This page lists some selected good posts from Dr. Andy Thomas’s great machine learning and TensorFlow blog. Check here for his GitHub repo for all the code involved on his blog.
- Python TensorFlow Tutorial – Build a Neural Network (pdf). You will get a pretty good sense of how TensorFlow works.
- If you have played with machine learning and TensorFlow for a while, I recommend reading his tips and tricks post (pdf).
- See his another post Convolutional Neural Networks Tutorial in TensorFlow (pdf) for a very good illustration and explanation about how CNN works and it is implementation in TensorFlow.
- Neural Networks Tutorial – A Pathway to Deep Learning (pdf). This post describes essential concepts involved in deep learning. The good thing is that for most concepts it provides Python code snippets.
- If you would like to dive into and to really get to know how Gradient Descent (It is a very important algorithm in machine learning and deep learning) works, check out his post: Stochastic Gradient Descent – Mini-batch and more (pdf).
- Keras tutorial – build a convolutional neural network in 11 lines (pdf) (May 17, 2017) provides a pretty good explanation of how to build a CNN model using Keras along with code snippet. The full code of this Keras tutorial can be found here.
- Word2Vec word embedding tutorial in Python and TensorFlow (pdf)(July 21, 2017) provides a nice introduction to what is Word2Vec and why we need Word2Vec, as well as a python tutorial for Word2Vec in TensorFlow.
- Check out this post (August 3, 2017) for a tutorial (in Python) for Microsoft CNTK to build a neural network (pdf).
- An introduction to TensorFlow queuing and threading (pdf) (August 12, 2017)
(more coming soon…)