By equipping machines with the ability to ‘learn’ to mimic human behaviour, machine learning is automating menial and repetitive tasks, delivering better insights from data, and even making cars drive themselves.
If the present state of ML is exciting as it is, the future of machine learning opens up significantly more and highly complex opportunities for technologists. Let’s look at them one by one.
The Future Scope of Machine Learning: Top Use Cases
“Machine learning is the process of automatically getting insights from data that can drive business value”, says Lavanya Tekumalla, founder of AiFonicLabs and Springboard mentor. This is typically done in the following process:
- Gathering and preparing large volumes of data that the machine will use to teach itself.
- Feeding the data into ML models and training them to make right decisions through supervision and correction.
- Deploying the model to make analytical predictions or feed with new kinds of data to expand its capabilities.
Let us look at some of the top use cases evolving today, which will come to expand the future scope of machine learning.
#1 Optimising Operations
The most common use case in optimising operations is in document management. Today, there are a large number of robotic process automation and computer vision companies such as UIPath, Xtracta, ABBYY etc. enabling this. The future of machine learning will aim higher though.
- There are emerging ML technologies that enable retail stores to monitor body temperatures and mask-wearing using thermal imaging and computer vision tech towards a safer return from COVID-19 to normalcy.
- Sensors and IoT technologies are helping manufacturing operations optimise granularly across the supply chain.
- The renewable energy industry is using AI to mitigate the unpredictability of sources.
#2 Safer Healthcare
We’ve been seeing significant growth in machine learning being used to predict and support COVID-19 strategies. The healthcare industry itself has been long using ML for a wide range of purposes, we believe that the future scope of machine learning will undertake more complex use cases.
- Robots performing complicated surgeries precisely.
- ML programs reading patient history, records, reports etc. to devise personalised treatment plans. IBM Watson Oncology is an important project in this space.
- Wearable technology for disease prevention and elder healthcare monitoring is also making great strides.
#3 Fraud Prevention
Banks and other financial institutions use machine-learning-based fraud detection technology to stop malpractices (although the irony of proving ‘I am not a robot’ to a machine is not lost!).
- Banks are building machine learning algorithms based on historical data to predict fraudulent transactions.
- Classification and regression methods are being used to identify and filter out phishing emails.
- Machine learning and computer vision algorithms are checking for identity matching across key databases in real-time to prevent identity theft.
- These pattern matching techniques are also used to identify fake documents to prevent forgery.
#4 Mass Personalisation
Retail, social media and entertainment platforms use ML to give customers personalised services and experiences.
- The face swap filter uses algorithms based on image recognition and computer vision to detect and (well, almost) accurately exchange facial features.
- E-commerce and media platforms are using ML to offer hyper-personalised experiences, as well as offer freemium models of payment.
ML Career Scope: Job Opportunities
LinkedIn currently lists more than 23,000 jobs for an ML engineer, with hiring having continued through the pandemic. Some of the companies hiring currently are PayPal Morgan Stanley, Airtel Payments Bank, Google, Autodesk etc.
Since machine learning needs you to know computer programming, statistics and data evaluation, the future scope of your machine learning career can also be in leadership roles in automation or analytics environments that use data science, big data analysis, AI integration etc.
Future of Machine Learning: Salaries
An ML engineer in India earns an average salary of ₹687,250. This is more than other related tech jobs like data scientist, software engineer and data analyst, as the image below shows.
The LinkedIn community reports that ML salaries can grow to ₹19,30,000 with 6-14 years of experience. Gaining additional skills in deep learning, NLP, computer vision etc. will enable an ML engineer to take up multi-skill roles like this one for a machine learning application developer at Accenture.
Prepare for the Future of Machine Learning with Springboard
The Springboard AI/ML Career Track will give you 14 real-world projects that you can add to your portfolio and use to impress an employer. You’ll also get 1:1 mentorship by industry experts and dedicated career coaching to make sure that the Springboard job guarantee leads directly to your dream job!