Laurence Moroney

Laurence Moroney is a Developer Advocate at Google working on Artificial Intelligence with TensorFlow. As the author of more programming books than he can count, he's excited to be working with deeplearn.ai and Coursera in producing video training. When not working with technology, he's a member of the Science Fiction Writers of America, having authored several science fiction novels, a produced screenplay and comic books, including the prequel to the movie 'Equilibrium' starring Christian Bale. Laurence is based in Washington State, where he drinks way too much coffee.

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Deploying Machine Learning Models in Production (Coursera)

May 1st 2024
Deploying Machine Learning Models in Production (Coursera)
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In the fourth course of Machine Learning Engineering for Production Specialization, you will learn how to deploy ML models and make them available to end-users. You will build scalable and reliable hardware infrastructure to deliver inference requests both in real-time and batch depending on the use case. You will [...]
May 1st 2024
Course Auditing
42.00 EUR/month

Natural Language Processing in TensorFlow (Coursera)

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Advanced Computer Vision with TensorFlow (Coursera)

Apr 29th 2024
Advanced Computer Vision with TensorFlow (Coursera)
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In this course, you will: a) Explore image classification, image segmentation, object localization, and object detection. Apply transfer learning to object localization and detection; b) Apply object detection models such as regional-CNN and ResNet-50, customize existing models, and build your own models to detect, localize, and label your own [...]

Device-based Models with TensorFlow Lite (Coursera)

Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. This second course teaches you how to run your machine learning models in [...]

Browser-based Models with TensorFlow.js (Coursera)

Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. In this first course, you’ll train and run machine learning models in any [...]

Convolutional Neural Networks in TensorFlow (Coursera)

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source [...]

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source [...]

Generative Deep Learning with TensorFlow (Coursera)

Apr 22nd 2024
Generative Deep Learning with TensorFlow (Coursera)
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In this course, you will: a) Learn neural style transfer using transfer learning: extract the content of an image (eg. swan), and the style of a painting (eg. cubist or impressionist), and combine the content and style into a new image; b) Build simple AutoEncoders on the familiar MNIST [...]

Custom Models, Layers, and Loss Functions with TensorFlow (Coursera)

Apr 22nd 2024
Custom Models, Layers, and Loss Functions with TensorFlow (Coursera)
Course Auditing
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In this course, you will: • Compare Functional and Sequential APIs, discover new models you can build with the Functional API, and build a model that produces multiple outputs including a Siamese network; • Build custom loss functions (including the contrastive loss function used in a Siamese network) in [...]