摘要： In the banking or pharmacy industry where regulations compel companies to have good governance in place, in industries such as publishing and telecom Data Governance often seems complicated and theoretical. That’s according to Sara Willovit, Product Data Governance at Becton Dickenson.
摘要： Data can be anywhere. Companies store data in the cloud, in data warehouses, in data lakes, on old mainframes, in applications, on drives — even on paper spreadsheets. Every day we create 2.5 quintillion bytes of data, and there are no signs of this slowing down anytime soon.
摘要： To build an effective learning model, it is must to understand the quality issues exist in data & how to detect and deal with it. In general, data quality issues are categories in four major sets.
摘要： Below picture represents the machine learning & data mining process in general. Data cleaning and Feature extraction is the most tedious job but you need to be good at it make your model more accurate.
摘要： Bayesian Target Encoding is a feature engineering technique used to map categorical variables into numeric variables. The Bayesian framework requires only minimal updates as new data is acquired and is thus well-suited for online learning. Furthermore, the Bayesian approach makes choosing and interpreting hyperparameters intuitive. I developed this technique in the recent Avito Kaggle Competition, where my team and I took 14th place out of 1,917 teams. We found that the Bayesian target encoding outperforms the built-in categorical encoding provided by the LightGBM package.
摘要： It is important to actually work on different kinds of data and projects along with learning the data science concepts. Some datasets are very popular and a lot more are easily available on the web
摘要： DataStax Apache Cassandra as a Service, a Database as a Service offering, and DataStax Insights, a performance management service, to be first of platform’s offerings built to simplify application development
Summary： Many think performance problems don’t exist in the cloud, but they do. Deal with them the same way you did before cloud. 許多人以為雲端不存在性能問題，但這些問題確實存在。
