TensorFlow Slim Tutorial for Beginners 🚩 TensorFlow Full Course ⚡️

About This Course
TF-Slim is a library that simplifies the process of building and training complex TensorFlow models. This course is designed for individuals with some prior TensorFlow experience who want to learn how to use TF-Slim. It is recommended that learners have a basic understanding of data science and deep learning theory. By taking this course, you will learn how to build maintainable and easy-to-read deep learning models using TF-Slim's wrapper functions. You will also gain experience with loss functions, optimizers, and regularizers, as well as learn how to fine-tune pre-trained models and implement routings for model training and evaluation. Finally, you will learn how to build and train feedforward neural networks and develop image and text classification models.

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Introduction
0:00:00 Welcome To The Course

TensorFlow-Slim Wrapper Functions
0:04:58 Variables In TensorFlow-Slim
0:17:34 Layers In TensorFlow-Slim: Part - 1
0:27:02 Layers In TensorFlow-Slim: Part - 2
0:31:47 Scopes In TensorFlow-Slim: Part - 1
0:45:42 Scopes In TensorFlow-Slim: Part - 2

Defining Deep Neural Network Models
0:52:41 Multilayer Feedforward Neural Network In TensorFlow-Slim: Part - 1
0:58:50 Multilayer Feedforward Neural Network In TensorFlow-Slim: Part - 2
1:04:18 Tensorflow
1:04:23 Download And Visualize The Flower Dataset With TensorFlow-Slim
1:10:09 Deep Convolutional Neural Network With TensorFlow-Slim
1:17:22 Download And Explore The DBpedia Dataset
1:21:29 Text Convolutional Neural Network With TensorFlow-Slim

Conclusion
1:36:42 Wrap Up And Thank You


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