Machine learning will soon be the omnipresent and the invisible force that will slowly replace human decision making with more sophisticated technologies. These technologies will be used across a spectrum of industries like automobiles, manufacturing, entertainment, agriculture, healthcare, etc. Top companies like Microsoft, Google, Apple, Facebook, etc are investing heavily in research and development of machine learning.
In this rapidly changing scenario, let us see some of the top emerging Machine Learning trends that will probably pave the way for the future.
Sieving the Big Data using Machine Learning
Today, data is both the fuel and the byproduct of Computer Science. We are producing mountains of data but are fast running out of places to store the data. Cloud Computing is very helpful but the overall costs of managing Big Data is driving us to find alternatives. In these situations, Machine Learning is used to sieve relevant data and route out the unnecessary data.
Inter-operability among Neural Networks
One of the major challenges of Artificial Neural Networks is to port them across different frameworks. To resolve this problem, Open Neural Network Exchange (ONNX) has emerged as a platform where AWS, Facebook and Microsoft have collaborated for the reuse of trained neural network models across multiple frameworks. ONNX is becoming an essential technology that will lead to increased interoperability among Neural Networks.
Automated Machine Learning
Automated Machine Learning will allow non-experts to easily handle complex scenarios in training ML models. Tools like AutoML can be used to train high-quality machine learning models without requiring a detailed understanding of the complex workflow but of course with the help of reasonable measure of expertise.
Use of Machine learning for Language and Speech
The use of Machine learning to process and analyze language will place an invaluable strategic asset in the hand of companies about the user’s sentiments, preferences, etc. This emerging technology is known as Natural Language Processing. The companies will use NLP for a better understanding of market trends, and operational risks. Some customer support applications like chatbots use ML and NLP to interact with the users in textual form.
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