TensorFlow (abreviated TF during this tutorial) is the newest library from Google dedicated to Machine Learning. Although guides describing TF can be find on the official website (www.tensorflow.org), many data scientists find that they lack clarity. For this reason, I started this tutorial series aiming to provide a structured, application orriented to machine learning (ML) using Tensorflow.
I assume that the reader have :
- installed tensorflow ( an uptodate guide from tensorflow.org) or have access to a cloud instance with T
- basic understanding of MachineLearning basic concepts (linear regression , neural networks, convolutional networks – an excellent guide being Stanford Andrew’s NG class)
- intermediate level knowledge of python ( and numy and pandas API for data processing and importing)