Indispensable Machine Learning App Ideas

We witness a lot of use cases of AI, NLP, DL, and ML in the computational world. Here we’ve tried listing some less-known apps of Machine Learning that can become profitable business ideas in 2023!

So, does anyone have an idea? Treat this article as a point during the company meeting where the leader opens up the floor and you don’t want to be caught off guard. It’s important to have an actionable process up your sleeve for how you’ll be the one to say, “Yes! I have an idea of machine learning in mobile applications”

There are three questions to consider, which position you to be the one who consistently produces good ideas, even endow you with the superpower of producing great ideas? These can be ideated by using the three G’s – Goal, Gap, and Gain. If you are not filling the gap then probably you are not contributing something significant, important, inspiring, original, challenging and out of the box! Just think about what is needed. Is it a product or a service that you are aspiring to create? Is it going to resolve a pertinent problem, or is it just for entertainment purposes only? What is the key question that requires an answer? What does the audience need? Anything under-researched or underfunded? Always remember that beneficial ideas inform, entertain, provide utility, and offer value for the greater good.

• Apps that respond to a desire – Lottery or Bumble
• Apps that satisfy a hope with the promise of a positive outcome – Tonal fitness
• Apps that address a need – Doordash
• Apps that point to a need – Apple’s iPhone
• Apps that solve a problem – Tylenol
• Apps that resolve a pain point – Mastercard’s True Name
• Apps to change perceptions – Momofuku
• Apps to provide fun or entertainment – TikTok or Twitch
• Apps to provide information or education – DuoLingo
• Apps to provide a utility – Google or LegalZoom
• Apps to advocate – Nike or Southern Poverty Law Center
• Apps for self-actualization – Alvin Ailey extension Dance classes

Natural language processing, deep learning, machine learning, and machine learning are interrelated and form a part of an umbrella concern for emerging technologies. One of the essential first steps in the long journey of establishing a successful business idea is coming up with ideas. Today, the artificial intelligence industry is becoming the most promising for startups with a rapidly increasing growth rate. Because of its flexibility, this technology can be used in several professions and sectors which makes settling for one difficult. Before the end of this article, you will be able to make a choice for your ML AI business. AI-based startups are leveraging NLP, Computer vision, DL and Machine learning to fulfil the emerging needs of the customers.

E-Learning

The first achievable machine learning and artificial intelligence idea is E-learning. In most schools, there is an insufficient number of teachers to teach and instruct students, especially those who are not doing well in their studies. This is based on the perceived notion that humans learn faster when taught according to their unique characteristics and abilities. AI can formulate how best to create an individualized lesson plan to help users to learn faster and better. AI/ML market is already there, you simply have to make it profitable to both user and you. There are different areas your startups can address. ML can be used to build a system that is used to diagnose an ailment or a system that provides medical intervention before the patient requires hospitalization.

First Aid

It helps to leverage the average life expectancy of humans, reduce the cost of healthcare and reduce human error.

Marketing Strategy

Marketing requires a lot of time and effort. While the majority of time is spent learning relevant skills or applying those skills. But applying artificial intelligence can actually help in amplifying the marketing performance of an organization, using experiences over time and combining it with advanced workflow analytics to boost the overall marketing strategy. This can be used by marketers and researchers to gather data

Retail and eCommerce

ML helps in shopping app personalization. The use of virtual assistants helps in picking the hints dropped by users as they browse the app.

Smart homes and home management

To check on kids, parents, and pets to allow controlling home from anywhere in the world.

Grammar and Word dictionary Applications

Syntactic analysis and parsing can be used to construct applications to check basic grammar rules, identify sentence structure, word organization, and work relation, and create spell check, grammar check, and correct English text. Machine learning development companies develop AI-powered assistants to make text clear, error-free and easy to understand. Applying syntactic analysis in tagging parts of speech and labelling tokens as verbs, adverbs, adjectives, nouns, etc helps infer the meaning of the word. This may mean different things to different organizational applications. These are also used to replace frequently occurring words or remove repeating words that do not add any semantics value like I, they, like, yours, have, etc. Also, word sense disambiguation and relationship extraction are also a part of semantic analysis.

Search Engine Optimizations

In another instance, lemmatization and stemming take care of reducing inflected words to their base form to make it easier to analyze. Search Engine Optimizations make use of lemmatization to respond to user queries in the best possible way.

Sentiment analysis is also used to better understand the user’s sentiments in a message. Any text is analyzed after lemmatization. Also, lemmatization can be used in information retrieval (advanced searches). It groups similar data and enhances the performance of search engines and other search algorithms. NLP and semantic analysis is often used in online dictionaries, to speed up the time-consuming process of rigorous testing, and conduct morphological analysis on words.

Examples of Real-Life Applications in ML

ML AI applications can also be built around Security services, IT services, cyber security, conversational interfaces, and next-generation chatting apps, which automatically detect faults and anomalies, and detect possible threats.

• Image recognition
• Speech recognition
• Medical Diagnosis
• Commuting Predictions
• Voice Assistants
• Filtering Emails, Spam, Malware
• Online customer support
• Online fraud detection
• Search engine optimization
• ML Educational Content Creator

Conclusive

If you have ever wished for the eureka moment to make an appearance during that monthly brainstorming session or the most awaited global seminar on AI/ML/Analytics for a new project? Producing great ideas on a roll may seem like a distant dream but you must always start first by determining the goal of the task at hand by hiring dedicated ML developers. The response to this can lead to a substantial idea. In a similar way, focus next on the gap you are looking to fill and the gains that can be derived.

Various AI/ML scenarios like Data-centric AI, Model centric AI, Applications centric AI, and Human-centric AI make use of AI to improve and augment evergreen classics of data labelling, synthetic data, knowledge data, and annotation. Ideas are seeds – your idea might inspire someone else. Often connect to other ideas, and they connect us to each other. Worthwhile ideas change the playing field and can literally alter the course of human progress.