Data Quality Document Machine Learning 
DataKitchen
NOVEMBER 5, 2024
The Race For Data Quality In A Medallion Architecture The Medallion architecture pattern is gaining traction among data teams. It is a layered approach to managing and transforming data. It sounds great, but how do you prove the data is correct at each layer? How do you ensure data quality in every layer ?
O'Reilly on Data
DECEMBER 19, 2018
We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.
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O'Reilly on Data
JULY 15, 2019
As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. Machine learning developers are beginning to look at an even broader set of risk factors. Sources of model risk.
O'Reilly on Data
DECEMBER 12, 2019
For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes.
O'Reilly on Data
NOVEMBER 19, 2024
Here’s a simple rough sketch of RAG: Start with a collection of documents about a domain. Split each document into chunks. One more embellishment is to use a graph neural network (GNN) trained on the documents. Chunk your documents from unstructured data sources, as usual in GraphRAG. at Facebook—both from 2020.
Smart Data Collective
SEPTEMBER 29, 2022
One study by Think With Google shows that marketing leaders are 130% as likely to have a documented data strategy. Data strategies are becoming more dependent on new technology that is arising. One of the newest ways data-driven companies are collecting data is through the use of OCR.
O'Reilly on Data
MARCH 24, 2020
If you’re basing business decisions on dashboards or the results of online experiments, you need to have the right data. On the machine learning side, we are entering what Andrei Karpathy, director of AI at Tesla, dubs the Software 2.0 Data professionals spend an inordinate amount on time cleaning, repairing, and preparing data.
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