You may have noticed that my course Natural Language Processing with Deep Learning in Python has gotten a lot longer recently!
As part of my course revitalization process, I’ve added a significant number of updates to this course.
All students are receiving this announcement because no matter what skill-level you’re currently at, you will get a lot of value from this update.
What has changed?
UPDATES FOR BEGINNERS:
A brand new section called “Beginner’s Corner”. This section requires only basic machine learning knowledge. Know what a feature vector is, and know how to use the SciKit-Learn API.
You will get a taste of what word2vec and GloVe vectors can do.
You can still get a good understanding of what the course is about even if you’re not (yet!) ready to tackle the rest of the course.
UPDATES FOR INTERMEDIATE STUDENTS:
A brand new “Review” section has been added. This section focuses on the bigram model, and several ways to implement it.
1) Just counting. For example, p(heads) = # heads / # total.
2) A single neuron (logistic model). We show how this is equivalent to #1.
3) A neural network model. We show how this actually makes #2 more efficient.
Crucially, this section provides you with all the techniques you need to tackle the next section on word2vec.
The word2vec section has also been completely re-done in order to take advantage of the concepts learned in the Review, making the transition seamless.
Finally, a brand new section on word vectors unifies the word2vec and GloVe sections, giving you a totally new (and in my opinion, better) way of training word2vec.
UPDATES FOR EXPERTS:
Additional theory lectures and Tensorflow code have been added to the RNN and Recursive Neural Network sections. Recall: the latter is a neural network structured like a tree.
Yes, Tensorflow’s capabilities have caught up! We can now do everything in Tensorflow that we’d previously done in Theano.
So if you’ve been avoiding these sections because you didn’t know Theano, now you have no excuse. =)
Hope you enjoy the updates, happy learning!