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5 Quirky Data Science Projects to Impress

KDnuggets

Develop unique yet standing-out data science projects to improve your data portfolio.

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Mathematics for Data Science

Analytics Vidhya

Introduction Mathematics is a way of uncovering possible insights or information from data as done in the field of Data Science. So data science is a vast and a type of mixed field of statistical analysis, computer science, and domain expertise.

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7 Steps to Mastering Math for Data Science

KDnuggets

Want to learn math for data science? This guide will help you go about learning math for data science—linear algebra, calculus, statistics, and more.

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5 Hidden Gem Python Libraries for Data Science

KDnuggets

Exploring the not-so-famous data science libraries that can be useful in your data workflow.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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Top 10 Platforms to Practice Data Science Skills

Analytics Vidhya

Introduction Data science is one of the professions in high demand nowadays due to the growing focus on analyzing big data. Hypothesis and conclusion-making from data broadly involve technical and non-technical skills in the interdisciplinary field of data science.

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Top 10 Data Science Alternative Career Paths

Analytics Vidhya

Introduction Data science’s abilities are so versatile that they open up various job alternatives. Thus, in the rapidly developing field of data science, such […] The post Top 10 Data Science Alternative Career Paths appeared first on Analytics Vidhya.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Greg Loughnane and Chris Alexiuk in this exciting webinar to learn all about: How to design and implement production-ready systems with guardrails, active monitoring of key evaluation metrics beyond latency and token count, managing prompts, and understanding the process for continuous improvement Best practices for setting up the proper mix of open- (..)