Tensorflow for Deep Learning Research | Stanford University

Learn the fundamentals of TensorFlow for deep learning research. Build models for tasks like word embeddings, translation, and optical character recognition.

Introduction

This course covers the fundamentals and contemporary usage of the Tensorflow library for deep learning research. Students will learn how to build and structure models best suited for deep learning projects, using Tensorflow to build models of different complexity, from simple linear/logistic regression to convolutional neural network and recurrent neural networks with LSTM.

Highlights

• Understand the graphical computational model of Tensorflow
• Explore the functions Tensorflow has to offer
• Build models for tasks such as word embeddings, translation, optical character recognition
• Learn best practices to structure a model and manage research experiments

Recommendation

This course is well-suited for students interested in deep learning research and the practical application of Tensorflow. The hands-on approach and focus on building models of increasing complexity make it a great choice for those looking to gain expertise in Tensorflow and deep learning.