I participated in PyData Tokyo Meetup # 2-New Data Analysis Infrastructure! The following is a memo that I summarized while listening, so it is not particularly organized.
Amazon Kinesis is a fully managed service that can process high-volume continuous data in real time.
Kinesis Client Library (KCL) now supports ** Python **
The story of AWS + Jubatus was personally interesting. There wasn't much talk about machine learning at AWS re: Invent, so this talk raised my expectations considerably.
This is a story I went to PyData NYC 2014.
――How do you handle big data using Python? ――It seems that PySpark was very hot --Separate data and operations --Unified interface to DB --You can put the data extracted from Mongo into Spark -Advanced Scikit-Learn: A fairly thick tutorial -Beaker Notebook: Notebook that can use various languages at the same time (runs locally) --Python → You can pass variables with JavaScript
The story of SymPy was quite interesting. Is there a demand for Python → Fortran? Actually, I haven't used it yet, but Caffe seems to be very interesting. Let's use it.
This was my first time participating, but I really liked PyData, so it was fun \ (^ o ^) / There are many stories that I can use in my work, so I will try various things. And PyData NYC, I want to go someday. I would also like to participate in the next and subsequent events mm Thank you!
Now that it's a social gathering, you can drink!
Recommended Posts