I gave a talk at Qcon London this year. Watch it here:
In this video, I introduced word embeddings and the word2vec algorithm. I then proceeded to discuss how the word2vec algorithm is used to create recommendation engines in companies like Airbnb and Alibaba. I close by glancing at real-world consequences of popular recommendation systems like those of YouTube and Facebook.
My Illustrated Word2vec post used and built on the materials I created for this talk (but didn’t include anything on the recommender application of word2vec). This was my first talk at a technical conference and I spent quite a bit of time preparing for it. In the six weeks prior to the conference I spent about 100 hours working on the presentation and ended up with 200 slides. It was an interesting balancing act of trying to make it introductory but not shallow, suitable for senior engineers and architects yet not necessarily ones who have machine learning experience. The Qcon organizers helped prepare us with seminars on giving technical talks. I found those useful.