Posted on July 20, 2018July 20, 2018Practical Machine Learning at QCon New York 2018 QCon had an amazing machine learning track that presented parctitioners from some of the biggest players in indutry like Pay Pal and Net Flix, but also provided some real world experiences from building data science and machine learning teams, and adding machine learning skills to existing software development teams. Did you know that without using machine learning for fraud detection, Pay Pal would not be possible? Given the currrent scale, growth and rate of attacks, machine learning is the only way to secure the business. At Net Flix they use an interesting approach for ensuring quality of their service, which is based on using machine learning techniques to augment the work of human engineers. The basic idea is not to leave everything to the machines (which is also not possible), but to use machine learning to help human engineers to detect and resolve issues more quickly. It was very interesting to hear how about entire machine learning pipelines used at Door Dash to predict and improve food delivery. One of the key points I liked about this preseentations was advice about evolving machine learning models. In the beggining nobody has enough data, so start with something simple and improve model over time, as th eamount of data increase. In a very interesting talk about team building by Sally Radwan, she discovered that once the company decided to include machine learning, that resulted in 60% of the team change in a period of one year. And interesting thing was that most of the developers left, while managerial positions were stable. That doesn’t have to be rule but be aware of the posibility. Deep Netts platform was presented during a session for application performance tuning using deep learning, whics was very well attended and we got some very usefull feedback. I had a great honour of hosting this track, working with all these great people and I learned a lot alonf the way. So thanks QCon for the great conference!