Data Science Related Topics 
Analytics Vidhya
FEBRUARY 10, 2024
Introduction Data Science is everywhere in the 21st century and has emerged as an innovative field. But what exactly is Data Science? And why should one consider specializing in it? This blog post aims to answer these questions and more.
Analytics Vidhya
MARCH 14, 2024
Introduction The role of statistics in the dynamic field of data science is foundational, acting as the critical toolset for analyzing and making sense of the vast data landscapes of today. This guide aims to […] The post 9 Best Statistics Books for Data Science in 2024 appeared first on Analytics Vidhya.
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Analytics Vidhya
SEPTEMBER 23, 2023
Introduction Are you eager to dive into data science and sharpen your skills? This article will explore five exciting data science projects with step-by-step solutions. Look no further!
Analytics Vidhya
JUNE 23, 2024
Introduction Data Science deals with finding patterns in a large collection of data. For that, we need to compare, sort, and cluster various data points within the unstructured data. Similarity and dissimilarity measures are crucial in data science, to compare and quantify how similar the data points are.
Advertiser: Data Robot
Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. But times are changing.
Analytics Vidhya
JUNE 14, 2024
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.
Analytics Vidhya
JULY 11, 2024
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.
Advertiser: Data Robot
Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. But times are changing.
Advertiser: Data Robot
Demand for data scientists is surging. With the number of available data science roles increasing by a staggering 650% since 2012, organizations are clearly looking for professionals who have the right combination of computer science, modeling, mathematics, and business skills.
Advertiser: Data Robot
As enterprises evolve their AI from pilot programs to an integral part of their tech strategy, the scope of AI expands from core data science teams to business, software development, enterprise architecture, and IT ops teams.
Advertiser: Data Robot
How can MLOps help data science teams, business leaders, and IT professionals build a resilient and scalable foundation for their AI initiatives? What are the core elements of an MLOps infrastructure? How can MLOps tools deliver trusted, scalable, and secure infrastructure for machine learning projects?
Advertiser: Data Robot
The new DataRobot whitepaper, Data Science Fails: Building AI You Can Trust, outlines eight important lessons that organizations must understand to follow best data science practices and ensure that AI is being implemented successfully. Download the report to gain insights including: How to watch for bias in AI.
Speaker: Judah Phillips, Co-CEO and Co-Founder, Product & Growth at Squark
Automating the sophisticated, complex aspects of data science is now simple with the no-code platform Squark. Judah Phillips, the co-CEO & co-Founder of Squark answers the 5 Things You Always Wanted to Know About Automating Data Science, but Never Asked!
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.
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- (..)
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