MyVidster Tag results for python

high performance python ii
Bookmarked 698 weeks ago
travis oliphantin this tutorial i will cover how to write very fast python code for data analysis i will briefly introduce numpy and illustrate how fast code for python is written in scipy using tools like fwrap f2py and cython i will also d

data analysis in python with pandas
Bookmarked 698 weeks ago
wes mckinneythe tutorial will give a hands-on introduction to manipulating and analyzing large and small structured data sets in python using the pandas library while the focus will be on learning the nuts and bolts of the library039s features i als

plotting with matplotlib
Bookmarked 698 weeks ago
mike mllerwhen it comes to plotting with python many people think about matplotlibit is widely used and provides a simple interface for creating a wide varietyof plots from very simple diagrams to sophisticated animationsthis tutorial is a

tutorial: advanced matplotlib from the library039s author john hunter
Bookmarked 698 weeks ago
in this video tutorial from the 2012 pydata workshop john hunter author of matplotlib is going to give you some advanced insight into the plotting libraryjohn039s tutorial will focus on broader topics concerning a wide set of users including:- customization- configuration- event handling- interacting with figures- tips amp tricks more educational videos on open source at http:marakanacoms

tutorial: scikit-learn - machine learning in python with contributor jake vanderplas
Bookmarked 698 weeks ago
in this video tutorial from pydata workshop jacob vanderplas is going to give you an overview of machine learning in python using scikit-learn he039ll talk about general machine learning concepts as well as walk you through a few exorcises that demonstrate how you can use machine learning technologymore tutorials on open source development at http:marakanacoms

2012 pydata workshop: data analysis in python with pandas
Bookmarked 698 weeks ago
coming from the 2012 pydata workshop wes mckinney cto and cofounder of lambda foundry gives us a tour of pandas a rich data manipulation tool built on top of numpy frustrated with working in r wes started building pandas in 2008 with a focus on fast intuitive data structures and data manipulation capabilities the pandas project has seen huge growth in the last few years and aims to be the ultimate data tool for python more educational resources on open source development at http:marakanacom see the rest of the presentations from the 2012 pydata workshop here - http:mrknco3tkq2

2012 pydata workshop: boosting numpy with numbexpr and cython
Bookmarked 698 weeks ago
in this video from the 2012 pydata workshop francesc alted from continuum analytics is going to show you how you can boost numpy with numbexpr and cythontopics covered include:- the era of big data- numpy and its ecosystem- numexpr- cython more educational resources on open source development at http:marakanacom

brisk: truly peer-to-peer hadoop
Bookmarked 698 weeks ago
in this presentation given at the san francisco java user group on june 14 2011 srisatish ambati chief java tinkerer at datastax is going to show you how to run hadoop mapreduce on a truly peer-to-peer storage layer powered by cassandra fsbrisk is an open-source hadoop amp hive distribution that uses apache cassandra for its core services and storage brisk makes it possible to run hadoop mapreduce on top of cassandrafs an hdfs-compatible storage layer by replacing hdfs with cassandrafs users leverage mapreduce jobs on cassandra039s peer-to-peer fault-tolerant and scalable architecturewith cassandrafs all nodes are peers data files can be loaded through any node in the cluster and any node can serve as the jobtracker for mapreduce jobs hive metastore is stored amp accessed as just another column family table on the distributed data store brisk makes hadoop truly peer-to-peer we demonstrate visualization amp monitoring of brisk using opscenter the operational simplicity of cassandra039s multi-datacenter amp multi-region aware replication makes brisk well-suited for a rich set of applications and use-cases and by being able to store and isolate hdfs amp online data within the same data cluster brisk makes analytics possible without etl check out the slides at http:mrkncof383