Upcoming Trends in Machine Learning
Did you know that artificial intelligence and machine learning are quickly becoming the metrics of how well an organization will survive in the future? Well, now you do!
So, are you looking for ways to make a name for yourself in the quickly growing machine learning spaces? Your best chance to do it is by taking up online machine learning courses. Programs such as ML courses with certificates at IIT Allahabad will not only teach you the skills you need but will also expose you to the upcoming trends and tips in the industry.
So, are you waiting for your
online machine learning courses to commence but do not want to wait longer to get learning? Well, you’re in the right place since this article will walk you through some of the trends in machine learning that you need to be on the lookout for in 2021!
How Are Trends Predicted?
The first thing you will learn through
online learning courses is the way the machine learning community is going on right now. In fact, as a student of machine learning, you should know that the more the data and information, the better the prediction. Therefore, you need to know what the state of machine learning is now to know what the future trends look like.
Therefore, as an expert in machine learning, before you set down to predict upcoming trends, you need to know what the trends look like today and looked like a few years in the past.
Don’t worry, though; you will not be asked to conduct that market research yourself! Go through the next section, and you will find all the upcoming trends in machine learning.
Upcoming Machine Learning Trends to be Aware Of
Here is a quick list of the upcoming trends in machine learning:
- Automated Machine Learning (AutoML)
- Tiny Machine Learning
- Quantum Machine Learning
- The intersection of Machine Learning with the Internet of Things
- Hyper Automation
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Automated Machine Learning
The biggest roles that Automated Machine Learning will play in the near future are the automatic turning of neural net architectures and labeling data.
Low-cost countries such as South America, India, Central Eastern Europe, and South Africa provide human annotators who label data. The automatic Machine Learning trend will be based on those annotators to label data automatically. By doing so, most of the business outcomes will have fewer touchpoints, allowing each company to generate higher revenues.
Since automated machine learning will also automate the process of selecting and tuning neural network models, most AI solutions will become much cheaper. Therefore, the overall production cost of products will drop, which will cause either higher revenue generation for enterprises, or lower market costs if products are made available to the customers.
Most organizations restrict machine learning for huge hardware and projects. However, the technology has so much scope to grow in just about any market, regardless of the size and consumer base. Therefore, the trend of Tiny ML is bound to arise in a small duration.
Tiny Machine Learning is an approach that will develop Machine Learning that runs on hardware-driven devices to be available for software devices as well. Therefore, while ML till now works through microcontrollers for utility meters, powering cars, and refrigerators, Tiny ML will work for a localized analysis of simple commands such as gesture and voice commands.
Through this trend, sounds such as a crying baby, gunshot, environmental conditions, and measurement of vital signs will be identified by the devices Tiny Ml is integrated into.
Quantum machine learning is the best practice that will lead to powerful machine learning platforms along with more potent artificial intelligence. Even though quantum machine learning is more of an idea of the future, the beginnings of the idea would begin to show up in the near future.
Companies such as Amazon, IMB, and Microsoft have already taken the step forward by computing simulators and resources that are easily accessible through cloud systems.
By intersecting Machine Learning into quantum computing, the technological industry is set to reap unimaginable benefits. Therefore, they will be able to solve problems that are potentially unsolvable in the current time.
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The intersection of ML with IoT
The near future is set to see an intersection of the Internet of Things and Machine Learning. It only makes sense because IoT is the technology that connects things or devices across networks, and the way they communicate with one another.
When IoT and ML will come together, all the data collected with IoT will be computed through ML to generate meaningful results.
The best way to understand how this will work is by understanding how IoT works for the GPS tracking fleet management market. Since the GPS systems already collect a lot of data from vehicles, when all this data will go into an ML algorithm, organizations can automatically determine which vehicle should be deployed at what time, automating most of the fleet and trip management process in logistics.
Gartner identified the upcoming IT megatrend, which will come into the picture with the help of machine learning. What this means is that with the help of Artificial Intelligence and Machine Learning, just about anything can be automated.
The best part about this is that all this automation does not necessarily need any extensive devices and tools to run. As long as a software can live on anything, automation is possible! Imagine what the world will be like where machines can do just about anything!
Summing Up
Learning is a continuous process, and opting for
ML courses with certificates at IIT Ahmedabad is the best way to get started with your technical career. However, enrolling in online machine learning courses will only get you so far if you do not actively entrench yourself in the community.
You should always be aware of the latest trends in the market to get the most out of your learning experiences.
More Information:
Career Prospects in Machine Learning
How to Build a Successful Career in Data Science?
How to Start a Career in Machine Learning 2022?
Data Science Engineer Vs Machine Learning Engineer
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