WordPress Hosti
HomeMobile Apps5 Best Ways to apply Machine Learning on your Apps

5 Best Ways to apply Machine Learning on your Apps

Best WordPress Themes

Machine Learning is not a new technology. We have already seen many applications with advanced AI algorithms. Recently, when the pandemic hit the human race, there was a rising concern that our hands should not come in regular contact with the face. 

It was essentially pointed out in a post on Reddit when this user wanted to create an app using Machine Learning to alert them whenever his hands came near to face. Though this is just one instance of ML’s application, it is almost an integral part of many mobile apps. 

According to this tweet, 2019 witnessed more funding than any other AI-based technology, which was around $28.5 billion. Mobile apps have seen many new advancements in smart integrations, and ML has one of them.

So, how do you go about leveraging this promising technology? Here, we are going to discuss the five best ways to apply such algorithms on your apps. 

How do I Create an App with Machine Learning?

Learning Robot

ML algorithms can record, analyze, and learn data from diverse sources. These algorithms often do not need human intervention making them useful tools of automation. If you are thinking of creating a mobile app with Machine Learning capabilities, there are two simple ways to do it.

  • Use a pre-built model.
  • Create one for your project. 

There are many pre-built models available in the market that are proven and tested. Some of these models are,

- Advertisement -Fiverr Business
  • Core ML by Apple
  • TensorFlow Lite by TensorFlow
  • Cloud AI by Google
  • ML Kit by Firebase

If you want to customize your ML algorithm for mobile applications, creating a native app or web app can be fruitful. You can choose to develop native ML apps or web apps now with dedicated kits provided by iOS and Android platforms. 

Now, let’s discuss the five best ways to use it in mobile apps. 

1. ML for Product Research

Machine Learning in Product Research

Machine Learning algorithms can help you gather and analyze data from the market to evaluate the app idea. Here, you can employ three different ways of researching your product with ML.

- Advertisement -Best WhatsApp Tracker

1. Generative Research

It is an approach that you can use specifically while entering a new domain. Suppose you are planning to create a chatbot for an eCommerce app that helps customers with product recommendations.

ML helps you beta test a chatbot app prototype with few users to get a general idea of the CX. 

2. Moderated Research

The first user session will provide you with factual data to create usability lists.

You will now know what kind of features customers will like; next, you can have moderated sessions for users and employ an ML algorithm to analyze the feedback. 

3. Unmoderated Research

Create a working prototype of your chatbot app after several iterations of feedback integrations through Machine Learning algorithms.

Now, execute unmoderated working prototype sessions to have feedback on a larger scale before the final product’s grand launch. 

2. ML for App Development

ML in App Development

With the expansion of cloud services and serverless technologies, the integration of Machine Learning into app development is relatively easy. But, the creation of custom ML algorithms needs infrastructure and skilled professionals at the helm.

If you are interested in mobile app development with Machine Learning, you will need a good algorithm designed according to business needs. 

Most of the native platforms offer Software Development Kits or SDKs specifically for Machine Learning. Take an example of the Teachable Machines from Google that allows you to teach your machine image recognitions and other such features.

It is an open-source project for anyone interested in Machine Learning models.

Machine Learning Models and Algorithms

There are many types of models already used by giants like Netflix, Youtube, eBay, or Amazon, where Machine Learning algorithms offer recommendations to customers based on their usage patterns.

For example, you watch a movie on Youtube, and an ML algorithm will provide you multiple recommendations based on common attributes. 

3. ML for Customer Engagement

Customer Engagement

According to Mihajlo Grbovic, the senior machine learning scientist at Airbnb, 

You would be surprised how many times you interact with a machine learning model when you are on Airbnb.com.

Airbnb is an e-marketplace for users to rent out their houses and spare space for guests. The firm has research sessions with the users to have comprehensive data regarding its product.

Machine Learning Airbnb 

It is a Machine Learning project that allows the guests to search for Airbnb experiences than just houses or properties. For example, a person wants to explore Dubai’s famous Burj Khalifa, and they can search for the tallest building in the world at the Airbnb search bar. 

One can use ML algorithms to achieve a high level of customer engagement with such personalized experiences. 

4. ML for Personalization

Customer Support

Machine Learning can help you personalize products to a greater extent by projecting customer’s creativity. Nike tried to achieve something like that back in 2017 with a live design campaign called “Nike Makers’ Experience.”

Users can start using a birthday or anniversary input to create patterns. Here, an algorithm converts the typographical information into relative patterns and then scales them according to the customer’s taste. 

There are endless color combinations and infinite customization patterns for consumers. You can use Machine Learning algorithms to induce such personalization in your mobile apps. 

5. ML for Customer Support

Serving your customers is a quintessential part of the business. Even if you create the most fantastic product, engage customers, and personalize interactions with ML, all is in vain if you don’t have good customer support service.

Fortunately, Machine Learning has been used extensively over the decades for assisting customers. 

Building Chatbots with Machine Learning is not the only way to enhance the customer experience. You can create an ecosystem of human customer service agents and Machine Learning models to generate better customer support systems.

The prediction engines of ML models can help you gauge customer behavior and recommend solutions or alternate products. 

Conclusion

Machine Learning models can help you create smarter mobile applications or web apps and create better products, engagements, and CX.

Before diving into the ML approach for your apps, it is essential to understand your business’s data-driven nature. How much a Machine Learning model impacts your business will help identify the exact approach.

The best practice is to have a comprehensive research and ideation phase for your Machine Learning apps before getting started. 

Author Bio

Hardik Shah works as a Tech Consultant at Simform – a dedicated team of mobile developers in Chicago . He leads large scale mobility programs that cover platforms, solutions, governance, standardization, and best practices. Connect with him to discuss the best practices of software methodologies @hsshah_

Related Topics

Paschal Okafor is NaijaTechGuide Team Lead. The article 5 Best Ways to apply Machine Learning on your Apps was written by NaijaTechGuide Team. The article was last modified: November 3rd, 2022
AliExpress 11 11 Sales
NaijaTechGuide may receive financial compensation for products/services purchased through affiliate links on this site. See full Affiliate Disclosure Here
NaijaTechGuide Team
NaijaTechGuide Team
NaijaTechGuide Team is made up of Experienced Tech Enthusiasts and Professionals led my Paschal Okafor, a graduate of Electrical and Electronics Engineering with over 17 years of Experience writing about Technology. Some of us were writing about Mobile Phones before the first Android Phones and iPhones were launched.

Recommended Read on NaijaTechGuide

Best Marketing Automation Software 2024

You need the best marketing automation software to scale your business fast and convert...

Best Content Marketing Tools for 2024

As a content marketer, you have a lot of tasks to accomplish. You need...

Best VPN Services Providers for 2024

The internet is one of the greatest achievements of humanity, but it is also...

Best 20KVA Generators to Buy in 2024

Generator sets, as an alternate source of power supply, come in their different sizes...

Best Laptops for Students 2024: 11 Top Picks to Choose From

So, you are a student who is looking to get the best laptop they...

Cheap Android Phones 2024 – Price, Specs, and Best Deals

Android phones are the most popular smartphone category. The popularity of Android phones are...

Best Android Phones 2024 – Price, Specs, and Best Deals

New Android Phones are launched into the market every week. This means that if...

Best Web Hosting Services for Building Websites in 2024

A good and reliable web hosting service will make a big difference for your...
Fiverr Business

More like this

Building a Resilient Database System for Financial Applications

In  general  terms,  resilience  is  the  ability  to  withstand  adversity  and  bounce  back  from ...

The 2024 Africa Technology Expo comes to Lagos in Full Flight

The 2024 Africa Technology Expo, organized by Spark Africa and now proudly sponsored by...

Database Optimisation, a Continuous Process not an Event

Databases are a critical component of applications that power small and large businesses. The...