KDnuggets

JANUARY 16, 2020

With integrations of multiple emerging technologies just in the past year, AI development continues at a fast pace. Following the blueprint of science and technology advancements in 2019, we predict 10 trends we expect to see in 2020 and beyond.

Technology 159

Technology 159

Data Engineering Podcast

JANUARY 13, 2020

Summary The modern era of software development is identified by ubiquitous access to elastic infrastructure for computation and easy automation of deployment. This has led to a class of applications that can quickly scale to serve users worldwide. This requires a new class of data storage which can accomodate that demand without having to rearchitect your system at each level of growth.

SQL 100

SQL PostgreSQL MongoDB Database 100

Uber Engineering

JANUARY 15, 2020

Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform. . As Uber’s operations became more complex and we offered additional features and … The post Engineering SQL Support on Apache Pinot at Uber appeared first on Uber Engineering Blog.

SQL 112

SQL Engineering Aggregated Data Hadoop 112

Confluent

JANUARY 14, 2020

Part 1 of this series discussed the basic elements of an event streaming platform: events, streams, and tables. We also introduced the stream-table duality and learned why it is a […].

Kafka 95

Kafka IT Process Data 95

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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

JANUARY 17, 2020

This article will tell you about the top 9 mobile apps that help the user in learning and practicing data science and hence is improving their productivity.

Data Science 146

Data Science Data 146

Teradata

JANUARY 12, 2020

Learn about the different ways to use R and Python with Vantage and the pros and cons of each option. Read more from our Teradata expert.

Python 80

Python SQL 80

Rockset

JANUARY 17, 2020

In this blog we will set up a real-time SQL API on Kafka using AWS Lambda and Rockset. At the time of writing (in early 2020) the San Francisco 49ers are doing remarkably well! To honor their success, we will focus on answering the following question. What are the most popular hashtags in tweets that mentioned the 49ers in the last 20 minutes? Because Twitter moves fast, we will only look at very recent tweets.

Kafka 40

Kafka SQL AWS Accessible 40

KDnuggets

JANUARY 17, 2020

This summary overviews the keynote at TensorFlow World by Jeff Dean, Head of AI at Google, that considered the advancements of computer vision and language models and predicted the direction machine learning model building should follow for the future.

Machine Learning 131

Machine Learning Building 131

Confluent

JANUARY 16, 2020

Now that we’ve learned about the processing layer of Apache Kafka® by looking at streams and tables, as well as the architecture of distributed processing with the Kafka Streams API […].

Kafka 26

Kafka Architecture Process 26

KDnuggets

JANUARY 16, 2020

This post is about fast-tracking the study and explanation of tree concepts for the data scientists so that you breeze through the next time you get asked these in an interview.

Algorithm 115

Algorithm Data Science Data 115

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

JANUARY 15, 2020

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 115

Programming 115

KDnuggets

JANUARY 13, 2020

Building Machine Learning models is fun, but making sure we build the best ones is what makes a difference. Follow this quick guide to appreciate how to effectively evaluate a classification model, especially for projects where accuracy alone is not enough.

Machine Learning 100

Machine Learning Project Building 100

KDnuggets

JANUARY 15, 2020

In this post I want to show how to use public available (open) data to create geo visualizations in python. Maps are a great way to communicate and compare information when working with geolocation data. There are many frameworks to plot maps, here I focus on matplotlib and geopandas (and give a glimpse of mplleaflet).

Python 90

Python Data 90

KDnuggets

JANUARY 14, 2020

All you need to know about decision trees and how to build and optimize decision tree classifier.

Algorithm 114

Algorithm Building 114

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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

JANUARY 16, 2020

Whereas a data warehouse will need rigid data modeling and definitions, a data lake can store different types and shapes of data. In a data lake, the schema of the data can be inferred when it’s read, providing the aforementioned flexibility. However, this flexibility is a double-edged sword.

Data Lake 66

Data Lake Data Warehouse Data 66

KDnuggets

JANUARY 16, 2020

Visit Deep Learning World, 11-12 May in Munich, to broaden your knowledge, deepen your understanding and discuss your questions with other Deep Learning experts!

Deep Learning 74

Deep Learning 74

KDnuggets

JANUARY 13, 2020

When machine learning tools are developed by technology first, they risk failing to deliver on what users actually need. It can also be difficult for development teams to establish meaningful direction. This article explores the challenges of designing an interface that enables users to visualise and interact with insights from graph machine learning, and explores the very new, uncharted relationship between machine learning and UX.

Machine Learning 70

Machine Learning Designing Technology IT 70

KDnuggets

JANUARY 15, 2020

Which algorithm works best for unbalanced data? Are there any tradeoffs?

Algorithm 105

Algorithm Machine Learning Data 105

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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

JANUARY 13, 2020

Also: The Book to Start You on Machine Learning; An Introductory Guide to NLP for Data Scientists with 7 Common Techniques; A Comprehensive Guide to Natural Language Generation; The Book to Start You on Machine Learning; 10 Python Tips and Tricks You Should Learn Today.

Machine Learning 59

Machine Learning Data Science Data Engineer Data Engineering 59

KDnuggets

JANUARY 14, 2020

Learn the basics of verifying segmentation, analyzing the data, and creating segments in this tutorial. When reviewing survey data, you will typically be handed Likert questions (e.g., on a scale of 1 to 5), and by using a few techniques, you can verify the quality of the survey and start grouping respondents into populations.

Data 58

Data 58

KDnuggets

JANUARY 13, 2020

The new technique can really improve how deep learning models are trained at scale.

Deep Learning 82

Deep Learning 82

KDnuggets

JANUARY 15, 2020

Also: The Book to Start You on Machine Learning - KDnuggets; Top KDnuggets tweets, Jan 1-7: Introduction to #DataVisualization and Storytelling: A Guide For The #DataScientist #eBook; 7 Steps to a Job-winning Data Science Resume - KDnuggets; Tips for open-sourcing research code.

Data Engineer 57

Data Engineer Data Engineering Machine Learning Engineering 57

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

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

JANUARY 13, 2020

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

Building 58

Building Education Data 58

KDnuggets

JANUARY 15, 2020

This year’s NEURIPS-2019 Vancouver conference recently concluded and featured a dozen papers on disentanglement in deep learning. What is this idea and why is it so interesting in machine learning? This summary of these papers will give you initial insight in disentanglement as well as ideas on what you can explore next.

Deep Learning 50

Deep Learning Machine Learning IT 50

KDnuggets

JANUARY 15, 2020

This week: learn the 5 must-have data science skills for the new year; find out which book is THE book to get started learning machine learning; pick up some Python tips and tricks; learn SQL, but learn it the hard way; and find an introductory guide to learning common NLP techniques.

Machine Learning 47

Machine Learning Data Science SQL Python 47

KDnuggets

JANUARY 14, 2020

Here are 7 powerful AI led use cases both for linear television and for OTT apps that are transforming the live sports production landscape.

Machine Learning 52

Machine Learning 52

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

Confluent

JANUARY 13, 2020

This four-part series explores the core fundamentals of Kafka’s storage and processing layers and how they interrelate. In this first part, we begin with an overview of events, streams, tables, […].

Kafka 25

Kafka Process 25

Confluent

JANUARY 15, 2020

Part 2 of this series discussed in detail the storage layer of Apache Kafka: topics, partitions, and brokers, along with storage formats and event partitioning. Now that we have this […].

Kafka 18

Kafka Process 18