Creating an AI-powered mobile app involves integrating artificial intelligence (AI) technologies to solve specific problems or provide unique features. Here's an overview of how to approach building an AI-powered mobile app: Key Steps to Build an AI-Powered Mobile App 1. Define the App's Purpose and Use Case Identify the problem your app will solve or the value it will offer. Examples of AI use cases in mobile apps: Chatbots (e.g., virtual assistants like Siri) Image Recognition (e.g., object detection, face recognition) Speech Recognition (e.g., voice commands, transcription) Recommendation Systems (e.g., personalized content or product recommendations) Predictive Analysis (e.g., health tracking, financial forecasting) Natural Language Processing (NLP) (e.g., sentiment analysis, language translation) 2. Choose an AI Technology or Framework Select the appropriate AI technologies or frameworks based on your use case: Machine Learning : Core frameworks: TensorFlow, PyTorch,...
#Swift, to supporting decoding and encoding we must adopt the #NSCoding protocol and implement its methods. #Apple has introduced a new way to decode and encode the #JSON data using with Codable since Swift 4. You need to consume the following API to search and display images. - Flickr Https://www.flickr.com/services/api/flickr.photos.search.htm The API results in search results for a Documentation on this page to get the image URLS: https://www.flickr.com/services/api/misc.urls.html XXXXXXXX - API Key Open Test Api - https://api.flickr.com/services/rest/?method=flickr.galleries.getPhotos&api_key=XXXXXXXX&gallery_id=66911286-72157647277042064&format=json&nojsoncallback=1 Model: - import Foundation struct ResponseCodable : Codable { let photos : Photos ? let stat : String ? enum CodingKeys : String , CodingKey { case photos = "photos" ...