I am currently at Scipy
2016 conference, so this week's blog I will try to list some of the
interesting things I learned from Scipy conference. The conference is from July
12th to July 17th at Austin TX. Here are the interesting things I learned:
July 13th 2016
Jupyter dashbord - Extension
for Jupyter Notebook that enables the layout and presentation of dashboards
from notebooks.
Jupyterlab - A computational environment. This is
a very early preview, and is not suitable for general usage yet. But nice to
checkout now.
altair - This is a declarative statistical visualization library for
Python.
geopandas - GeoPandas extends the datatypes
used by pandas to allow spatial operations on geometric types.
yt - A python package for analyzing and visualizing volumetric,
multi-resolution data from astrophysical simulations, radio telescopes, and a
burgeoning interdisciplinary community.
Glumpy - A python library for scientific visualization
that is both fast, scalable and beautiful.
tpot - A python tool that
automatically creates and optimizes machine learning pipelines using genetic
programming.
The best part of today's
conference is that I talked a lot with Sebastian Raschka about Machine
learning, and he gave me many great suggestions ^)^ Check out his book if you
want to do machine learning with python - Python
Machine Learning, which is a very nice book if you want to do machine
learning quick.
July 14th 2016
HDBSCAN - Hierarchical Density-Based Spatial
Clustering of Applications with Noise.
lightning - A framework for data visualization providing API-based
access to reproducible, web-based, interactive visualizations.
binder - Turn a GitHub repo into a collection of interactive
notebooks.
cesium - Open-Source Machine Learning for Time Series Analysis.
dask - A flexible parallel computing library for analytics, it can 'deal with' big data even on a single machine.
simpeg - An open source python package for simulation and gradient based parameter estimation in geophysical applications.
steno3d - Visualize 3d data, but it is not free if data size over certain limit.
Intel Python distribution - It is said to boost the performance of the packages.
HPX-5 - A distributed programming model allowing programs to run unmodified on systems from a single SMP to large clusters and supercomputers with thousands of nodes.
loopy - A code generator for array-based code in the OpenCL/CUDA execution model.
Sensor Data Management System - Public sensor data.
resampy - Efficient resampling for the audio data.
datalore - An intelligent, cloud-based computational workbook with collaborative support. (require sign up).
sharedmem - A different flavor of multiprocessing in Python.
July 15th 2016
datashader - A graphics pipeline system for
creating meaningful representations of large amounts of data.
canopy-geo - Python-based analysis environment for geophysics.
nbflow - A tool that supports
one-button reproducible workflows with the Jupyter Notebook and Scons.
auto-sklearn - An automated machine
learning toolkit and a drop-in replacement for a scikit-learn estimator.
hyperopt-sklearn - Hyperopt based model selection among
machine learning algorithms in scikit-learn.
scikit-optimize - A simple and efficient
library for model-based optimization, accessible to everybody and reusable in
various contexts.
symengine - A fast symbolic manipulation library, written in C++.
nbdime - Tools for diffing and merging of Jupyter notebooks.
flexx - Write desktop and web apps in pure python.
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