Wed.Aug 24, 2022

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7 Techniques to Handle Imbalanced Data

KDnuggets

This blog post introduces seven techniques that are commonly applied in domains like intrusion detection or real-time bidding, because the datasets are often extremely imbalanced.

Datasets 159
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Reinforcement Learning for Budget Constrained Recommendations

Netflix Tech

by Ehtsham Elahi with James McInerney , Nathan Kallus , Dario Garcia Garcia and Justin Basilico Introduction This writeup is about using reinforcement learning to construct an optimal list of recommendations when the user has a finite time budget to make a decision from the list of recommendations. Working within the time budget introduces an extra resource constraint for the recommender system.

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The Bias-Variance Trade-off

KDnuggets

Understanding how these prediction errors work and how they can be used will help you build models that are not only accurate and perform well - but also avoid overfitting and underfitting.

Building 104
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Wolt loves open-source software

Wolt

Here at Wolt we truly love open-source software. We’re a fast-growing company, building the rocket ship while riding it to allow our business to scale. This wouldn’t be possible without standing on the shoulders of giant open-source projects. Almost our whole tech stack is based on open-source software, most notably on the data engineering side.

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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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KDnuggets News, August 24: Implementing DBSCAN in Python • How to Avoid Overfitting

KDnuggets

Implementing DBSCAN in Python • How to Avoid Overfitting • Simplify Data Processing with Pandas Pipeline • How to Use Data Visualization to Add Impact to Your Work Reports and Presentations • The Data Quality Hierarchy of Needs.

Python 84
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Daniel Kahneman and Nate Silver to Headline IMPACT: The Data Observability Summit

Monte Carlo

What do Daniel Kahneman, the Nobel Prize-winning psychologist, economist, and author of Thinking, Fast and Slow , and Nate Silver, founder and editor-in-chief of opinion poll analysis website FiveThirtyEight , have in common? Not only are they two of the most interesting voices in data, but they’re speaking at IMPACT: The Data Observability Summit , from October 25-26, 2022.

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Building Custom Runtimes with Editors in Cloudera Machine Learning

Cloudera

Cloudera Machine Learning (CML) is a cloud-native and hybrid-friendly machine learning platform. It unifies self-service data science and data engineering in a single, portable service as part of an enterprise data cloud for multi-function analytics on data anywhere. CML empowers organizations to build and deploy machine learning and AI capabilities for business at scale, efficiently and securely, anywhere they want.

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Custom Directive In Angular

U-Next

Introduction. Among the most popular programming interfaces is Angular, a part of the JavaScript environment, and Google introduced it in 2009. 30.7 % of software engineers use AngularJS and its revised edition, Angular 2, to construct interface design, per a recent StackOverflow survey. The custom directive in Angular 2 is next-level functional and feature-rich.

Banking 40
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An introduction to unit testing your dbt Packages

dbt Developer Hub

Editors note - this post assumes working knowledge of dbt Package development. For an introduction to dbt Packages check out So You Want to Build a dbt Package. It’s important to be able to test any dbt Project, but it’s even more important to make sure you have robust testing if you are developing a dbt Package. I love dbt Packages, because it makes it easy to extend dbt’s functionality and create reusable analytics resources.

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Iterate Dictionary Python

U-Next

Introduction. When utilizing collections in Python, you may retrieve an item using an index, which is a number that indicates where the element is located in the list. For each consecutive entry in the list, the index rises by one, starting at 0 for the very first component. An illustration may be seen right here, but if we have to preserve this “link” in our code and save two interrelated value systems?

Python 40
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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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All There Is To Know About Reinforcement Learning in Machine Learning

U-Next

Introduction. Artificial intelligence is expanding rapidly, with a 7.35 billion US dollar size of the market anticipated. According to McKinsey , deep learning and reinforced learning is two AI methodologies that have the potential to produce from $3.5T and $5.8T in value each year across nine business operations in 19 sectors. While Machine Learning is sometimes viewed as monolithic, it has several subs, including computer vision, Machine Learning, and the trying to cut reinforcement learning t

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What Is Data Abstraction?

U-Next

Introduction. Only the most pertinent information is shown to the user when data abstraction is in place. The user does not see the extra or unnecessary units. For instance, rather than its parts, an automobile is seen as a whole. Data abstraction is known as the technique of recognizing only the necessary aspects of an item while discarding the extraneous features.

Data 40