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Data Sciences

Intelligent Mobile Projects with TensorFlow

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Working in a hands-on learning environment, led by our Intelligent Mobile Projects with TensorFlow expert instructor, students will learn about and explore:
Build TensorFlow-powered AI applications for mobile and embedded devices.Learn modern AI topics such as computer vision, NLP, and deep reinforcement learning.Get practical insights and exclusive working code not available in the TensorFlow documentation.

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Course Access

Unlimited Duration

Last Updated

July 29, 2021

Students Enrolled

20

Total Reviews

Posted by

Ernesto Lee

Certification

As a developer, you always need to keep an eye out and be ready for what will be trending soon, while also focusing on what's trending currently. So, what's better than learning about the integration of the best of both worlds, the present and the future? Artificial Intelligence (AI) is widely regarded as the next big thing after mobile, and Google's TensorFlow is the leading open source machine learning framework, the hottest branch of AI. This course covers more than 10 complete iOS, Android, and Raspberry Pi apps powered by TensorFlow and built from scratch, running all kinds of cool TensorFlow models offline on-device: from computer vision, speech and language processing to generative adversarial networks and AlphaZero-like deep reinforcement learning. You’ll learn how to use or retrain existing TensorFlow models, build your own models, and develop intelligent mobile apps running those TensorFlow models. You'll learn how to quickly build such apps with step-by-step tutorials and how to avoid many pitfalls in the process with lots of hard-earned troubleshooting tips..

Course Curriculum

    • Getting Started with Mobile TensorFlow 00:00:00
    • Setting up TensorFlow 00:00:00
    • Setting up Xcode 00:00:00
    • Setting up Android Studio 00:00:00
    • TensorFlow Mobile vs TensorFlow Lite 00:00:00
    • Running sample TensorFlow iOS apps 00:00:00
    • Running sample TensorFlow Android apps 00:00:00
    • Classifying Images with Transfer Learning 00:00:00
    • Classifying Images with Transfer Learning 00:00:00
    • Transfer learning – what and why 00:00:00
    • Retraining using the Inception v3 model 00:00:00
    • Retraining using MobileNet models 00:00:00
    • Using the retrained models in the sample iOS app 00:00:00
    • Using the retrained models in the sample Android app 00:00:00
    • Adding TensorFlow to your own iOS app 00:00:00
    • Adding TensorFlow to your own Android app 00:00:00
    • Detecting Objects and Their Locations 00:00:00
    • Object detection–a quick overview 00:00:00
    • Setting up the TensorFlow Object Detection API 00:00:00
    • Retraining SSD-MobileNet and Faster RCNN models 00:00:00
    • Using object detection models in iOS 00:00:00
    • Using YOLO2–another object-detection model 00:00:00
    • Transforming Pictures with Amazing Art Styles 00:00:00
    • Neural Style Transfer – a quick overview 00:00:00
    • Training fast neural-style transfer models 00:00:00
    • Using fast neural-style transfer models in iOS 00:00:00
    • Using fast neural-style transfer models in Android 00:00:00
    • Using the TensorFlow Magenta multi-style model in iOS 00:00:00
    • Using the TensorFlow Magenta multi-style model in Android 00:00:00
    • Understanding Simple Speech Commands 00:00:00
    • Speech recognition – a quick overview 00:00:00
    • Training a simple commands recognition model 00:00:00
    • Using a simple speech recognition model in Android 00:00:00
    • Using a simple speech recognition model in iOS with Objective-C 00:00:00
    • Describing Images in Natural Language 00:00:00
    • Transforming and optimizing the image captioning model 00:00:00
    • Using the image captioning model in iOS 00:00:00
    • Using the image captioning model in Android 00:00:00
    • Recognizing Drawing with CNN and LSTM 00:00:00
    • Drawing classification – how it works 00:00:00
    • Training, predicting, and preparing the drawing classification model 00:00:00
    • Using the drawing classification model in iOS 00:00:00
    • Using the drawing classification model in Android 00:00:00
    • Predicting Stock Price with RNN 00:00:00
    • RNN and stock price prediction – what and how 00:00:00
    • Using the TensorFlow RNN API for stock price prediction 00:00:00
    • Using the Keras RNN LSTM API for stock price prediction 00:00:00
    • Running the TensorFlow and Keras models on iOS 00:00:00
    • Running the TensorFlow and Keras models on Android 00:00:00
    • Generating and Enhancing Images with GAN 00:00:00
    • GAN – what and why 00:00:00
    • Building and training GAN models with TensorFlow 00:00:00
    • Using the GAN models in iOS 00:00:00
    • Using the GAN models in Android 00:00:00
    • Building an AlphaZero-like Mobile Game App 00:00:00
    • AlphaZero – how does it work? 00:00:00
    • Training and testing an AlphaZero-like model for Connect 4 00:00:00
    • Using the model in iOS to play Connect 4 00:00:00
    • Using the model in Android to play Connect 4 00:00:00
    • Using TensorFlow Lite and Core ML on Mobile 00:00:00
    • TensorFlow Lite – an overview 00:00:00
    • Using TensorFlow Lite in iOS 00:00:00
    • Using TensorFlow Lite in Android 00:00:00
    • Core ML for iOS – an overview 00:00:00
    • Using Core ML with Scikit-Learn machine learning 00:00:00
    • Using Core ML with Keras and TensorFlow 00:00:00
    • Developing TensorFlow Apps on Raspberry Pi 00:00:00
    • Setting up Raspberry Pi and making it move 00:00:00
    • Setting up TensorFlow on Raspberry Pi 00:00:00
    • Image recognition and text to speech 00:00:00
    • Audio recognition and robot movement 00:00:00
    • Reinforcement learning on Raspberry Pi 00:00:00

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