Object Localization with TensorFlow
Welcome to this 2 hour long guided project on creating and training an Object Localization model with TensorFlow. In this guided project, we are going to use TensorFlow's Keras API to create a convolutional neural network which will be trained to classify as well as localize emojis in images. Localization, in this context, means the position of the emojis in the images. This means that the network will have one input and two outputs. Think of this task as a simpler version of Object Detection.
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Welcome to this 2 hour long guided project on creating and training an Object Localization model with TensorFlow. In this guided project, we are going to use TensorFlow's Keras API to create a convolutional neural network which will be trained to classify as well as localize emojis in images. Localization, in this context, means the position of the emojis in the images. This means that the network will have one input and two outputs. Think of this task as a simpler version of Object Detection. In Object Detection, we might have multiple objects in the input images, and an object detection model predicts the classes as well as bounding boxes for all of those objects. In Object Localization, we are working with the assumption that there is just one object in any given image, and our CNN model will classify and localize that object. Please note that you will need prior programming experience in Python. You will also need familiarity with TensorFlow. This is a practical, hands on guided project for learners who already have theoretical understanding of Neural Networks, Convolutional Neural Networks, and optimization algorithms like Gradient Descent but want to understand how to use use TensorFlow to solve computer vision tasks like Object Localization.الوحدات
Object Localization with TensorFlow
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- Graded Quiz: Test your Project Understanding
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- Object Localization with TensorFlow
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Embark on a dynamic journey into the realm of computer vision with the "Object Localization with TensorFlow" course. This engaging, 2-hour guided project is tailored for individuals who possess a foundational understanding of Python programming and TensorFlow. Dive into the process of creating and training a convolutional neural network that not only classifies but also localizes emojis within images. Unlike object detection, this course simplifies the concept by focusing on single-object localization, making it an excellent stepping stone for more complex tasks. Led by Coursera, this intermediate-level course leverages TensorFlow's Keras API, guiding you through the hands-on application of theoretical knowledge about Neural Networks, Convolutional Neural Networks, and optimization algorithms like Gradient Descent. If you're eager to apply your understanding of these concepts to real-world computer vision challenges, this practical project is your perfect match. Best of all, this course is available for free, making it an accessible and valuable opportunity for those looking to enhance their skills in IT and Computer Science. Join now and start building your proficiency in object localization with TensorFlow!
Amit Yadav