KDnuggets

DECEMBER 9, 2019

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

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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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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 99

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 19

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Whether you’re creating complex dashboards or fine-tuning large language models, your data must be extracted, transformed, and loaded. ETL and ELT pipelines form the foundation of any data product, and Airflow is the open-source data orchestrator specifically designed for moving and transforming data in ETL and ELT pipelines. This eBook covers: An overview of ETL vs.

Architecture

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 123

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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Technology Project Systems Building 84

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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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 123

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.

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Data Analytics Data 61

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 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 123

KDnuggets

DECEMBER 10, 2019

From not sweating missing values, to determining feature importance for any estimator, to support for stacking, and a new plotting API, here are 5 new features of the latest release of Scikit-learn which deserve your attention.

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Data Preparation Machine Learning Python Data 123

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 119

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.

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Programming 108

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Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

Cloud

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 106

KDnuggets

DECEMBER 12, 2019

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

Python 101

Python Accessibility Accessible Programming 101

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 98

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 98

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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence

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 90

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.

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Data Science Data Education 85

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

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 79

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

Data

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 77

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 73

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 69

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 64

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

Manufacturing

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 10, 2019

Also: 10 Free Must-read Books on AI; Data Science for Managers: Programming Languages; The Complete Data Science LinkedIn Profile Guide.

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Programming Language Coding Data Science Programming 60

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 59

KDnuggets

DECEMBER 13, 2019

The Machine Learning community must shape the world so that AI is built and implemented with a focus on the entire outcome for our society, and not just optimized for accuracy and/or profit.

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Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

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