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diff --git a/tensorflow/docs_src/tutorials/next_steps.md b/tensorflow/docs_src/tutorials/next_steps.md deleted file mode 100644 index 01c9f7204a..0000000000 --- a/tensorflow/docs_src/tutorials/next_steps.md +++ /dev/null @@ -1,36 +0,0 @@ -# Next steps - -## Learn more about TensorFlow - -* The [TensorFlow Guide](/guide) includes usage guides for the - high-level APIs, as well as advanced TensorFlow operations. -* [Premade Estimators](/guide/premade_estimators) are designed to - get results out of the box. Use TensorFlow without building your own models. -* [TensorFlow.js](https://js.tensorflow.org/) allows web developers to train and - deploy ML models in the browser and using Node.js. -* [TFLite](/mobile/tflite) allows mobile developers to do inference efficiently - on mobile devices. -* [TensorFlow Serving](/serving) is an open-source project that can put - TensorFlow models in production quickly. -* The [ecosystem](/ecosystem) contains more projects, including - [Magenta](https://magenta.tensorflow.org/), [TFX](/tfx), - [Swift for TensorFlow](https://github.com/tensorflow/swift), and more. - -## Learn more about machine learning - -Recommended resources include: - -* [Machine Learning Crash Course](https://developers.google.com/machine-learning/crash-course/), - a course from Google that introduces machine learning concepts. -* [CS 20: Tensorflow for Deep Learning Research](http://web.stanford.edu/class/cs20si/), - notes from an intro course from Stanford. -* [CS231n: Convolutional Neural Networks for Visual Recognition](http://cs231n.stanford.edu/), - a course that teaches how convolutional networks work. -* [Machine Learning Recipes](https://www.youtube.com/watch?v=cKxRvEZd3Mw&list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal), - a video series that introduces basic machine learning concepts with few prerequisites. -* [Deep Learning with Python](https://www.manning.com/books/deep-learning-with-python), - a book by Francois Chollet about the Keras API, as well as an excellent hands on intro to Deep Learning. -* [Hands-on Machine Learning with Scikit-Learn and TensorFlow](https://github.com/ageron/handson-ml), - a book by Aurélien Geron's that is a clear getting-started guide to data science and deep learning. -* [Deep Learning](https://www.deeplearningbook.org/), a book by Ian Goodfellow et al. - that provides a technical dive into learning machine learning. |