gsheni

5 ms·

1. 1.▲
   Synthetic Data for Better Machine Learning(databricks.com)

   5 points by gsheni 3y ago|0 comments
2. 2.▲
   by gsheni 4y ago

   I've been working in the open-source community for six years, and I've learned a lot about what it takes to create successful open-source projects. In this blog post, I share the key lessons that have made the biggest impact on my
3. 3.▲
   Automated feature engineering on a database: Featuretools-SQL(innovation.alteryx.com)

   1 points by gsheni 4y ago|1 comments
4. 4.▲
   by gsheni 4y ago

   Featuretools-SQL: import data from your RDBMS and perform automated feature engineering. Supports SnowFlake, MySQL, Postgres.
5. 5.▲
   Minimal Dependencies of Minimal Dependencies(innovation.alteryx.com)

   6 points by gsheni 4y ago|0 comments
6. 6.▲
   by gsheni 4y ago

   If your dataset has hundreds of columns, do you really want to individually identify the correct type for each column? With Woodwork, an open source library for rich semantic data typing, we made type identification fast, simple, and effort
7. 7.▲
   Type Inference for Natural Language(innovation.alteryx.com)

   9 points by gsheni 4y ago|2 comments
8. 8.▲
   by gsheni 4y ago

   I haven't given much thought to type annotations. pandas recommends using accessors to extend DataFrames (as we do in Woodwork), which are actually just decorators: https://pandas.pydata.org/pandas-docs/stable&#x2F
9. 9.▲
   by gsheni 4y ago

   I’ve been creating an open source library for rich semantic data typing, which helps you managing and communicating data typing information. If you’re curious what this library can do, check out our new blog post!
10. 10.▲
    Woodwork – An Open Source Python Library for Rich Semantic Data Typing(innovation.alteryx.com)

    2 points by gsheni 4y ago|3 comments