AnacondaCON February 7-9, Austin Texas http://anacondacon17.io 3-day Anaconda Open Data Science User Conference celebrating a strong Python success story. Hello everyone, It has been 5 years since Peter Wang and I started Continuum Analytics with the objective of expanding the commercial adoption of Python for data-science, quantitative, computational, and numerical computing. Thanks to the amazing community and my colleagues at Continuum we've seen that objective come to fruition and company after company is choosing Python as their forward looking numerical computing modeling and data-science language. We created Anaconda to make it easy for individuals and organizations to adopt the rich suite of tools and libraries that are commonly used by scientists, engineers, and mathematicians. As Anaconda has lowered the barrier for people to adopt the open data science software stack we've seen a significant increase in use by people who previously were unlikely to move beyond Excel, and organizations who are recognizing the kind of value that a strategic investment in Python can bring them. Nearly 8 million people have downloaded Anaconda this year many of whom are using Python for the first time (and choosing Python 3.X). It's been a dream come true to see all of our early efforts around SciPy, NumPy, and Python come to fruition in the enterprise. It's been an incredible journey and is something the Python community can and should celebrate. With that background I am excited to announce AnacondaCON, a 3 day Anaconda user conference happening February 7-9 in Austin Texas. We currently have 2-for-1 pricing until January 16th (2 tickets for $999). We have an amazing line up of speakers from industry, government, academia and, of course, Continuum. https://anacondacon17.io/speakers/ Peter and I will both be speaking there. I will be speaking about the future of open data science including what community-oriented open-source technologies we specifically will be working on and contributing to that continue the success of numpy, scipy, pandas, conda, numba, bokeh, dask, spyder, holoviews, phosphorjs, jupyter, and more. I will also be discussing some ideas we are pursuing on the future of array computing for Python 3.X and how to build a substructure for vector computing that integrates better with the broader Python ecosystem and is inspired by and can use the typing hints becoming popular in Python 3.X. Python's future in technical computing and data science has never been brighter and AnacondaCON is a great opportunity to connect with an interesting segment of this larger community and catch up with others interested in enterprise adoption of Python for data science and numerical / technical computing. I really hope to see you there. Best, Travis Oliphant