Data Engineering Podcast

SEPTEMBER 9, 2019

Summary The first stage in every data project is collecting information and routing it to a storage system for later analysis. For operational data this typically means collecting log messages and system metrics. Often a different tool is used for each class of data, increasing the overall complexity and number of moving parts. The engineers at Timber.io decided to build a new tool in the form of Vector that allows for processing both of these data types in a single framework that is reliable an

Building 100

Building Kafka Media Data 100

KDnuggets

SEPTEMBER 9, 2019

This is a collection of 10 interesting resources in the form of articles and tutorials for the aspiring data scientist new to Python, meant to provide both insight and practical instruction when starting on your journey.

Python 120

Python Data Programming Data Science 120

Teradata

SEPTEMBER 11, 2019

AI & Deep Learning allow organizations to maximize player performance while minimizing player risk through better insights from performance and wellness data.

Deep Learning 98

Deep Learning Data 98

Rockset

SEPTEMBER 13, 2019

What Is Grafana? Grafana is an open-source software platform for time series analytics and monitoring. You can connect Grafana to a large number of data sources, from PostgreSQL to Prometheus. Once your data source is connected, you can use a built-in query control or editor to fetch data, and build dashboards from your data source. Grafana is frequently deployed for a wide variety of use cases, including DevOps and AdTech.

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PostgreSQL SQL Building Engineering 52

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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

nodeSWAT

SEPTEMBER 9, 2019

Story about unexpected slowdown during AWS RDS upgrade to AWS Aurora and InnoDB adaptive hash index parameter TL;DR at the end. The parameter. MySQL 5.7 documentation about InnoDB adaptive hash index. Turning this parameter ON enables the database engine to analyze index searches and to automatically adapt to the queries/searches you are running. It does so by making custom indexes for these specific cases, in return making your queries run faster because they can now use the automatically gener

AWS 52

AWS MySQL Database SQL 52

KDnuggets

SEPTEMBER 11, 2019

As compute gets cheaper and time to market for machine learning solutions becomes more critical, we’ve explored options for speeding up model training. One of those solutions is to combine elements from Spark and scikit-learn into our own hybrid solution.

Machine Learning 118

Machine Learning Systems Python 118

Confluent

SEPTEMBER 13, 2019

Static Membership is an enhancement to the current rebalance protocol that aims to reduce the downtime caused by excessive and unnecessary rebalances for general Apache Kafka ® client implementations. This applies to Kafka consumers, Kafka Connect, and Kafka Streams. To get a better grasp on the rebalance protocol, we’ll examine this concept in depth and explain what it means.

Kafka 21

Kafka Cloud Metadata Process 21

Netflix Tech

SEPTEMBER 10, 2019

Toby Mao , Sri Sri Perangur , Colin McFarland Another day, another custom script to analyze an A/B test. Maybe you’ve done this before and have an old script lying around. If it’s new, it’s probably going to take some time to set up, right? Not at Netflix. ABlaze: The standard view of analyses in the XP UI Suppose you’re running a new video encoding test and theorize that the two new encodes should reduce play delay, a metric describing how long it takes for a video to play after you press the s

Raw Data 87

Raw Data Python Datasets SQL 87

KDnuggets

SEPTEMBER 12, 2019

It is important to distinguish prediction and classification. In many decision-making contexts, classification represents a premature decision, because classification combines prediction and decision making and usurps the decision maker in specifying costs of wrong decisions.

IT 113

IT Machine Learning Data Science Data 113

KDnuggets

SEPTEMBER 13, 2019

While ensembling techniques are notoriously hard to set up, operate, and explain, with the latest modeling, explainability and monitoring tools, they can produce more accurate and stable predictions. And better predictions can be better for business.

Machine Learning 113

Machine Learning 113

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

SEPTEMBER 10, 2019

How does the scikit-learn machine learning library for Python compare to the mlr package for R? Following along with a machine learning workflow through each approach, and see if you can gain a competitive advantage by knowing both frameworks.

Machine Learning 110

Machine Learning Python 110

KDnuggets

SEPTEMBER 12, 2019

There is no such thing as a free lunch in life or data science. Here, we'll explore some science philosophy and discuss the No Free Lunch theorems to find out what they mean for the field of data science.

Data Science 107

Data Science Data Machine Learning 107

KDnuggets

SEPTEMBER 10, 2019

In this post, I am going to be talking about some of the most important graph algorithms you should know and how to implement them using Python.

Algorithm 119

Algorithm Python Data Data Science 119

KDnuggets

SEPTEMBER 9, 2019

In this blog, Seth DeLand of MathWorks discusses two of the most common obstacles relate to choosing the right classification model and eliminating data overfitting.

Machine Learning 104

Machine Learning Data 104

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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.

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KDnuggets

SEPTEMBER 9, 2019

BERT is changing the NLP landscape and making chatbots much smarter by enabling computers to better understand speech and respond intelligently in real-time.

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104

KDnuggets

SEPTEMBER 13, 2019

This post expands on the NAACL 2019 tutorial on Transfer Learning in NLP organized by Matthew Peters, Swabha Swayamdipta, Thomas Wolf, and Sebastian Ruder. This post highlights key insights and takeaways and provides updates based on recent work.

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KDnuggets

SEPTEMBER 11, 2019

Online hate speech is a complex subject. Follow this demonstration using state-of-the-art graph neural network models to detect hateful users based on their activities on the Twitter social network.

Machine Learning 95

Machine Learning 95

KDnuggets

SEPTEMBER 9, 2019

I am really interested in creating a tight, clean pipeline for disaster relief applications, where we can use something like crowd sourced building polygons from OSM to train a supervised object detector to discover buildings in an unmapped location.

Building 91

Building Data Machine Learning Python 91

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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

SEPTEMBER 9, 2019

In this article, we’ll look at research and model architectures that have been written and developed to do just that using deep learning.

Deep Learning 102

Deep Learning Architecture 102

KDnuggets

SEPTEMBER 9, 2019

Recently, Alphabet’s subsidiaries Waymo and DeepMind partnered to find a more efficient process to train self-driving vehicles algorithms and their work took them back to one of the cornerstones of our history as species: evolution.

Algorithm 86

Algorithm Process 86

KDnuggets

SEPTEMBER 12, 2019

It turned out that, if we ask the weak algorithm to create a whole bunch of classifiers (all weak for definition), and then combine them all, what may figure out is a stronger classifier.

Machine Learning 86

Machine Learning Algorithm IT Python 86

KDnuggets

SEPTEMBER 10, 2019

ODSC has developed a mini-bootcamp, designed to reduce the time and monetary costs of discovering which pathway into data science you should take. In this article, we’ll discuss seven reasons why ODSC’s Mini-Bootcamp might be right for you.

Data Science 83

Data Science Data Designing Education 83

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

SEPTEMBER 11, 2019

Data Driven Government is coming to Washington, DC, Sep 26, and includes a stellar lineup of experts who will share the emerging trends and best practices of government agencies in the current use of data analytics to enhance mission outcomes. Use code KDNUGGETS to get 15% off.

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Government Data Analytics Data Coding 82

KDnuggets

SEPTEMBER 12, 2019

Io-Tahoe, a pioneer in Smart Data Discovery and AI-Driven Data Catalog products, has announced that Clearsense, a scalable data platform as a service built for healthcare, has chosen the smart data discovery platform to automatically discover and catalog relationships across immense amounts of medical and clinical data.

Healthcare 75

Healthcare Medical Data 75

KDnuggets

SEPTEMBER 10, 2019

Also: Top Handy SQL Features for Data Scientists; 12 NLP Researchers, Practitioners & Innovators You Should Be Following; Knowing Your Neighbours: Machine Learning on Graphs.

Machine Learning 71

Machine Learning SQL Data 71

KDnuggets

SEPTEMBER 13, 2019

I am a Git god, why do I need another version control system for Machine Learning Projects?

Machine Learning 98

Machine Learning Datasets Data Science Project 98

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

SEPTEMBER 12, 2019

This article explains the Support Vector Machines (SVM) algorithm in an easy way.

Algorithm 98

Algorithm Machine Learning 98

KDnuggets

SEPTEMBER 9, 2019

Also: Python Libraries for Interpretable Machine Learning; TensorFlow vs PyTorch vs Keras for NLP; Advice on building a machine learning career and reading research papers by Prof. Andrew Ng; Object-oriented programming for data scientists: Build your ML estimator.

Machine Learning 56

Machine Learning Python Programming Data 56

KDnuggets

SEPTEMBER 11, 2019

How one person overcame rejections applying to Data Scientist positions by getting actual data on who is getting hired; Advice from Andrew Ng on building ML career and reading research papers; 10 Great Python resources for Data Scientists; Python Libraries for Interpretable ML,

Python 53

Python Data Building 53

KDnuggets

SEPTEMBER 11, 2019

Python Libraries for Interpretable Machine Learning; How #AI will transform #healthcare (and can it fix US healthcare system?); Building Recommendation System - an overview ; I wasn't getting hired as a Data Scientist. So I sought data on who is.

Healthcare 47

Healthcare Python Machine Learning Systems 47

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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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