TensorFlow for CNNs: Object Recognition

ofrecido por
Coursera Project Network
En este proyecto guiado, tú:

Learn the fundamentals of Object Recognition algorithms

Learn how to build deep learning object recognition models

Learn how to create a convolutional neural network with Tensorflow

Clock2 hours
IntermediateIntermedio
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

This guided project course is part of the "Tensorflow for Convolutional Neural Networks" series, and this series presents material that builds on the second course of DeepLearning.AI TensorFlow Developer Professional Certificate, which will help learners reinforce their skills and build more projects with Tensorflow. In this 2-hour long project-based course, you will learn In this project, you will learn practically how to build an object recognition model in computer vision with real-world applications, and you will create your own object recognition algorithm with TensorFlow using real data, and you will get a bonus deep learning exercise implemented with Tensorflow. By the end of this project, you will have learned the fundamentals of object recognition and created a deep learning model with TensorFlow on a real-world dataset. This class is for learners who want to learn how to work with convolutional neural networks and use Python for solving object recognition tasks with TensorFlow, and for learners who are currently taking a basic deep learning course or have already finished a deep learning course and are searching for a practical deep learning project with TensorFlow. Also, this project provides learners with further knowledge about creating and training convolutional neural networks and improves their skills in Tensorflow which helps them in fulfilling their career goals by adding this project to their portfolios.

Habilidades que desarrollarás

Deep LearningConvolutional Neural NetworkObject RecognitionTensorflowComputer Vision

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  1. Introduction and overview of the project

  2. Import Libraries and Download the Dataset

  3. Setup Data Dimensions and Plot Images

  4. Data preparation and configuration of the Model

  5. Create and Build the Neural Network

  6. Train the Neural Network

  7. Visualize the Results and Test the Model

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

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