If you just include "machine learning" in your pitch you can add a zero on to the end of your valuation. Machine Learning (ML) and the Internet of Things (IoT) have been huge buzzwords in the past few years, much of which has been hype and much of which reflects their profound potential. The above quote came somewhat jokingly from an investor, but it has some truth to it too. Given the hype around machine learning and IoT and the broad range of application to which they can be brought to bear, it can be difficult to cut through the noise and understand where the actual value lies. In this post, I'll explain how machine learning can be valuable for IoT, when it's appropriate to use, and some machine learning applications and use cases currently out in the world today.

One of the most watched developments in data analytics and business technology these days is that of machine learning. Becoming something of a business-critical technology, machine learning makes computing processes more efficient, cost-effective, and reliable and may ultimately accelerate every aspect of business decision-making. Machine learning has applications in most industries, where it presents a great opportunity to improve upon existing processes. Yet many organizations are slow on the uptake. Recent surveys report that fewer than 25% of businesses have adopted any significant level of machine learning automation; yet it is currently behind some of the most game-changing advancements at Google, PayPal, Netflix, and other industry giants. Where data analytics is easily the jet plane of data processing, machine learning could be considered a rocket ship, providing a means to quickly and automatically produce models that analyze larger volumes of highly complex data and deliver results faster and with more accuracy.

One of the most watched developments in data analytics and business technology these days is that of machine learning. Becoming something of a business-critical technology, machine learning makes computing processes more efficient, cost-effective, and reliable and may ultimately accelerate every aspect of business decision-making. Machine learning has applications in most industries, where it presents a great opportunity to improve upon existing processes. Yet many organizations are slow on the uptake. Recent surveys report that fewer than 25% of businesses have adopted any significant level of machine learning automation; yet it is currently behind some of the most game-changing advancements at Google, PayPal, Netflix, and other industry giants.

This chapter is adapted from the Ultimate Guide to Getting Started in IoT -- A free eBook written by Leverege. With all the hype around machine learning, many organizations are asking if there should be machine learning applications in their business somehow. In the vast majority of cases, the answer is a resounding no. One of the major benefits of the cloud is that it enables you to leverage virtually infinite storage and processing power to gain critical insights from the data your sensors/devices will be collecting. Both data analytics and machine learning can be powerful tools in doing so, but there's often confusion on what they actually mean and when is best to use one or the other.

If you just include "machine learning" in your pitch you can add a zero on to the end of your valuation. Machine Learning (ML) and the Internet of Things (IoT) are huge buzzwords right now, and they're both near the peak of the hype cycle. The above quote came somewhat jokingly from an investor, but it has some truth to it too. Given all the hype and buzz around machine learning and IoT, it can be difficult to cut through the noise and understand where the actual value lies. In this week's #askIoT post, I'll explain how machine learning can be valuable for IoT, when it's appropriate to use, and some machine learning applications and use cases currently out in the world today.

If you just include "machine learning" in your pitch you can add a zero on to the end of your valuation. Machine Learning (ML) and the Internet of Things (IoT) are huge buzzwords right now, and they're both near the peak of the hype cycle. The above quote came somewhat jokingly from an investor, but it has some truth to it too. Gartner's 2016 Hype Cycle for Emerging Technologies -- Machine Learning is at the very peak of the hype cycle, with IoT Platform and other related IoT technologies on the up-slope. Given all the hype and buzz around machine learning and IoT, it can be difficult to cut through the noise and understand where the actual value lies.

Machine Learning (ML) and the Internet of Things (IoT) are huge buzzwords right now, and they're both near the peak of the hype cycle. The above quote came somewhat jokingly from an investor, but it has some truth to it too. Given all the hype and buzz around machine learning and IoT, it can be difficult to cut through the noise and understand where the actual value lies. In this week's #askIoT post, I'll explain how machine learning can be valuable for IoT, when it's appropriate to use, and some applications and use cases currently out in the world today. And if you're new to these topics, you might want to get up to speed on Machine Learning and the Internet of Things before we dive in!

What are some of the applications and use cases? Machine Learning (ML) and the Internet of Things (IoT) are huge buzzwords right now, and they're both near the peak of the hype cycle. The above quote came somewhat jokingly from an investor, but it has some truth to it too. Given all the hype and buzz around machine learning and IoT, it can be difficult to cut through the noise and understand where the actual value lies. In this week's #askIoT post, I'll explain how machine learning can be valuable for IoT, when it's appropriate to use, and some applications and use cases currently out in the world today.