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…)