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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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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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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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Similarity and Dissimilarity Measures in Data Science

Analytics Vidhya

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.

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How Banks Are Winning with AI and Automated Machine Learning

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.

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Behind the Screen: How Netflix Uses Data Science?

Analytics Vidhya

Netflix employs sophisticated data strategies to ensure it’s tough to hit the stop button once you start watching, or you can say Netflix uses Data Science. Yep, your weekend binge […] The post Behind the Screen: How Netflix Uses Data Science? appeared first on Analytics Vidhya.

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Top Data Science Specializations for 2024

Analytics Vidhya

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.

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How Banks Are Winning with AI and Automated Machine Learning

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.

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5 Things a Data Scientist Can Do to Stay Current

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.

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The Forrester Wave™: AI/ML Platforms: Vendor Strategy, Market Presence, and Capabilities Overview

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.

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MLOps 101: The Foundation for Your AI Strategy

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?

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Data Science Fails: Building AI You Can Trust

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.

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5 Things You Always Wanted to Know About Automating Data Science, But Never Asked!

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!

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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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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- (..)