There are 1 repository under data-processing-pipelines topic.
convtools is a specialized Python library for dynamic, declarative data transformations with automatic code generation
Artifician is an event-driven framework designed to simplify and accelerate the process of preparing datasets for Artificial Intelligence models.
Understanding the customer life cycle Acquiring customer data Applying big data concepts to your customer relationships Finding high propensity prospects Upselling by identifying related products and interests Generating customer loyalty by discovering response patterns Predicting customer lifetime value (CLV) Identifying dissatisfied customers Uncovering attrition patterns Applying predictive analytics in multiple use cases Designing data processing pipelines Implementing continuous improvement
A pipeline that consumes twitter data to extract meaningful insights about a variety of topics using the following technologies: twitter API, Kafka, MongoDB, and Tableau.
An open-source Python library for processing and developing End-to-End AI pipelines for Time Series Analysis
Homework assignments for MFF UK course NDBI046 - Introduction to Data Engineering
Notebooks from finance, general practice and Jovian courses on data analysis, ML and DL
Dataset
Codes for data flow between models, data post-process, and visualization
Data Engineering & Software Blog
Experimental libraries - Azure Storage, multithreaded Data Processing pipelines, and many more ...