13-10-2024, 05:13 AM
[center]![[Image: f6t7S4KPpqZqNbswqXxfVbV2SnPeJ4wl.jpg]](https://sanet.pics/storage-10/1024/f6t7S4KPpqZqNbswqXxfVbV2SnPeJ4wl.jpg)
The Complete Course To Build On-Device Ai Applications
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 811.42 MB | Duration: 0h 53m
Master how to build on-Device AI Applications and deploy AI Applications into various devices!
[/center]
What you'll learn
Be able to build on-Device AI Applications
Learn how to build and deploy the application into various devices
have the knowledge to build responsive and energy-efficient applications.
Build some applications with AI
Requirements
You must have basics knowledge of CSS and HTML
Description
You will learn how to Build on-Device AI Applications in this course. On-device AI applications are rapidly transforming how artificial intelligence is deployed, offering powerful advantages in terms of performance, privacy, and energy efficiency. Unlike cloud-based AI, which relies on sending data to external servers for processing, on-device AI performs computations locally on a user's device, such as a smartphone, smartwatch, or IoT sensor. This shift in paradigm is reshaping industries by enabling faster decision-making, improving security, and reducing latency in real-time applications.one of the benefits of on-device AI is reduced latency. By eliminating the need to send data back and forth to a remote server, AI models can process information instantly. This is critical for applications requiring real-time responses, such as autonomous driving, augmented reality (AR), and virtual assistants. For instance, a self-driving car must detect and react to objects in its environment in milliseconds, something that cloud computing alone cannot guarantee due to potential delays in communication. On-device AI also enhances user privacy. By keeping sensitive data on the device, the risk of exposure during transmission to external servers is minimized. on-device AI is unlocking new opportunities across various industries, enabling more responsive, private, and energy-efficient applications. As hardware and software innovations continue to evolve, the potential for on-device AI will only grow, offering even more sophisticated and ubiquitous intelligent experiences.
Overview
Section 1: Introduction
Lecture 1 Build on-Device AI Applications Introduction
Lecture 2 Build AI Applications Overview
Lecture 3 building ToDo Application with AI
Lecture 4 Creating an E-Commerce Website with AI
Lecture 5 AI components with API
Lecture 6 AI Powered componets
Lecture 7 Building an E commerce Webportal with AI
Data scientists and AI Developers
Screenshots
The Complete Course To Build On-Device Ai Applications
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 811.42 MB | Duration: 0h 53m
Master how to build on-Device AI Applications and deploy AI Applications into various devices!
[/center]
What you'll learn
Be able to build on-Device AI Applications
Learn how to build and deploy the application into various devices
have the knowledge to build responsive and energy-efficient applications.
Build some applications with AI
Requirements
You must have basics knowledge of CSS and HTML
Description
You will learn how to Build on-Device AI Applications in this course. On-device AI applications are rapidly transforming how artificial intelligence is deployed, offering powerful advantages in terms of performance, privacy, and energy efficiency. Unlike cloud-based AI, which relies on sending data to external servers for processing, on-device AI performs computations locally on a user's device, such as a smartphone, smartwatch, or IoT sensor. This shift in paradigm is reshaping industries by enabling faster decision-making, improving security, and reducing latency in real-time applications.one of the benefits of on-device AI is reduced latency. By eliminating the need to send data back and forth to a remote server, AI models can process information instantly. This is critical for applications requiring real-time responses, such as autonomous driving, augmented reality (AR), and virtual assistants. For instance, a self-driving car must detect and react to objects in its environment in milliseconds, something that cloud computing alone cannot guarantee due to potential delays in communication. On-device AI also enhances user privacy. By keeping sensitive data on the device, the risk of exposure during transmission to external servers is minimized. on-device AI is unlocking new opportunities across various industries, enabling more responsive, private, and energy-efficient applications. As hardware and software innovations continue to evolve, the potential for on-device AI will only grow, offering even more sophisticated and ubiquitous intelligent experiences.
Overview
Section 1: Introduction
Lecture 1 Build on-Device AI Applications Introduction
Lecture 2 Build AI Applications Overview
Lecture 3 building ToDo Application with AI
Lecture 4 Creating an E-Commerce Website with AI
Lecture 5 AI components with API
Lecture 6 AI Powered componets
Lecture 7 Building an E commerce Webportal with AI
Data scientists and AI Developers
Screenshots
Code:
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