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LLMOps demystified: Why it’s crucial and best practices for 2023

Data Science Dojo

Exploratory Data Analysis (EDA) Data collection: The first step in LLMOps is to collect the data that will be used to train the LLM. This is done by using a machine learning algorithm to learn the patterns in the data. The scope of LLMOps within machine learning projects can vary widely, tailored to the specific needs of each project.

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Ending an Ugly Chapter in Chip Design

Flipboard

The crux of the clash was whether Google’s AI solution to one of chip design’s thornier problems was really better than humans or state-of-the-art algorithms. It pitted established male EDA experts against two young female Google computer scientists, and the underlying argument had already led to the firing of one Google researcher.

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11 Open Source Data Exploration Tools You Need to Know in 2023

ODSC - Open Data Science

ydata-profiling GitHub | Website The primary goal of ydata-profiling is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Algorithm-visualizer GitHub | Website Algorithm Visualizer is an interactive online platform that visualizes algorithms from code.

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I Won $10,000 in a Machine Learning Competition — Here’s My Complete Strategy

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EDA: Know Your Data Here’s where my fintech background became my superpower, and I approached this like any other credit risk problem. Conclusion This competition reinforced something I’ve known for a while: Success in machine learning isn’t about having the fanciest tools or the most complex algorithms.

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How to Work Smarter, Not Harder, with Artificial Intelligence

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Yet, navigating the world of AI can feel overwhelming, with its complex algorithms, vast datasets, and ever-evolving tools. Essential AI Skills Guide TL;DR Key Takeaways : Proficiency in programming languages like Python, R, and Java is essential for AI development, allowing efficient coding and implementation of algorithms.

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Fair Classification with Adversarial Debiasing

Towards AI

Last Updated on October 9, 2023 by Editorial Team Author(s): Lorenzo Pastore Originally published on Towards AI. EDA This member-only story is on us. Upgrade to access all of Medium.

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Roadmap to Learn Data Science for Beginners and Freshers in 2023

Becoming Human

For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis. First learn the basics of Feature Engineering, and EDA then take some different-different data sheets (data frames) and apply all the techniques you have learned to date.