The Complete Guide For Machine Learning App Development

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The Complete Guide For Machine Learning App
Development

• NIMBLE APPGENIE LLP

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INDEX

• What is Machine Learning?
• Market Scenario of Machine Learning
• Approaches for Machine Learning App Development
• States of AI Powered Mobile Apps
• Why Should you Integrate AI into Mobile Apps?
• Step Wise for Machine Learning App Development
• Three Primary Ways to Implements AI
• How to Starts Implementation of AI into Apps?
• Top 5 AI Integrated Apps
• Conclusion

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WHAT IS MACHINE LEARNING?

1. Machine Learning is the science of getting
   computers trained and understanding and acting as
   humans do.
2. When people think about machine learning (ML),
   they think of logistics, forums, calculus figures
   in the air, lots of numbers, and almost every
   important, relevant thing.
3. The Machine learning algorithms used in machine
   learning app development could be divided into
   three ways

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TYPES OF MACHINE LEARNING
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MARKET SCENARIO OF MACHINE LEARNING

• Machine learning is a digital transformation, and
  by the end of 2021, is estimated to have received
  USD 58 billion in cumulative investment.
• The (machine learning) ML industry growth is
  predicted to reach around USD 9 billion in the
  latter part of 2022 at a compound annual growth
  rate (CAGR) of approximately 42.
• According to Markets And Markets, the Artificial
  Neural Network Market size grew from 117 million
  in 2019 to 296 million by 2024, at a CAGR
  (Compound Annual Growth Rate) of 20.5.

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STATS OF AI-POWERED MOBILE APPS

• According to research by Gartner, AI
  implementation was rare only 10 15 of
  enterprises had deployed AI or would do so
  shortly. But now, in 2021 around 37 of
  organizations have implemented AI, which is a
  270 increase in four years.
• According to Microsoft, around 44 of
  organizations fear that theyll lose out to
  startups if theyre too slow to implement AI.
• According to the Street Wall Journal, from now
  until 2030, AI advancements can increase Gross
  Domestic Product (GDP) by 14 across the globe.
• According to research, GrandViewResearch foretells
  that USD 25.0647 billion is the anticipated
  value of the global AI market by 2028 at a CAGR
  of 40.2.

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APPROACHES FOR MACHINE LEARNING APP DEVELOPMENT

• Conversion Between Model Formats

• Use Pre-Built Models

Focus on Native Development

• Using pre-built models is a shortcut way of
  building machine learning apps.
• As you can not set the foundation of your machine
  learning app on a weaker model because it would
  collapse.
• The reason is that they know what and how to fix
  and optimize everything to provide you with good
  functionality and the best results.

• In machine learning app development, always adopt
  a step-by-step approach where each model used in
  the ML (machine learning) module is converted
  from one format to another.
• To show similar results on multiple platforms,
  keep checking out suitable converters that enable
  the model conversion.
• It is a tip that will become handy in your
  development process.

•  Machine learning and Artificial Intelligence
  technology provide efficient and proficient
  services based on its search from the data set. 
• Native applications are rapid, responsive, and
  offer a significant user experience.

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STEPWISE GUIDE FOR MACHINE LEARNING APP
DEVELOPMENTS

• Selection and Formulation of Problem Statement
• Developing and Strategizing Plan
• Gathering Data
• Preparing and Analyzing Data-Sets
• Pre-processing Datasets
• Constructing Structure
• Developing Machine Learning Model
• Train The Machine Learning Model
• Test The Created Model
• Deployment of The Model

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WHY SHOULD YOU INTEGRATE AI INTO MOBILE APPS?

• Personalization- Any AI algorithm attached to
  your mobile application can analyze several
  sources of information, from social media
  activities to credit ratings and also provide
  recommendations to every user device.
• Advanced Search- The algorithms learn from the
  different queries asked by customers and
  prioritize the results accordingly. Modern mobile
  applications and search algorithms enable you to
  collect all the user data, including typical
  actions and search histories. 
• Predicting User Behavior- The significant
  advantage for marketers of AI-based machine
  learning iOS app development and android app
  development, is that they understand the
  preferences of the user and behavior patterns. 

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CONTINUE

• Improved Security Level- Artificial Intelligence
  can make a very effective marketing tool for
  mobile apps to secure app authentication and
  streamline the process.
• More Relevant Ads- Many industry experts have
  said that if you want to move forward in this
  never-ending consumer market, it can only be
  achieved by personalizing every experience for
  every customer. 
• User Engagement- The Artificial Intelligence (AI)
  development services and solutions engage
  companies to offer a span of features and
  balanced customer support. 

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THREE PRIMARY WAYS TO IMPLEMENT AI

• Recommendation

• Reasoning

Behavioral

• AI is a very proficient technology that absorbs
  the power of reasoning for solving queries.
• For example, applications like Google Maps,
  Zomato, Uber, and many more individuals travel to
  different areas often change the course or route
  according to traffic conditions.

• The technology based on the customers
  preferences then suggests the most popular
  options in their watch playlist or that
  individuals with similar tastes have watched.
• This is an amazingly popular technology for
  streaming services and is currently being
  executed into various applications.

• Every time someone tries to impersonate an online
  transaction and takaes your data via fraudulent
  activities without your knowledge, the AI system
  can track the uncommon behavior and stop the
  transaction then and there only.

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HOW TO START IMPLEMENTATION OF AI INTO APPS?
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TOP 5 AI-INTEGRATED APPS

• Siri- As Siri is very popular, I dont think it
  needs any introduction. Indeed, it is a virtual
  voice assistant app by Apple.It is available on
  all iOS devices. 
• Cortana- Cortana is another innovative and best
  AI-powered app launched by Microsoft, and it is
  also a virtual voice assistant AI mobile app. 
• Google Assistant- Google Assistant is the most
  advanced and used virtual voice assistant AI
  mobile app launched by Google. 
• Alexa- Alexa is commonly known as Amazon Alexa
  because it is an AI-powered app launched by
  Amazon. 
• Elsa- Elsa is an AI-powered app that helps users
  to learn how to speak English. Through this app,
  users can learn the pronunciation and meaning of
  the words.

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CONCLUSION

• Ive covered the step-by-step guide for machine
  learning app development. Each step is
  significant in developing the perfect
  architecture of a successful machine learning
  project. Also, it is essential to follow each of
  the mentioned steps in the same order as
  presented above.
• I hope now its clear to you how to implement
  mobile apps, and it is time to apply the
  top-notch performance and quality for AI to bring
  out the best in the application. AI is becoming
  the future of the advancement of mobile app
  development.