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,...
One Line Parsing JSON in Swift 4.0 With Codable or Decodle
Swift 4 includes a new way to generate and parse JSON with Swift Codable protocol.
JSON:-
{
"name" = Rahul'
"id" = 10
"collage" = RTS Collage
"code" = A190
}
Start:-
import UIKit
struct Profile: Codable {
let name: String
let id: Int
let collage: String
let code: String
Convert Item(Profile) to JSON
init?(json: [String: Any]){
guard let name = json["name" ] as? String,
let id= json["id" ] as? Int,
let collage= json["collage" ]as? String,
let code= json["code" ] as? String, else { return nil}
self.name = name
self.id = id
self.collage = collage
self.code = code
}
}
class ViewController: UIViewController {
guard let url = URL(string: "https://xxxxxxxxxx") else {return}
URLSession.shared.dataTask(with: url) { (data, response , error) in
guard let data = data else {return}
do{
let decoder = try JSONDecoder().decoder(Profile.self, from: data)
// check access data......
print(decoder.name)
} catch let err{
print("Err", err)
}
}.resume()
}
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