Remove Data Preparation Remove Data Wrangling Remove Python
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State of Machine Learning Survey Results Part Two

ODSC - Open Data Science

Machine learning practitioners are often working with data at the beginning and during the full stack of things, so they see a lot of workflow/pipeline development, data wrangling, and data preparation.

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Speed up Your ML Projects With Spark

Towards AI

As a Python user, I find the {pySpark} library super handy for leveraging Spark’s capacity to speed up data processing in machine learning projects. But here is a problem: While pySpark syntax is straightforward and very easy to follow, it can be readily confused with other common libraries for data wrangling.

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Roadmap to Learn Data Science for Beginners and Freshers in 2023

Becoming Human

One is a scripting language such as Python, and the other is a Query language like SQL (Structured Query Language) for SQL Databases. Python is a High-level, Procedural, and object-oriented language; it is also a vast language itself, and covering the whole of Python is one the worst mistakes we can make in the data science journey.

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Why SQL is important for Data Analyst?

Pickl AI

Data Analysts need deeper knowledge on SQL to understand relational databases like Oracle, Microsoft SQL and MySQL. Moreover, SQL is an important tool for conducting Data Preparation and Data Wrangling.

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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. If a reviewer wants more detail, they can always look at the Python module directly.

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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. Python Python’s prominence is expected.

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Integrating custom dependencies in Amazon SageMaker Canvas workflows

AWS Machine Learning Blog

Amazon SageMaker Canvas is a low-code no-code (LCNC) ML platform that guides users through every stage of the ML journey, from initial data preparation to final model deployment. Without writing a single line of code, users can explore datasets, transform data, build models, and generate predictions. The script.py The script.py

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