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MVVM Image Search App

Course Reviews

Track :

Mobile Development

Lessons no : 13

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What will you learn in this course?
  • Implement MVVM architecture to develop scalable and maintainable image search applications using modern frameworks and tools
  • Design and build user interfaces for image search apps that enhance user experience and engagement with intuitive layouts and navigation
  • Integrate reverse image search functionalities, including image descriptor definition, dataset indexing, and similarity metrics, into mobile apps
  • Optimize image search algorithms for accuracy, speed, and relevancy to deliver precise results in real-world applications
  • Utilize APIs and third-party services like Google Lens and TinEye to enhance image recognition and search capabilities
  • Apply best practices for data management, storage, and retrieval to ensure efficient handling of large image datasets
  • Implement testing and debugging techniques to ensure app reliability, performance, and security in diverse environments
  • Create comprehensive documentation and user guides to facilitate app deployment, updates, and user onboarding

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Lessons | 13


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4.7
6 Reviews
Husnain Ali 

good
2025-05-30

Abdoulaye Bonkoungou 

EXCELLENT
2025-05-07

Eli Njoroge 

Very easy to follow and understand. I can't believe I followed the whole tutorial without experiencing errors. Thanks Bro the tutorial
2023-08-03

Abdul Kalam 

Good
2023-06-11

BAJCHAND 

Very good
2023-06-11

Charumathi Devarajpandi 

Very much interesting
2023-05-26

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What is the best image search app? The 10 Best Reverse Image Search Apps for iPhone and Android CamFind. Image Gallery (2 Images) ... Google Lens. Image Gallery (2 Images) ... Veracity. Image Gallery (2 Images) ... Reverse Image Search App. Image Gallery (2 Images) ... Direct Image Search on Google. Image Gallery (3 Images) ... Photo Sherlock. Image Gallery (2 Images) ... TinEye Reverse Image Search. ... Reverse Photos Image Search.How do I make an image a search engine? So there you have it, the four steps of building an image search engine, from front to back: Define your image descriptor. Index your dataset. Define your similarity metric. Perform a search, rank the images in your index in terms of relevancy to the user, and display the results to the user.