Remove Azure Remove Data Preparation Remove Data Wrangling
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Speed up Your ML Projects With Spark

Towards AI

Image generated by Gemini Spark is an open-source distributed computing framework for high-speed data processing. It is widely supported by platforms like GCP and Azure, as well as Databricks, which was founded by the creators of Spark. This practice vastly enhances the speed of my data preparation for machine learning projects.

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Roadmap to Learn Data Science for Beginners and Freshers in 2023

Becoming Human

There is a position called Data Analyst whose work is to analyze the historical data, and from that, they will derive some KPI s (Key Performance Indicators) for making any further calls. For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis.

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Must-Have Prompt Engineering Skills for 2024

ODSC - Open Data Science

Databricks: Powered by Apache Spark, Databricks is a unified data processing and analytics platform, facilitates data preparation, can be used for integration with LLMs, and performance optimization for complex prompt engineering tasks. Kubernetes: A long-established tool for containerized apps.

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How to Use Exploratory Notebooks [Best Practices]

The MLOps Blog

Example template for an exploratory notebook | Source: Author How to organize code in Jupyter notebook For exploratory tasks, the code to produce SQL queries, pandas data wrangling, or create plots is not important for readers. in a pandas DataFrame) but in the company’s data warehouse (e.g., documentation. Aside neptune.ai

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