Data Engineering Podcast

JULY 28, 2019

Summary The ETL pattern that has become commonplace for integrating data from multiple sources has proven useful, but complex to maintain. For a small number of sources it is a tractable problem, but as the overall complexity of the data ecosystem continues to expand it may be time to identify new ways to tame the deluge of information. In this episode Tim Ward, CEO of CluedIn, explains the idea of eventual connectivity as a new paradigm for data integration.

Data Integration 100

Data Integration Metadata Media Architecture 100

KDnuggets

JULY 29, 2019

Check out our latest Top 10 Most Popular Data Science and Machine Learning podcasts available on iTunes. Stay up to date in the field with these recent episodes and join in with the current data conversations.

Machine Learning 122

Machine Learning Data Science Data 122

Netflix Tech

JULY 30, 2019

v2.0 and beyond By Anoop Panicker and Kishore Banala Conductor is a workflow orchestration engine developed and open-sourced by Netflix. If you’re new to Conductor, this earlier blogpost and the documentation should help you get started and acclimatized to Conductor. Netflix Conductor: A microservices orchestrator In the last two years since inception, Conductor has seen wide adoption and is instrumental in running numerous core workflows at Netflix.

Metadata 75

Metadata Media AWS Transportation 75

Teradata

JULY 28, 2019

In a cost-cutting culture, directly linking data projects to top business initiatives is a good way to keep them from getting clipped. Learn more.

Data 73

Data Project 73

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

Pandora Engineering

JULY 29, 2019

Credit: Kanok Sulaiman Disclaimer: These are my experiences from being a Pandora software developer intern in the summer of 2019. All opinions expressed are my own, and represent no one except myself. I recently spent the last summer of my undergraduate program as an intern for Pandora Media in Oakland, CA. I gained a lot from my experience, and I’m writing this post to detail the application process, the lessons that I learned, and the company culture.

Java 52

Java Recruitment Algorithm Computer Science 52

KDnuggets

JULY 29, 2019

At my workplace, we produce a lot of functional prototypes for our clients. Because of this, I often need to make Small Data go a long way. In this article, I’ll share 7 tips to improve your results when prototyping with small datasets.

Datasets 121

Datasets Data 121

Teradata

JULY 30, 2019

It's not enough just to drive personalization in your marketing efforts, you need to take a multi-dimensional approach. Find out why it's worth the investment.

IT 49

IT 49

Confluent

JULY 31, 2019

Delivers the new Confluent Operator for cloud-native automation on Kubernetes, a redesigned Confluent Control Center user interface to simplify how you manage event streams, and a preview of Role-Based Access Control for enterprise-grade security. Over the past year, we’ve been amazed at how fast Confluent Platform has matured within our user base—both in terms of size and criticality of deployments.

Kafka 19

Kafka Cloud Accessible Accessibility 19

KDnuggets

JULY 31, 2019

I had a feeling that R has developed as a language to such a degree that many of us are using it now in completely different ways. This means that there are likely to be numerous tricks, packages, functions, etc that each of us use, but that others are completely unaware of, and would find useful if they knew about them.

IT 119

IT Data Science Data 119

KDnuggets

JULY 30, 2019

The Tensor Processing Unit (TPU) is Google's custom tool to accelerate machine learning workloads using the TensorFlow framework. Learn more about what TPUs do and how they can work for you.

Process 119

Process Machine Learning 119

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

KDnuggets

AUGUST 2, 2019

This cheatsheet should be easier to digest than the official documentation and should be a transitional tool to get students and beginners to get started reading documentations soon.

Deep Learning 119

Deep Learning Python 119

KDnuggets

AUGUST 1, 2019

By mixing simple concepts of object-oriented programming, like functionalization and class inheritance, you can add immense value to a deep learning prototyping code.

Deep Learning 118

Deep Learning Programming Coding Python 118

KDnuggets

AUGUST 1, 2019

Object detection has been applied widely in video surveillance, self-driving cars, and object/people tracking. In this piece, we’ll look at the basics of object detection and review some of the most commonly-used algorithms and a few brand new approaches, as well.

Algorithm 113

Algorithm 113

KDnuggets

AUGUST 1, 2019

Getting trained neural networks to be deployed in applications and services can pose challenges for infrastructure managers. Challenges like multiple frameworks, underutilized infrastructure and lack of standard implementations can even cause AI projects to fail. This blog explores how to navigate these challenges.

Deep Learning 110

Deep Learning Project Management 110

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

JULY 30, 2019

Data Scientists need computing power. Whether you’re processing a big dataset with Pandas or running some computation on a massive matrix with Numpy, you’ll need a powerful machine to get the job done in a reasonable amount of time.

Data Science 105

Data Science Datasets Data Process 105

KDnuggets

AUGUST 1, 2019

A machine learning model that predicts some outcome provides value. One that explains why it made the prediction creates even more value for your stakeholders. Learn how Interpretable and Explainable ML technologies can help while developing your model.

Machine Learning 96

Machine Learning Technology IT 96

KDnuggets

AUGUST 2, 2019

Lessons learned from repeatedly smashing my head with a 2-meter long metal pole for a college engineering course.

Data Science 121

Data Science Data Engineering Education 121

KDnuggets

JULY 31, 2019

We put an AutoML tool to the test on a real-world problem, and the results are surprising. Even with automatic machine learning, you still need expert data scientists.

Machine Learning 90

Machine Learning Data 90

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Project

KDnuggets

JULY 30, 2019

This technical webinar on Aug 14 discusses traditional and modern approaches for interpreting black box models. Additionally, we will review cutting edge research coming out of UCSF, CMU, and industry.

Data Science 87

Data Science Data Machine Learning 87

KDnuggets

JULY 30, 2019

This article is designed to give you a full picture from constructing a hypothesis testing to understanding p-value and using that to guide our decision making process.

Data 88

Data Designing Process Data Science 88

KDnuggets

AUGUST 2, 2019

The future is here! Speed up your Machine Learning workflow using Python RAPIDS libraries support.

Machine Learning 115

Machine Learning Data Analytics Python Data 115

KDnuggets

JULY 29, 2019

This free ebook is a great resource for data science beginners, providing a good introduction into Python, coding with Raspberry Pi, and using Python to building predictive models.

Python 70

Python Data Science Coding Building 70

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

JULY 31, 2019

You can do more data science than you think from the terminal.

Data Science 100

Data Science Data 100

KDnuggets

JULY 29, 2019

Recently, AI researchers from Microsoft open sourced the Decentralized & Collaborative AI on Blockchain project that enables the implementation of decentralized machine learning models based on blockchain technologies.

Machine Learning 58

Machine Learning Building Technology Project 58

KDnuggets

JULY 31, 2019

How Netflix works: the (hugely simplified) complex stuff that happens every time; Top Certificates and Certifications in Analytics, Data Science, ML; Nothing but NumPy: Understanding &Creating Neural Networks with Computation.

Certification 52

Certification Data Science Data 52

KDnuggets

JULY 29, 2019

Also: Convolutional Neural Networks: A Python Tutorial Using TensorFlow and Keras; Fantastic Four of Data Science Project Preparation; The Death of Big Data and the Emergence of the Multi-Cloud Era; The title CDO started out as a joke.

Big Data 50

Big Data Data Science Python Cloud 50

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

AUGUST 2, 2019

South Dakota State University is seeking a Data Visualization Developer and Analyst in Brookings, SD, to create business intelligence tools and reports to support the use of a campus-wide business intelligence and decision support system, compile multiple visualizations into intuitive dashboards for campus-wide use, and more.

Business Intelligence 49

Business Intelligence Data Systems 49

KDnuggets

JULY 29, 2019

Seeking a Lecturer / Sr Lecturer for the Monash Blockchain Technology Centre (Monash BTC): a visionary enterprise that will bring together world-leading expertise from across Monash to explore, develop and innovate the technology of blockchain, in collaboration with various industry and societal sectors.

Technology 48

Technology 48

KDnuggets

JULY 31, 2019

Learn the essential skills needed to become a Data Science rockstar; Understand CNNs with Python + Tensorflow + Keras tutorial; Discover the best podcasts about AI, Analytics, Data Science; and find out where you can get the best Certificates in the field.

Data Science 47

Data Science Certification Python Data 47

KDnuggets

JULY 31, 2019

When it comes to AI, there’s plenty of talk of the future of machines. But it’s the people behind AI development who have the insights needed to shape that future. Register now to catch all of our speakers at the Data Science Salon Miami, Sep 10-11, 2019.

Data Science 46

Data Science Data IT 46

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