From aa9b5dcff5dfbfba3e6a10f092d81774299ed378 Mon Sep 17 00:00:00 2001 From: Amil Khanzada Date: Sun, 2 Feb 2020 14:21:27 -0800 Subject: [PATCH] README.md: add links to tutorials 1-7 --- README.md | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index 9b3309c..92b20ba 100644 --- a/README.md +++ b/README.md @@ -9,39 +9,39 @@ I will try to make the tutorials accessible for everyone, thus I will try to wor ### List of tutorials available: #### Getting started --- -* **01. Build a simple neural network** - This tutorial shows you how to build and train a one-hidden layer neural network using the Eager mode of TensorFlow, on a synthetically generated dataset. +* [**01. Build a simple neural network**](01_simple_feedforward_neural_network.ipynb) - This tutorial shows you how to build and train a one-hidden layer neural network using the Eager mode of TensorFlow, on a synthetically generated dataset. -* **02. Using metrics in Eager mode** - This tutorial shows you how to use metrics +* [**02. Using metrics in Eager mode**](02_using_metrics_in_eager_mode.ipynb) - This tutorial shows you how to use metrics that are compatible with Eager mode, for three types of machine learning problems (multi-classification, imbalanced dataset and regression). #### Simple but useful stuff --- -* **03. Save and restore a trained model** - Simple tutorial on how you can save a trained model and restore it at a later time to make predictions on new data. +* [**03. Save and restore a trained model**](03_save_and_restore_model.ipynb) - Simple tutorial on how you can save a trained model and restore it at a later time to make predictions on new data. -* **04. Transfer text data to TFRecords** - This tutorial shows you how to store text data of variable sequence length to TFRecords. The data can be easily padded +* [**04. Transfer text data to TFRecords**](04_text_data_to_tfrecords.ipynb) - This tutorial shows you how to store text data of variable sequence length to TFRecords. The data can be easily padded on the fly, within a batch, when reading the dataset with an iterator. -* **05. Transfer image data to TFRecords** - Easy and simple tutorial on how to transfew image data and its metadata (e.g. target) to TFRecords. +* [**05. Transfer image data to TFRecords**](05_images_to_tfrecords.ipynb) - Easy and simple tutorial on how to transfew image data and its metadata (e.g. target) to TFRecords. -* **06. How to read TFRecords data in batches** - This tutorial shows you how to read either variable length sequence data or image data, in batches, from TFRecords. +* [**06. How to read TFRecords data in batches**](06_read_data_in_batches_from_tfrecords.ipynb) - This tutorial shows you how to read either variable length sequence data or image data, in batches, from TFRecords. #### Convolutional neural networks ---- -* **07. Build a CNN for emotion recognition** - This tutorial shows you how to build a CNN from scratch using the TensorFlow Eager API and the FER2013 dataset. At the end of the tutorial you will be able to test the network on yourself using a webcam. Very fun exercise! +* [**07. Build a CNN for emotion recognition**](07_convolutional_neural_networks_for_emotion_recognition.ipynb ) - This tutorial shows you how to build a CNN from scratch using the TensorFlow Eager API and the FER2013 dataset. At the end of the tutorial you will be able to test the network on yourself using a webcam. Very fun exercise! #### Recurrent neural networks ---- -* **08. Build a dynamic RNN for sequence classification** - Learn how to work with variable sequence input data. This tutorial shows you how to build a dynamic RNN using the TensorFlow Eager API and the Stanford Large Movie Review Dataset. +* [**08. Build a dynamic RNN for sequence classification**](08_dynamic_recurrent_neural_networks_for_sequence_classification.ipynb) - Learn how to work with variable sequence input data. This tutorial shows you how to build a dynamic RNN using the TensorFlow Eager API and the Stanford Large Movie Review Dataset. -* **09. Build a RNN for time series regression** - Learn how to build a RNN for timeseries forecasting. +* [**09. Build a RNN for time series regression**](09_recurrent_neural_networks_for_time_series_regression.ipynb) - Learn how to build a RNN for timeseries forecasting.