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Machine learning is a modern science which enables computers to work without being explicitly programmed. The modern-day technology deploys algorithms that can train and improve on the data that is fed to them. Over the years, machine learning has made possible the concept of self-driving cars, effective web search, spam free emails, practical speech recognition software, personalized marketing and so on. Today, machine learning is increasingly being deployed in credit card purchase fraud detection, personalized advertising though pattern identification, personalized shopping/entertainment recommendations, to determine cab arrival times, pick-up locations, and finding routes on maps.
The growth of machine learning is driving business and revenues to new heights. It is predicted that about $47 billion will be budgeted towards machine learning in 2020. The prospect of startups and business establishments adopting machine learning technology is equally promising. Forecasts estimate a 64% adoption by enterprises investing into machine learning with 72% of the executives concurring to incorporate machine learning solutions as a core ingredient into their business operations.
Machine learning is the buzz of the tech generation; here are the top 5 machine learning trends of 2018:
Machine learning jobs are in hot demand. Data scientist tops the job chart with the huge gap in demand and supply of resources. There is a wide skill gap between the qualified machine learning professionals and the job market potential. This machine learning trend will disrupt the technical education system, academicians will have to plan and execute courses to answer the ever-widening gap in demand and supply. Education certifications on machine learning will be in huge demand as hiring issues will remain to escalate without proper educational skill sets.
The development and growth of data accessibility have led to progressive hacking techniques. Multiple devices connected to the internet create data and also expose the systems to vulnerable risks. Machine learning in cybersecurity works both ways, if used by potential hackers it can result in stronger attacks while if deployed by cybersecurity firms it can increase the level of security. Since machine learning is a readily available technology, it is best if the defenses to cybersecurity are fortified in anticipation of the potential security threats.
The human adaptability to machine learning has led to a heavy reliance on robotic process automation with intelligent drones and robots dominating the technological revolution space. The deployment of robotic process automation extends to finance, health and even manufacturing processes where robots make the task easier. Though there is an increasing concern that robots may replace humans at work, there is no need to press the panic button now, there will be human operators to the robots and the intelligent human minds constructing their blueprints.
InfoTech is generating massive data through log files, status reports and error logs. There is huge data being generated through hardware components, software components, server applications, and operating systems. Not all the data is fit as inputs to machine learning models. Machine learning captures, cleans data and generates intelligent business insights to make an IT enterprise become proactive instead of reactive. Models built on machine learning operate on clean data for training and testing phases. Machine learning algorithms assist IT operations teams to find the root cause of issues, supported by predictive analytics for improved operations.
The impact of machine learning models in industries such as retail, healthcare, medicine, and logistics has been increasingly felt. Machine learning algorithms are deployed especially in loan application evaluations and medical diagnosis applications. Machine learning through predictive models brings transparency in decision-making in the multitude of domains. Machine learning is an effective tool in transparent decision-making where laws and regulations (for example in HR operations treating job applications equally without consideration of age, gender, religion, caste, creed, color, etc.) come into the picture.
To conclude, 2018 holds a promising opportunity for technological innovations. The new exciting technological developments will witness faster and more accurate machine learning algorithms. The exponential improvement of machine learning technologies will open up new avenues for Internet of Things, NLP, and self-teaching AI to lead a change in the business industry and our everyday life. On one hand, machine learning if dominated by wrong hands and minds will create a threat to security, but on the other hand, new approaches and solutions to improved living are continuously evolving. The changes brought by machine learning will bring amazing outcomes that will redefine our way of living in times to come.
