Opiniones y comentarios de aprendices correspondientes a TensorFlow for CNNs: Multi-Class Classification por parte de Coursera Project Network
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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 how to build a multi-class Classifier in CNNs using a pre-trained model trained on the much larger dataset, and you will learn practically how to solve a multi-image classification deep learning task in the real world and create, train, and test a neural network with Tensorflow using real-world images, and you will get a bonus deep learning exercise implemented with Tensorflow. By the end of this project, you will have learned how to build a multi-class classifier in convolutional neural networks 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 building multi-class classifier using convolutional neural networks 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 project. 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....
1 - 3 de 3 revisiones para TensorFlow for CNNs: Multi-Class Classification
por DEXTER J V
28 de oct. de 2020
Thank you for this online course very informative .
por Priscila A B
24 de nov. de 2020
por Bryan R
12 de abr. de 2021
Course was easily understood, however, some of the questions on the exam were not clear and could use some polishing.