KDnuggets

DECEMBER 3, 2019

What follows is a set of broad recommendations, and it will inevitably require a lot of adjustments in each implementation. Given that caveat, here are our curriculum recommendations.

Data Science 159

Data Science Data IT Education 159

Data Engineering Podcast

DECEMBER 2, 2019

Summary The financial industry has long been driven by data, requiring a mature and robust capacity for discovering and integrating valuable sources of information. Citadel is no exception, and in this episode Michael Watson and Robert Krzyzanowski share their experiences managing and leading the data engineering teams that power the business. They shared helpful insights into some of the challenges associated with working in a regulated industry, organizing teams to deliver value rapidly and re

Data Engineering 100

Data Engineering Data Engineer Engineering Machine Learning 100

Confluent

DECEMBER 5, 2019

Modern Python has very good support for cooperative multitasking. Coroutines were first added to the language in version 2.5 with PEP 342 and their use is becoming mainstream following the […].

Python 19

Python Kafka 19

Netflix Tech

DECEMBER 3, 2019

by David Berg , Ravi Kiran Chirravuri , Romain Cledat , Savin Goyal , Ferras Hamad , Ville Tuulos tl;dr Metaflow is now open-source! Get started at metaflow.org. Netflix applies data science to hundreds of use cases across the company, including optimizing content delivery and video encoding. Data scientists at Netflix relish our culture that empowers them to work autonomously and use their judgment to solve problems independently.

Data Science 95

Data Science Amazon Web Services Machine Learning AWS 95

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In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate

Data Pipeline

KDnuggets

DECEMBER 6, 2019

Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.

Machine Learning 159

Machine Learning Deep Learning Python 159

Teradata

DECEMBER 2, 2019

The cloud’s flexibility is becoming an essential success factor for businesses. But moving your data analytics to the cloud isn't just lift and shift. Read more.

Data Analytics 56

Data Analytics Cloud IT Data 56

Netflix Tech

DECEMBER 2, 2019

Julie (Novak) Beckley, Andy Rhines, Jeffrey Wong, Matthew Wardrop, Toby Mao, Martin Tingley Ever wonder why Netflix works so well when you’re streaming at home, on the train, or in a foreign hotel? Behind the scenes, Netflix engineers are constantly striving to improve the quality of your streaming service. The goal is to bring you joy by delivering the content you love quickly and reliably every time you watch.

Datasets 58

Datasets Data Algorithm Engineering 58

KDnuggets

DECEMBER 4, 2019

What is Explainability in AI and how can we leverage different techniques to open the black box of AI and peek inside? This practical guide offers a review and critique of the various techniques of interpretability.

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Teradata

DECEMBER 4, 2019

Learn how Teradata Vantage and its modern cloud architecture enables companies to leverage 100% of their data to uncover real-time intelligence, at scale.

Cloud 49

Cloud Architecture IT Data 49

KDnuggets

DECEMBER 6, 2019

In this article, I will present five techniques to prevent overfitting while training neural networks.

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145

Speaker: Tamara Fingerlin, Developer Advocate

Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.

Data

KDnuggets

DECEMBER 5, 2019

Increase your confidence to perform data cleaning with a broader perspective of what datasets typically look like, and follow this toolbox of code snipets to make your data cleaning process faster and more efficient.

Datasets 144

Datasets Data Coding Process 144

KDnuggets

DECEMBER 2, 2019

The world still cannot be reduced to numbers on a page because human beings are still the ones making all the decisions. So, the best data scientists understand the numbers and the people. Check out these great data science books that will make you a better data scientist without delving into the technical details.

Data Science 141

Data Science Data 141

KDnuggets

DECEMBER 5, 2019

Deep learning models are revolutionizing the business and technology world with jaw-dropping performances in one application area after another. Read this post on some of the numerous composite technologies which allow deep learning its complex nonlinearity.

Deep Learning 121

Deep Learning Technology IT 121

KDnuggets

DECEMBER 5, 2019

While AI may be the new electricity significant challenges remain to realize AI potential. Here we examine why data scientists and teams can’t rely on software engineering tools and processes for machine learning.

Software Engineering 116

Software Engineering Software Engineer Machine Learning Process 116

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.

Systems

KDnuggets

DECEMBER 2, 2019

The latest release of MobileNets incorporates AutoML and other novel ideas in mobile deep learning.

Deep Learning 115

Deep Learning Machine Learning 115

KDnuggets

DECEMBER 4, 2019

Take part in our latest poll, asking readers their opinions on the effectiveness of current automated machine learning solutions.

Machine Learning 107

Machine Learning 107

KDnuggets

DECEMBER 4, 2019

Let’s say your project is humongous and needs data labeling to be done continuously - while you’re on-the-go, sleeping, or eating. I’m sure you’d appreciate User-generated Data Labeling. I’ve got 6 interesting examples to help you understand this, let’s dive right in!

Data 107

Data Project Data Preparation Data Science 107

KDnuggets

DECEMBER 2, 2019

What are trust and safety? What is the role of trust and security in the modern world? Read this overview of 7 data science application use cases in the realm of trust and security.

Data Science 90

Data Science Data 90

Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives

Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri

Manufacturing

KDnuggets

DECEMBER 3, 2019

Vega and Vega-lite follow in a long line of work that can trace its roots back to Wilkinson’s ‘The Grammar of Graphics.’ Since then VegaLite has come into existence, bringing high-level specification of interactive visualisations to the Vega-Lite world.

IT 90

IT Data 90

KDnuggets

DECEMBER 3, 2019

With deep learning and AI on the forefront of the latest applications and demands for new business directions, additional education is paramount for current machine learning engineers and data scientists. These courses are famous among peers, and will help you demonstrate tangible proof of your new skills.

Deep Learning 87

Deep Learning Education Machine Learning Engineering 87

KDnuggets

DECEMBER 6, 2019

Such as the gross exaggerations Stanford researchers broadcasted about their infamous "AI gaydar" project, there exists a prevalent "accuracy fallacy" in relation to AI from the media. Find out more about how the press constantly misleads the public into believing that machine learning can reliably predict psychosis, heart attacks, sexuality, and much more.

Media 78

Media Machine Learning Project 78

KDnuggets

DECEMBER 4, 2019

The Reinforce AI Conference is coming to Budapest again. Join us Apr 6-7 for the conference days, and optionally Apr 8 for workshops. Stefan Otte returns as a speaker, while Francois Chollet joins this time as well.

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73

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With Airflow being the open-source standard for workflow orchestration, knowing how to write Airflow DAGs has become an essential skill for every data engineer. This eBook provides a comprehensive overview of DAG writing features with plenty of example code. You’ll learn how to: Understand the building blocks DAGs, combine them in complex pipelines, and schedule your DAG to run exactly when you want it to Write DAGs that adapt to your data at runtime and set up alerts and notifications Scale you

Data Engineering

KDnuggets

DECEMBER 6, 2019

Learn how pharma and healthcare organizations are using the power of Natural Language Processing (NLP) to transform unstructured text into actionable structured data.

Process 65

Process Healthcare Structured Data Data 65

KDnuggets

DECEMBER 4, 2019

This week: The Future of Careers in Data Science & Analysis; Task-based effectiveness of basic visualizations; Open Source Projects by Google, Uber and Facebook for Data Science and AI; Getting Started with Automated Text Summarization; A Non-Technical Reading List for Data Science; and much more!

Data Science 61

Data Science Data Project 61

KDnuggets

DECEMBER 5, 2019

Is AI making more good than harm?

Machine Learning 60

Machine Learning 60

Netflix Tech

DECEMBER 2, 2019

Julie (Novak) Beckley, Andy Rhines, Jeffrey Wong, Matthew Wardrop, Toby Mao, Martin Tingley Ever wonder why Netflix works so well when you’re streaming at home, on the train, or in a foreign hotel? Behind the scenes, Netflix engineers are constantly striving to improve the quality of your streaming service. The goal is to bring you joy by delivering the content you love quickly and reliably every time you watch.

Datasets 57

Datasets Data Algorithm Engineering 57

Speaker: Tamara Fingerlin, Developer Advocate

In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!

Data

KDnuggets

DECEMBER 3, 2019

This online course is available – for free – to anyone interested in building practical skills in using data to solve problems better.

Building 55

Building Education Data 55

Netflix Tech

DECEMBER 3, 2019

by David Berg , Ravi Kiran Chirravuri , Romain Cledat , Savin Goyal , Ferras Hamad , Ville Tuulos tl;dr Metaflow is now open-source! Get started at metaflow.org. Netflix applies data science to hundreds of use cases across the company, including optimizing content delivery and video encoding. Data scientists at Netflix relish our culture that empowers them to work autonomously and use their judgment to solve problems independently.

Data Science 54

Data Science Amazon Web Services Machine Learning AWS 54

Netflix Tech

DECEMBER 3, 2019

by David Berg, Ravi Kiran Chirravuri, Romain Cledat, Savin Goyal, Ferras Hamad, Ville Tuulos Continue reading on Netflix TechBlog ».

Data Science 52

Data Science Data Machine Learning Python 52

Netflix Tech

DECEMBER 2, 2019

Julie (Novak) Beckley, Andy Rhines, Jeffrey Wong, Matthew Wardrop, Toby Mao, Martin Tingley Ever wonder why Netflix works so well when you’re streaming at home, on the train, or in a foreign hotel? Behind the scenes, Netflix engineers are constantly striving to improve the quality of your streaming service. The goal is to bring you joy by delivering the content you love quickly and reliably every time you watch.

Datasets 52

Datasets Data Algorithm Engineering 52

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

Software Engineer