Data Engineering Podcast

DECEMBER 8, 2019

Summary Data warehouses have gone through many transformations, from standard relational databases on powerful hardware, to column oriented storage engines, to the current generation of cloud-native analytical engines. SnowflakeDB has been leading the charge to take advantage of cloud services that simplify the separation of compute and storage. In this episode Kent Graziano, chief technical evangelist for SnowflakeDB, explains how it is differentiated from other managed platforms and traditiona

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Data Warehouse Cloud AWS Relational Database 100

Uber Engineering

DECEMBER 10, 2019

Michelangelo , Uber’s machine learning (ML) platform, powers machine learning model training across various use cases at Uber, such as forecasting rider demand , fraud detection , food discovery and recommendation for Uber Eats , and improving the accuracy of … The post Productionizing Distributed XGBoost to Train Deep Tree Models with Large Data Sets at Uber appeared first on Uber Engineering Blog.

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Food Machine Learning Data Engineering 121

KDnuggets

DECEMBER 12, 2019

Python's plotting libraries such as matplotlib and seaborn does allow the user to create elegant graphics as well, but lack of a standardized syntax for implementing the grammar of graphics compared to the simple, readable and layering approach of ggplot2 in R makes it more difficult to implement in Python.

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Python IT Data Science Data 122

Netflix Tech

DECEMBER 10, 2019

Netflix Hack Day?—?Fall 2019 By Tom Richards , Carenina Garcia Motion , and Leslie Posada Hack Day at Netflix is an opportunity to build and show off a feature, tool, or quirky app. The goal is simple: experiment with new ideas/technologies, engage with colleagues across different disciplines, and have fun! We know even the silliest idea can spur something more.

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Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Data Science

Teradata

DECEMBER 11, 2019

Teradata's team of experts are chiming in on their top technology and business predictions for 2020 - from AI to Customer Experience to the Cloud. Read more!

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Cloud Technology 72

Rockset

DECEMBER 9, 2019

As a data engineer, my time is spent either moving data from one place to another, or preparing it for exposure to either reporting tools or front end users. As data collection and usage have become more sophisticated, the sources of data have become a lot more varied and disparate, volumes have grown and velocity has increased. Variety, Volume and Velocity were popularised as the three Vs of Big Data and in this post I’m going to talk about my considerations for each when selecting technologies

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Data Engineering Data Engineer Raw Data Engineering 40

Netflix Tech

DECEMBER 10, 2019

Netflix Hack Day?—?Fall 2019 By Tom Richards , Carenina Garcia Motion , and Leslie Posada Hack Day at Netflix is an opportunity to build and show off a feature, tool, or quirky app. The goal is simple: experiment with new ideas/technologies, engage with colleagues across different disciplines, and have fun! We know even the silliest idea can spur something more.

Technology 52

Technology Project Systems Building 52

Teradata

DECEMBER 9, 2019

Identifying and focusing on priority analytic use cases within your organization will ensure you are asking the right business questions. Find out more.

Data Analytics 61

Data Analytics Data 61

Confluent

DECEMBER 9, 2019

Although starting out with one Confluent Schema Registry deployment per development environment is straightforward, over time, a company may scale and begin migrating data to a cloud environment (such as […].

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Kafka Cloud Data 18

KDnuggets

DECEMBER 9, 2019

The field of Data Science is growing with new capabilities and reach into every industry. With digital transformations occurring in organizations around the world, 2019 included trends of more companies leveraging more data to make better decisions. Check out these next trends in Data Science expected to take off in 2020.

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Data Science Data Cloud Computing Cloud 118

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.

Engineering

Netflix Tech

DECEMBER 10, 2019

Netflix Hack Day?—?Fall 2019 By Tom Richards , Carenina Garcia Motion , and Leslie Posada Hack Day at Netflix is an opportunity to build and show off a feature, tool, or quirky app. The goal is simple: experiment with new ideas/technologies, engage with colleagues across different disciplines, and have fun! We know even the silliest idea can spur something more.

Technology 52

Technology Project Systems Building 52

Teradata

DECEMBER 9, 2019

Identifying and focusing on priority analytic use cases within your organization will ensure you are asking the right business questions. Find out more.

Data Analytics 40

Data Analytics Data 40

KDnuggets

DECEMBER 13, 2019

We show how to build intuitive and useful pipelines with Pandas DataFrame using a wonderful little library called pdpipe.

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Building Data Preparation Python Data 120

KDnuggets

DECEMBER 11, 2019

We asked leading experts - what are the most important developments of 2019 and 2020 key trends in AI, Analytics, Machine Learning, Data Science, and Deep Learning? This blog focuses mainly on technology and deployment.

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Deep Learning Machine Learning Data Science Technology 88

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.

Building

KDnuggets

DECEMBER 12, 2019

The speed at which AI made advancements and news during 2019 makes it imperative now to step back and place these events into order and perspective. It's important to separate the interest that any one advancement initially attracts, from its actual gravity and its consequential influence on the field. This review unfolds the parallel threads of these AI stories over this year and isolates their significance.

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IT 86

KDnuggets

DECEMBER 9, 2019

Here are four common hurdles that need to be overcome before tapping into the benefits of predictive maintenance.

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Machine Learning 110

KDnuggets

DECEMBER 10, 2019

One of the biggest highlights of Grafana is the ability to bring several data sources together in one dashboard with adding rows that will host individual panels. Let's look at installing, configuring, and creating our first dashboard using Grafana.

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Building BI Data 84

KDnuggets

DECEMBER 9, 2019

As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.

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Deep Learning Machine Learning Data Science Technology 83

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KDnuggets

DECEMBER 11, 2019

The second part in a series on leveraging techniques to take a look inside the black box of AI, this guide considers post-hoc interpretation that is useful when the model is not transparent.

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Python 68

KDnuggets

DECEMBER 13, 2019

What is "ultralearning" and how can you follow the strategy to become an expert of data science? Start with this first part in a series that will guide you through this self-motivated methodology to help you efficiently master difficult skills.

Data Science 73

Data Science Data Education 73

KDnuggets

DECEMBER 11, 2019

Math for Programmers teaches you the math you need to know for a career in programming, concentrating on what you need to know as a developer.

Programming 82

Programming 82

KDnuggets

DECEMBER 9, 2019

Also: Data Science Curriculum Roadmap; Enabling the Deep Learning Revolution; The Essential Toolbox for Data Cleaning; A Non-Technical Reading List for Data Science; The Future of Careers in Data Science & Analysis.

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Machine Learning Deep Learning Data Science Coding 62

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

Building

KDnuggets

DECEMBER 10, 2019

Graph machine learning is a developing area of research that brings many complexities. One challenge that both fascinates and infuriates those working with graph algorithms is — scalability. We take a close look at scalability for graph machine learning methods covering what it is, what makes it difficult, and an example of a method that tackles it head-on.

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Machine Learning Algorithm Deep Learning IT 60

KDnuggets

DECEMBER 9, 2019

The new model showed great improvements over the previous AlphaZero agent.

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KDnuggets

DECEMBER 10, 2019

This blog will explain the basics of deploying a machine learning algorithm, focusing on developing a Naïve Bayes model for spam message identification, and using Flask to create an API for that model.

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Machine Learning Algorithm 60

KDnuggets

DECEMBER 12, 2019

This post attempts to summarize my recent detour into NLP, describing how I exposed a Huggingface pre-trained Language Model (LM) on an AWS-based web application.

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AWS 62

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.

Certification

KDnuggets

DECEMBER 12, 2019

ACM SIGKDD Invites Industry and Academic Experts to Submit Advancements in Data Mining, Knowledge Discovery and Machine Learning for 26 th Annual Conference in San Diego.

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Data Mining Data Science Machine Learning Data 51

KDnuggets

DECEMBER 11, 2019

NeurIPS 2019 is underway in Vancouver, and the committee has just recently announced this year's Outstanding Paper Awards. Find out what the selections were, along with some additional info on NeurIPS papers, here.

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KDnuggets

DECEMBER 11, 2019

AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments and Key Trends; Down with technical debt! Clean #Python for #DataScientists; Calculate Similarity?-?the most relevant Metrics in a Nutshell.

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Deep Learning Machine Learning Data Science Python 49

KDnuggets

DECEMBER 12, 2019

Check out this introduction to creating, accessing, and updating dictionaries in Python.

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Python Accessible Accessibility Programming 73

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