Remove Business Intelligence Remove Citizen Data Scientist Remove Python
article thumbnail

An open-source, low-code Python wrapper for easy usage of the Large Language Models such as…

Mlearning.ai

An open-source, low-code Python wrapper for easy usage of the Large Language Models such as ChatGPT, AutoGPT, LLaMa, GPT-J, and GPT4All An introduction to “ pychatgpt_gui” —  A GUI-based APP for LLM’s with custom-data training and pre-trained inferences. It is an open-source python package. Students and Teachers.

Python 52
article thumbnail

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East…

ODSC - Open Data Science

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Well, these libraries will give you a solid start. Register for free!

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

The Modern Data Stack Explained: What The Future Holds

Alation

A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means.

article thumbnail

Data science

Dataconomy

Roles of data professionals Various professionals contribute to the data science ecosystem. Data scientists are the primary practitioners, employing methodologies to extract insights from complex datasets. Essential technical skills Data preparation and mining: Proficiency in cleaning and organizing data effectively.