Mon.Sep 20, 2021

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Machine Learning Model Management: What It Is and Why We Need It

Dataiku

According to the O’Reilly book “Machine Learning Logistics” by Ted Dunning and Ellen Friedman, “90% of the effort in successful machine learning is not about the algorithm or the model or the learning. It’s about logistics.” Many of these logistics fall within the confines of machine learning model management which, without a crystal-clear process in place for, is bound to cause errors (or worse, failures) within a given project.

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Beginner’s Guide to Recursion in Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction: Hello Readers, hope all of you are doing great. In this article, we will be covering all the basics needed for a beginner to start with recursion in python. What is Recursion? In many programs, you must have implemented a function that calls/invokes […]. The post Beginner’s Guide to Recursion in Python appeared first on Analytics Vidhya.

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Start DataOps Today with ‘Lean DataOps’

DataKitchen

Data organizations don’t always have the budget or schedule required for DataOps when conceived as a top-to-bottom, enterprise-wide transformational change. An essential part of the DataOps methodology is Agile Development , which breaks development into incremental steps. DataOps can and should be implemented in small steps that complement and build upon existing workflows and data pipelines.

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Gradient Boosting Algorithm: A Complete Guide for Beginners

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction In this article, I am going to discuss the math intuition behind the Gradient boosting algorithm. It is more popularly known as Gradient boosting Machine or GBM. It is a boosting method and I have talked more about boosting in this article. […]. The post Gradient Boosting Algorithm: A Complete Guide for Beginners appeared first on Analytics Vidhya.

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

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Data-Driven Strategies for Resolving Cyber Threats as a Business Owner

Smart Data Collective

Big data has become an essential asset in the fight against cybercrime. This has caused the demand for cybersecurity professionals with a background in big data to grow. It is important to use the latest data analytics and AI technology to counter these threats if at all possible. Business Owners Lean on Big Data to Deal with Cybercrime Threats. It’s no secret that the COVID pandemic caused a lot of industries to get flipped on their head or at least make some major organizational changes in ord

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Big Announcement – Analytics Vidhya Announces Strategic Funding from Fractal!

Analytics Vidhya

Analytics Vidhya secures $5.5 million (INR 40 crores) investment from Fractal It is with immense pleasure and pride, we announce that Analytics Vidhya has secured a $5.5 million (INR 40 crores) investment from Fractal (fractal.ai) with an aim to train 500,000 Full Stack AI Professionals. Since its inception, Analytics Vidhya has been at the helm […].

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How to use cohort analysis?

Aryng

Cohort analysis is a technique used in several analytical methodologies, including customer analytics, for dividing users into groups with common characteristics. Analyzing these groups, or cohorts, can help companies understand user behavior. Cohort analysis is used to measure engagement of users over a specific period of time. This specific use of a time period enables […] The post How to use cohort analysis?

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Why Data Intensive Graphics Cards Aren’t Just For Gamers

Smart Data Collective

Computers are notoriously dependent on data. Data has always been the backbone of digital technology, even back in the 1970s. As big data has become more impregnated in our lives, its role in computing has grown as well. One of the biggest changes driven by the evolution of big data has involved improvements in graphic cards. Data scientists are investing in new GPUs, which has become easier as they have become more affordable.

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Flexibility and Resiliency Across the Supply Chain

Teradata

The supply chain is not just the sum of its parts. Each function, organization, decision & action are connected & have an effect on each part of the supply chain. Find out more.

IT 52
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Scaling Machine Learning Adoption: A Pragmatic Approach

DataCamp

In this episode of DataFramed, we speak with Noah Gift, founder of Pragmatic AI Labs and prolific author about operationalizing machine learning in organizations and his new book Practical MLOPs.

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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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6.NEXT Breakout Speakers You Don’t Want to Miss!

Nutanix

NEXT 2021 is just around the corner, and it’s time to build your agendas!

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Apache Kafka Deployments and Systems Reliability – Part 1

Cloudera

There are many ways that Apache Kafka has been deployed in the field. In our Kafka Summit 2021 presentation, we took a brief overview of many different configurations that have been observed to date. In this blog series, we will discuss each of these deployments and the deployment choices made along with how they impact reliability. In Part 1, the discussion is related to: Serial and Parallel Systems Reliability as a concept, Kafka Clusters with and without Co-Located Apache Zookeeper, and Kafka

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Data Insights for Everyone — The Semantic Layer to the Rescue

Rocket-Powered Data Science

What is a semantic layer? That’s a good question, but let’s first explain semantics. The way that I explained it to my data science students years ago was like this. In the early days of web search engines, those engines were primarily keyword search engines. If you knew the right keywords to search and if the content providers also used the same keywords on their website, then you could type the words into your favorite search engine and find the content you needed.

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CIOs: Urgent Data Problems

Alation

This last weekend, I asked CIOs two questions: First, what data problems are most urgent for you to solve? And second, what would be the business impact of solving them? The answers reflected various levels of data maturity. But more importantly, the importance of fixing data governance was a core theme. The CIO’s Role in Data. Before we dive in, let’s define the role of the CIO.

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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

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5 Factors to Consider When Choosing Board Reporting Software

Jet Global

The board of directors sits at the pinnacle of every organization. They are the strategic thinkers that see the big picture, ask the important questions, and ultimately guide the company toward success. To do that, they need the right information. Reports to your board must be accurate, timely, and thorough. At the same time, a good board packet should tell a story.