Computer Vision Guided Projects using Keras

This is a curated collection of Guided Projects for aspiring machine learning engineers, software engineers, and data scientists. This collection will help you get started with basic computer vision tasks like: 1) training convolutional neural networks (CNN) to perform Image Classification and Image Similarity, 2) deploying the models using TensorFlow Serving and FlaskCustomizing Keras layers and callbacks, and 3) building a deep convolutional generative adversarial networks to understand the technology behind generating Deepfake images.

While there are many other important tasks in the domain of computer vision (object detection, semantic or instance segmentation etc.), these Guided Projects will help you build a foundation so you can complete advanced projects on your own in the future.

This collection is suitable even if you have never used CNN in Keras before. However, prior experience in Python programming and a solid conceptual understanding of how neural networks, CNN, and optimization algorithms like Gradient Descent work is highly recommended. Please note that each of these Guided Projects use TensorFlow’s implementation of Keras.

Computer Vision Guided Projects using Keras

This is a curated collection of Guided Projects for aspiring machine learning engineers, software engineers, and data scientists. This collection will help you get started with basic computer vision tasks like: 1) training convolutional neural networks (CNN) to perform Image Classification and Image Similarity, 2) deploying the models using TensorFlow Serving and FlaskCustomizing Keras layers and callbacks, and 3) building a deep convolutional generative adversarial networks to understand the technology behind generating Deepfake images.

While there are many other important tasks in the domain of computer vision (object detection, semantic or instance segmentation etc.), these Guided Projects will help you build a foundation so you can complete advanced projects on your own in the future.

This collection is suitable even if you have never used CNN in Keras before. However, prior experience in Python programming and a solid conceptual understanding of how neural networks, CNN, and optimization algorithms like Gradient Descent work is highly recommended. Please note that each of these Guided Projects use TensorFlow’s implementation of Keras.

Classification with Transfer Learning in Keras

Classification with Transfer Learning in Keras

Coursera Project Network

projeto guiado
Avaliado como 4.5 de 5 estrelas. 149 análises
Intermediate LevelIntermediate Level

What is Keras?

Keras is an incredibly powerful but simple to use API built on top of TensorFlow. Because of its ease of use, Keras is often used for rapid prototyping — imagine being able to train and test a model with just a few lines of code! It is also possible to deploy models trained with Keras in production usually by saving the models in TensorFlow's SavedModel format.

Keras is very flexible and lends itself really well to all kinds of machine learning tasks.

What is computer vision?

Computer vision is a very broad field of computer science that attempts to automate a variety of visual tasks that humans can do. For example, humans can identify and localize various objects in given images — this task is called object detection. In recent years, deep learning, particularly using convolutional neural networks (CNN), has been more and more effective in solving these computer vision tasks.

What is a Guided Project?

A Guided Project helps you learn a job-relevant skill in under 2 hours through an interactive experience with step-by-step instructions from a subject matter expert. Everything you need to complete a Guided Project is available right in your browser. No software or prior experience is required to get started.

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TensorFlow and Keras Projects for Beginners

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Machine Learning Projects using scikit-learn

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