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Machine Learning Projects for Mobile Applications: Build Android and iOS applications using TensorFlow Lite and Core ML
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Master the concepts of machine learning and build powerful apps on mobiles using TensorFlow Lite, Caffe2, and Core ML.
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What Stands Out
Podrobnosti produkta
- Explore machine learning using classification, analytics, and detection tasks
- Build Android and iOS apps using Caffe, Core ML, and TensorFlow Lite
- Learn how to classify age and gender using Core ML and TensorFlow Lite
- Discover neural style transfer and deep convolutional neural networks
- Use Google's ML Kit for Firebase to detect handwritten text on mobile
- Create a Snapchat-like AR filter using facial attributes and OpenCV
| Publisher | Packt Publishing |
| Publication date | October 31, 2018 |
| Language | English |
| Print length | 246 pages |
| ISBN-10 | 1788994590 |
| ISBN-13 | 978-1788994590 |
| Item Weight | 1.06 pounds (480 grams) |
| Dimensions | 7.5 x 0.56 x 9.25 inches (19.1 x 1.4 x 23.5 cm) |
Who Should Buy?
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Mobile Developers
Developers looking to integrate machine learning into their Android or iOS applications using TensorFlow Lite and Core ML.
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Data Scientists
Data scientists wanting to gain practical experience in deploying machine learning models on mobile platforms.
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Students Learning ML
Students seeking to learn about mobile applications with real-world machine learning projects and practical implementations.
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Beginner Programmers
Complete beginners may struggle with the concepts and coding required for implementing machine learning in mobile apps.
OPIS IZDELKA
Machine Learning Projects for Mobile Applications: Build Android and iOS applications using TensorFlow Lite and Core ML
About This Item
Introducing Machine Learning Projects for Mobile Applications: Build Android and iOS applications using TensorFlow Lite and Core ML Are you ready to take your mobile app development skills to the next level? With Machine Learning Projects for Mobile Applications, you can now learn how to build Android and iOS applications using cutting-edge machine learning technologies like TensorFlow Lite and Core ML. Whether you're a beginner or an experienced mobile developer, this comprehensive guide is packed with step-by-step tutorials, real-world examples, and hands-on projects that will help you harness the power of machine learning in your Android and iOS apps. With the rise of artificial intelligence and machine learning, integrating intelligent features into mobile applications has become a must for developers. By leveraging TensorFlow Lite, an open-source machine learning framework for mobile devices, and Core ML, a machine learning framework specifically designed for Apple devices, you'll be able to create intelligent and dynamic mobile apps that can analyze data, recognize objects, and make predictions in real-time. This book covers a wide range of topics, including Android machine learning projects, iOS machine learning projects, mobile app development with machine learning, TensorFlow Lite for mobile applications, Core ML for mobile applications, and much more.
You'll learn how to train machine learning models, integrate them into your apps, and optimize their performance for mobile devices. Discover how to build intelligent image recognition apps, automate tedious tasks using natural language processing, create predictive models for forecasting and recommendation systems, and much more. With the guidance of this book, you'll have the necessary skills and knowledge to develop advanced machine learning-powered mobile applications that will delight your users and set your apps apart from the competition. Unleash the potential of machine learning in mobile app development. Get your copy of Machine Learning Projects for Mobile Applications today and start building intelligent Android and iOS apps using TensorFlow Lite and Core ML.
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Prednosti
- Innovative project ideas
- User-friendly approach
- Real-world applications
- Great for beginners
- Well-structured content
Slabosti
- May need basic coding knowledge
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Značilnosti in prednosti
- Explore machine learning using classification, analytics, and detection tasks.
- Work with image, text, and video datasets to delve into real-world tasks.
- Build apps for Android and iOS using Caffe, Core ML, and Tensorflow Lite.
- Learn how to detect handwritten text, create custom filters, and classify food.
- Build an image classifier, compare its performance, and analyze the results.
- Targeted audience: data scientists, machine learning experts, deep learning, or AI enthusiasts.
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