Fri.Aug 06, 2021

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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

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5 ways for Data Scientists to Code Efficiently in Python

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Writing a code is like a piece of art and. The post 5 ways for Data Scientists to Code Efficiently in Python appeared first on Analytics Vidhya.

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The Role of Model Governance in Machine Learning and Artificial Intelligence

Domino Data Lab

In the world of machine learning (ML) and artificial intelligence (AI), governance is a lifelong pursuit. All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards. As such, model governance needs to be applied to each model for as long as it’s being used.

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Basic Financial Calculations using Python

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Python has become immensely popular these days across many fields. The post Basic Financial Calculations using Python appeared first on Analytics Vidhya.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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The Foundations of a Modern Data-Driven Organisation: Gaining a Clear View of the Customer

Cloudera

Today’s organizations face rising customer expectations in a fragmented marketplace amidst stiff competition. This landscape is one that presents opportunities for a modern data-driven organization to thrive. At the nucleus of such an organization is the practice of accelerating time to insights, using data to make better business decisions at all levels and roles.

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How KNN Uses Distance Measures?

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Hello folks, so this article has the detailed concept of. The post How KNN Uses Distance Measures? appeared first on Analytics Vidhya.

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A Beginners Guide to Machine Learning: Binary Classification of legendary Pokemon using multiple ML algorithms

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon INTRODUCTION Machine Learning is widely used across different problems in real-world. The post A Beginners Guide to Machine Learning: Binary Classification of legendary Pokemon using multiple ML algorithms appeared first on Analytics Vidhya.

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How DAZN Uses Dataiku to Ensure Customer Retention

Dataiku

How can organizations ensure that their customers keep coming back? This is a business problem that DAZN , a forecast streaming service which focuses on live sports (i.e., the Netflix of sports) tackled using Dataiku. Luke Clark , analytics engineer at DAZN, and Andrea Salvati , data scientist at DAZN, walked us through their process in one of Dataiku’s 2021 Product Days sessions.

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MLOps – 5 Steps you Need to Know to Implement a Live Project

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Is your company looking to expand in the area of. The post MLOps – 5 Steps you Need to Know to Implement a Live Project appeared first on Analytics Vidhya.

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Why your Data Visualization Platform should talk to Excel

InsightOut

b' In the business world, the most relevant information is often locked inside reams of data stored in popular data tabulation and analysis software, such as Microsoft Excel.xc2xa0 Excel has matured over time to allow in-ecosystem data calculation and analysis via customizable and in-built formulas. It enables data visualization with its in-built charts feature, including popular chart types like bar graphs, pie charts, histograms, etc.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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The Concept Of Hypothesis Testing in Probability and Statistics!

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction: Hello Learners, Welcome! In this article, we are going to. The post The Concept Of Hypothesis Testing in Probability and Statistics! appeared first on Analytics Vidhya.

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The Role of Model Governance in Machine Learning and AI

Domino Data Lab

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Seven ways to simplify your digital workspace deployment in 2021-Blog 3

Nutanix

A digital workspace requires an enterprise-class hypervisor and a highly performant system for hosting user data. No less important, however, they should be built in and so easy to use that they are practically invisible.

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Adopting the 4 Step Data Science Lifecycle for Data Science Projects

Domino Data Lab

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Driving Business Impact for PMs

Speaker: Jon Harmer, Product Manager for Google Cloud

Move from feature factory to customer outcomes and drive impact in your business! This session will provide you with a comprehensive set of tools to help you develop impactful products by shifting from output-based thinking to outcome-based thinking. You will deepen your understanding of your customers and their needs as well as identifying and de-risking the different kinds of hypotheses built into your roadmap.

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Learning at 200mph – IndyCar Racing

DataRobot

“Winning at 200mph” is the theme for DataRobot’s amazing and unique sponsorship of an Andretti Autosports Indy race car driven by Robert Megennis. The 12-city series of events ranged from the streets of St. Petersburg, Florida, to downtown Toronto, to Portland International Raceway, with the season coming to its end at the Long Beach Grand Prix. Throughout 2021, I went on an adventure of traveling around the country to many racing events learning everything I could about the technology, the peop

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Enterprise MLOps for Model Risk Management

Domino Data Lab