Interesting Things I Learned at SciPy 2016

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.

mplstereonet - Provides lower-hemisphere equal-area and equal-angle stereonets for matplotlib.

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.

ipywidgets - Interactive HTML widgets for Jupyter notebooks and the IPython kernel. 

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.

spearmint - A software package to perform Bayesian optimization.

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.