6 Real and Innovative Ways to Make Money with Machine Learning
Waves of ML/AI are already impacting industries like Information Technology (IT), Financial Technology (FinTech), Healthcare Technology (HealthTech), Education Technology (EdTech), and others. Companies are more laser-focused on AI value, moving beyond the testing phase and concentrating on rapidly expanding their usage of AI.
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SEMrush predicts that by 2025, the worldwide market for artificial intelligence will be worth $190.61 billion. Consequently, this will raise the demand for skill sets specific to ML/AI. There has never been a better moment to start making money in machine learning. You may work with companies across the globe on intriguing technology initiatives, and your career options can scale new horizons.
Basic knowledge of technology and programming language can get you started with ML. For starters, you need to adopt a programming language, work with different frameworks, and be able to write different codes to solve problems. But, at its core, you have AI as the backbone and ML as an application part.
Besides the technical know-how, reaching out to the right people is essential. Complement your machine learning skills with consistent efforts to boost your online visibility. Think of investing in online marketing, creating a free ecommerce website, and registering yourself on freelancing platforms like Fiverr or Upwork, thereby accelerating efforts on personal branding through social media.
Once done, here are some ways to explore and profit from machine learning.
#1. Develop a Simple AI App
Earn money by creating an AI-driven application for social media monitoring, chatbots, IoT apps, etc. This can be a paid app where users pay to access exclusive content. App sales on Android and iOS combined for $133 billion in 2021. Other estimates show that subscription applications generate more revenue than other types of in-app sales.
Make these applications available on multiple platforms (Desktop, Mobile Phones, Tablets, etc.) to reach a larger audience and create a difference in users’ lives. You can choose open-source app development platforms like Flutter to mitigate costs and resource dependencies. For example, use Flippa to sell your app, and you will make money immediately.
Try carving out a specific market niche and using audience data knowledge to generate money-building apps across different sectors.
#2. Become an ML Educational Content Creator
Machine learning is a relatively new field of study with very few experts. There is a huge gap in the demand and supply of AI experts. Therefore, offer to tutor students and business professionals if you have enough knowledge.
Leverage online learning platforms like Coursera and Udemy to create and sell your courses. Alternatively, start your own YouTube channel or design a course to educate the public on this technology. You can also conduct webinars and provide hands-on knowledge to machine learning enthusiasts for a fee.
#3. Freelance ML Jobs
Another way to leverage your ML knowledge is by earning money for your expertise by taking freelance jobs.
On the other hand, Toptal caters to the most qualified freelancing machine learning programmers and the most qualified firms eager to recruit them. Hiring businesses can check hourly rates, developers’ quality, experience, and expertise.
Getting a freelance contract from Toptal requires passing a few tests. But once you are through, you are up for a high-paying contract if roped in by a top enterprise for your expertise.
Another way to earn money with AI as a freelancer is to register with clickworker as a so-called “Clickworker” and do jobs on the clickworker online platform to create training data for AI, such as various photos, including selfies, or creating short videos and voice recordings.
The advantage with these jobs is that you support and improve AI systems, and you don’t need any programming skills to do so.
Many businesses leverage social media to drive growth by understanding customer requirements and knowing them better. Even social media platforms use machine learning to improve user experience.
One of the many benefits of AI in social media is a custom news feed tailored to satiate users’ tastes. Accordingly, the platform shows ads that have higher chances of conversion. ML can analyze user behavior to determine the best course of action to take, considering user interests, career, and nature.
Even Pinterest offers recommendations based on the pins users like using machine vision to recognize things in photographs using Computer Vision. This ML application gleans useful data from videos and photos. It identifies the pins in photographs, providing recommendations for related pins tailored for a specific user.
This is useful for businesses looking to promote their products on Pinterest. When they onboard Pinterest experts, they value your recommendations. You can help their business characterize pins in a way that makes them searchable (with a decent grasp of relevant keywords). The more convenient it is to look up a pin, the more people will visit the business’ pins, driving more sales.
#5. Generate Vast Artificial Intelligence Data
Another great way to earn money using ML is by offering AI-driven data. Businesses need data for decision-making and since machine learning can produce huge amounts of data easily, try extracting and selling those.
AI works like a human brain. It can comprehend audio-visual elements and also adapt to new learnings. An AI system feeds on comparable learning and dynamic data made available from different medium — text, audio, and video.
Access to such data is expensive, but you can monetize it by selling it to research foundations and knowledge enterprises. You may need to use agency services to ensure privacy, security, accountability, accuracy, and reliability when transacting those data for money.
#6. Financial Apps and Predictive Analytics
Your ML expertise and knowledge can help bring in money through the stock market by increasing the chances of profits. Machine learning helps predict when to purchase or sell a certain stock or even a winning bet in a sporting event.
You may charge money to online betters and stock market investors if you have a track record of making reliable forecasts with just a small margin of error.
Try practicing paper trading before investing real money in anything too complicated. You can retrieve data using API in Python. For example, you can make stock market predictions based on historical trade figures and run a query for predicting future buy/sell calls.
Conclusion
Mastering machine learning is pretty straightforward, as there are plenty of online courses and masterclasses from experts. Enrolling yourself in such programs helps sharpen your knowledge and get you industry-ready.
Here’s a complete history of machine learning that helps you know its origins, but the scope is much wider now. Therefore, acquiring key skills in this domain can open floodgates of opportunities in the coming time. Once you are confident enough of your knowledge, start with any of the abovementioned activities to drive personal and financial growth.
FAQs on Make Money with Machine Learning
How much can I earn with machine learning?
The answer to this question depends on a variety of factors, including your experience level, the industry you work in, and the specific job roles you are applying for. That said, machine learning professionals can expect to earn an average salary of $80,000 per year
Which job in AI offers the highest salary?
There is no definitive answer to this question as it largely depends on experience, geographical location, and the specific company. However, some of the highest paying AI jobs include positions such as Data Scientists, Machine Learning Engineers, and AI Researchers.
How to make money using machine learning ?
There are a few ways to make money using machine learning. One is to develop models that can be sold or leased to other companies. Another way is to develop machine learning-based products that can be sold to consumers. Finally, companies can use machine learning to improve their own internal processes and make themselves more efficient.
