Review the six key features that work together to form Google's machine learning platform, including its language, speech and translation APIs. Continue Reading

Tip

Weigh the pros and cons of Amazon's machine learning service

While Amazon Machine Learning makes it easy for novices to get started with the technology, those with more advanced expertise could be left wanting more -- at least, for now. Continue Reading

Tip

Azure offers a robust suite of AI features -- at a price

Microsoft Cognitive Services has over two dozen AI features, but pricing and integration can become complex. Give the services a test drive to estimate costs before you commit. Continue Reading

Feature

Compare the top four cloud machine learning platforms

AWS, Azure, Google and IBM all have expansive machine learning offerings, but there are important differences to note. Take a closer look at each before you make a decision. Continue Reading

4Test your AI knowledge-

How much do you know about machine learning and AI?

Take this machine learning and AI quiz to assess how much you know about these two hot technologies.

Take this quiz

5Terminology-

Start your cloud AI journey with the right terms

Knowing the key terms related to a technology can go a long way. Build a strong foundation of knowledge with these basic machine learning and AI terms.

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