Women in Tech: How to Build A Human CompanyLuminary Labs
We often think about design in terms of product or service strategy, but what about the design of companies? In the words of Phin Barnes of First Round Capital: “Entrepreneurs are the designers of companies. Great startup CEOs recognize very early that their job is not to build a product, but to build a company — defined by mission, values, and culture.”
Recently, organizations large and small have radically rethought company design by embracing employee-favorable policies such as establishing livable wages, developing creative equity plans, offering paid parental leave policies, and even pulling out of an entire state in protest of discrimination. In addition to sending a strong signal that people come first, these organizations are also making an economic argument to investors that employee-friendly policies pay dividends in reduced turnover and improved business outcome.
In this talk, Sara Holoubek, CEO of Luminary Labs, shares the forces behind this sea change as well as practical examples from companies featured in The Human Company Playbook, including Plated, Etsy, Pinterest, and General Assembly.
The Human Company Playbook, Version 1.0Luminary Labs
Recently, major corporations have radically rethought how they do business by establishing livable wages, developing creative equity plans, offering paid parental leave policies, and even pulling out of an entire state in protest of discrimination. In addition
to sending a strong signal that people come first, these organizations are also making
an economic argument to investors that employee-friendly policies pay dividends in reduced turnover and improved business outcome.
But what about small companies, and what about startups? The playbook aims to answer just that.
Read more: https://medium.com/@sarita/we-don-t-need-more-woman-friendly-companies-27a533b1fb9f#.p5iskl75j
Artificial intelligence (AI) is everywhere, promising self-driving cars, medical breakthroughs, and new ways of working. But how do you separate hype from reality? How can your company apply AI to solve real business problems?
Here’s what AI learnings your business should keep in mind for 2017.
Lightning talk showing various aspectos of software system performance. It goes through: latency, data structures, garbage collection, troubleshooting method like workload saturation method, quick diagnostic tools, famegraph and perfview
JP version - Beyond Shuffling - Apache Spark のスケールアップのためのヒントとコツHolden Karau
The Japanese version of "Beyond Shuffling - Apache Spark のスケールアップのためのヒントとコツ"
皆さんについて
RDD の再利用 (キャッシング、永続化レベル、およびチェックポイント機能)
キー・バリュー・データの処理
group キーの使用が危険な理由と対処方法
Spark アキュムレーターに関するベスト・プラクティス*
Spark SQL がすばらしい理由
Spark MLLib のパフォーマンスを高めるための将来の機能強化に関する説明
38. PySparkの起動
■ PySparkの起動
38
$ cd $SPARK_HOME/bin
$ ./pyspark
Python 2.7.9 (default, Feb 10 2015, 03:28:08)
[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.56)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
Using Spark's default log4j profile: org/apache/spark/log4j-
defaults.properties
15/07/11 13:35:56 INFO SparkContext: Running Spark version 1.4.0
(中略)
Welcome to
____ __
/ __/__ ___ _____/ /__
_ / _ / _ `/ __/ '_/
/__ / .__/_,_/_/ /_/_ version 1.4.0
/_/
Using Python version 2.7.9 (default, Feb 10 2015 03:28:08)
SparkContext available as sc, HiveContext available as sqlContext.
>>>