KDnuggets

OCTOBER 17, 2019

This post aims to make you get started with putting your trained machine learning models into production using Flask API.

Machine Learning 123

Machine Learning Python 123

Uber Engineering

OCTOBER 16, 2019

Michelangelo , Uber’s machine learning (ML) platform, supports the training and serving of thousands of models in production across the company. Designed to cover the end-to-end ML workflow, the system currently supports classical machine learning, time series forecasting, and deep … The post Evolving Michelangelo Model Representation for Flexibility at Scale appeared first on Uber Engineering Blog.

Machine Learning 111

Machine Learning Engineering Designing Systems 111

Data Engineering Podcast

OCTOBER 14, 2019

Summary Managing a data warehouse can be challenging, especially when trying to maintain a common set of patterns. Dataform is a platform that helps you apply engineering principles to your data transformations and table definitions, including unit testing SQL scripts, defining repeatable pipelines, and adding metadata to your warehouse to improve your team’s communication.

Data Warehouse 100

Data Warehouse PostgreSQL AWS Programming Language 100

Confluent

OCTOBER 16, 2019

Trains are an excellent source of streaming data—their movements around the network are an unbounded series of events. Using this data, Apache Kafka ® and Confluent Platform can provide the foundations for both event-driven applications as well as an analytical platform. With tools like KSQL and Kafka Connect, the concept of streaming ETL is made accessible to a much wider audience of developers and data engineers.

Kafka 19

Kafka Building Data Coding 19

Advertisement

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

OCTOBER 16, 2019

This post is about various evaluation metrics and how and when to use them.

Data 123

Data Machine Learning Python 123

Uber Engineering

OCTOBER 16, 2019

Michelangelo , Uber’s machine learning (ML) platform, supports the training and serving of thousands of models in production across the company. Designed to cover the end-to-end ML workflow, the system currently supports classical machine learning, time series forecasting, and deep … The post Evolving Michelangelo Model Representation for Flexibility at Scale appeared first on Uber Engineering Blog.

Machine Learning 110

Machine Learning Engineering Designing Systems 110

Teradata

OCTOBER 15, 2019

Find out how our UX team is going to radically simplify the Teradata user experience. To be unveiled at Teradata Universe!

65

65

KDnuggets

OCTOBER 16, 2019

A guide covering the things you should learn to become a data scientist, including the basics of business intelligence, statistics, programming, and machine learning.

Business Intelligence 123

Business Intelligence Machine Learning Programming Data 123

Dataquest

OCTOBER 16, 2019

Exciting news: we just launched a totally revamped Data Engineering path that offers from-scratch training for anyone who wants to become a data engineer or learn some data engineering skills. Looks cool, right? But it begs the question: why learn data engineering in the first place? Typically, data science teams are comprised of data analysts, data scientists, and data engineers.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 52

Netflix Tech

OCTOBER 18, 2019

Faisal Siddiqi Infrastructure for Contextual Bandits and Reinforcement Learning?—? theme of the ML Platform meetup hosted at Netflix, Los Gatos on Sep 12, 2019. Contextual and Multi-armed Bandits enable faster and adaptive alternatives to traditional A/B Testing. They enable rapid learning and better decision-making for product rollouts. Broadly speaking, these approaches can be seen as a stepping stone to full-on Reinforcement Learning (RL) with closed-loop, on-policy evaluation and model objec

Algorithm 53

Algorithm Architecture Machine Learning Deep Learning 53

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

OCTOBER 14, 2019

As an engineer, scientist, or researcher, you may want to take advantage of this new and growing technology, but where do you start? The best place to begin is to understand what the concept is, how to implement it, and whether it’s the right approach for a given problem.

Technology 122

Technology Engineering IT 122

KDnuggets

OCTOBER 17, 2019

While the average salary for a Software Engineer is around $100,000 to $150,000, to make the big bucks you want to be an AI or Machine Learning (Specialist/Scientist/Engineer.).

Machine Learning 122

Machine Learning Software Engineer Software Engineering Engineering 122

KDnuggets

OCTOBER 18, 2019

Read this quick overview of neural networks and learn how to implement your first in very few lines using Keras.

Coding 119

Coding Python 119

KDnuggets

OCTOBER 18, 2019

If you want to launch your data science skills into freelance work, then check out these important tips to help you kick start your next adventure in data.

Data Science 104

Data Science Data Consulting 104

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

OCTOBER 14, 2019

Selecting the perfect machine learning model is part art and part science. Learn how to review multiple models and pick the best in both competitive and real-world applications.

Machine Learning 100

Machine Learning 100

KDnuggets

OCTOBER 14, 2019

Density estimation is estimating the probability density function of the population from the sample. This post examines and compares a number of approaches to density estimation.

90

90

KDnuggets

OCTOBER 15, 2019

In this research guide, we’ll look at deep learning papers aimed at synthesizing video frames within an existing video.

Deep Learning 87

Deep Learning 87

KDnuggets

OCTOBER 16, 2019

Learn about one of the fundamental theorems of probability with an easy everyday example.

85

85

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

OCTOBER 18, 2019

In this second part we want to outline our own experience building an AI application and reflect on why we chose not to utilise deep learning as the core technology used.

Deep Learning 79

Deep Learning Building Technology Machine Learning 79

KDnuggets

OCTOBER 15, 2019

The way we control our data isn’t working. Data is as vulnerable as ever. Download this white paper, which outlines lessons about how data science and governance programs can, if implemented properly, reinforce each other’s objective.

Government 79

Government Data Governance Data Science Data 79

KDnuggets

OCTOBER 17, 2019

While effective anonymization technology remains elusive, understanding the history of this challenge can guide data science practitioners to address these important concerns through ethical and responsible use of sensitive information.

Data Science 76

Data Science Data Technology 76

KDnuggets

OCTOBER 15, 2019

Even though I’m still in my studies, here’s a list of the most important things I’ve learned (as of yet).

Data Science 75

Data Science Data Education 75

Advertisement

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

OCTOBER 14, 2019

A recent survey outlined the main neural architecture search methods used to automate the design of deep learning systems.

Architecture 72

Architecture Designing Deep Learning Systems 72

KDnuggets

OCTOBER 15, 2019

Follow this step-by-step tutorial using Tensorflow to setup a DC/OS Data Science Engine as a PaaS for enabling distributed multi-node, multi-GPU model training.

Data Science 71

Data Science Data Engineering Cloud Computing 71

KDnuggets

OCTOBER 16, 2019

This week on KDnuggets: Beyond Word Embedding: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI; Activation maps for deep learning models in a few lines of code; There is No Such Thing as a Free Lunch; 8 Paths to Getting a Machine Learning Job Interview; and much, much more.

Deep Learning 65

Deep Learning Machine Learning Coding Data Science 65

KDnuggets

OCTOBER 16, 2019

Also: Kannada-MNIST: A new handwritten digits dataset in ML town; Math for Programmers; The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization; The Last SQL Guide for Data Analysis You’ll Ever Need.

Process 64

Process Datasets Data Science SQL 64

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

OCTOBER 18, 2019

ODSC West comes to San Francisco on Oct 29 - Nov 1. With over 300 hours of content, 200+ speakers, and thousands of attendees, there is certainly a lot to see, learn, and do at the conference. Register by Friday for 10% off your pass.

Data Science 55

Data Science Data 55

KDnuggets

OCTOBER 14, 2019

Also: Activation maps for deep learning models in a few lines of code; The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization; OpenAI Tried to Train AI Agents to Play Hide-And-Seek but Instead They Were Shocked by What They Learned; 10 Great Python Resources for Aspiring Data Scientists.

Data Analysis 55

Data Analysis Deep Learning Process SQL 55

KDnuggets

OCTOBER 17, 2019

Watch UChicago Master of Science in Analytics capstone projects unfold in Real Data, Big Impact and see how students collaborate with their clients to deliver successful analytics projects.

Project 54

Project Data Education 54

Dataquest

OCTOBER 16, 2019

We’ve got some really exciting news: we’ve just launched a total revamp of our Data Engineering learning path ! This revamped path is designed to be more like our other course paths. You can start it even if you have no prior experience with coding , and it’ll take you from total beginner to experienced practitioner with all of the core skills needed to become a data engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering SQL 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