KDnuggets

JULY 26, 2019

Education, coding, SQL, big data platforms, storytelling and more. These are the 13 skills you need to master to become a rockstar data scientist.

Education 123

Education Big Data SQL Data 123

Confluent

JULY 24, 2019

Using Jaeger tracing, I’ve been able to answer an important question that nearly every Apache Kafka ® project that I’ve worked on posed: how is data flowing through my distributed system? Quick disclaimer: if you’re simply looking for an answer to that question, this post won’t provide that answer directly. Instead, in this post I will point you to an earlier blog post where I already answered that question and then I will focus on what should be your next question: now that I’m relying on Jaege

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Kafka Systems Bytes Project 54

Data Engineering Podcast

JULY 22, 2019

Summary The current trend in data management is to centralize the responsibilities of storing and curating the organization’s information to a data engineering team. This organizational pattern is reinforced by the architectural pattern of data lakes as a solution for managing storage and access. In this episode Zhamak Dehghani shares an alternative approach in the form of a data mesh.

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Data Lake Hadoop Data Architecture 100

Teradata

JULY 21, 2019

Democratizing data science through access to tools like Teradata Vantage are helping businesses bridge the data scientist gap to get the outcomes they need.

Data Science 74

Data Science Data Accessible Accessibility 74

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In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate

Data Pipeline

KDnuggets

JULY 26, 2019

Different neural network architectures excel in different tasks. This particular article focuses on crafting convolutional neural networks in Python using TensorFlow and Keras.

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Python Architecture 123

Confluent

JULY 23, 2019

The Kafka Summit Program Committee recently published the schedule for the San Francisco event, and there’s quite a bit to look forward to. For starters, it is a two-day event, which means we get to attend 14 talks, miss out on 42 talks (that we’ll later watch on video), and spend two days hanging out with our favorite community friends. While the keynotes have not been announced yet (they will be soon!

Kafka 18

Kafka Hadoop Media Software Engineer 18

Teradata

JULY 23, 2019

Large enterprises are investing heavily in cloud-based analytics technologies. What qualities should they be looking for in these cloud vendors? Find out more.

Cloud 69

Cloud IT Technology 69

KDnuggets

JULY 26, 2019

This article takes a closer look at the four fantastic things we should keep in mind when approaching every new data science project.

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Data Science Project Data Data Preparation 123

KDnuggets

JULY 25, 2019

Here are the top certificates and certifications in Analytics, AI, Data Science, Machine Learning and related areas.

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Certification Machine Learning Data Science Data 123

KDnuggets

JULY 24, 2019

Recently, researchers from the Google Brain team published a paper proposing a new method called Concept Activation Vectors (CAVs) that takes a new angle to the interpretability of deep learning models.

Deep Learning 123

Deep Learning 123

Speaker: Tamara Fingerlin, Developer Advocate

Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.

Data

KDnuggets

JULY 25, 2019

As long as there is ‘data’ in data scientist, Structured Query Language (or see-quel as we call it) will remain an important part of it. In this blog, let us explore data science and its relationship with SQL.

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SQL Data Science Data Relational Database 120

KDnuggets

JULY 25, 2019

Find out how to use randomness to learn your data by using Noise Contrastive Estimation with this guide that works through the particulars of its implementation.

Deep Learning 99

Deep Learning IT Data 99

KDnuggets

JULY 24, 2019

Learn how to incorporate security into your practices without slowing down your project. Read this ActiveState blog post to learn more.

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Data Science Project Data 66

KDnuggets

JULY 25, 2019

ODSC focuses on research at its conferences and invites the experts pushing the boundaries of AI to speak. Between the two upcoming conferences, researchers from more than 20 of the top research institutes in the country (Open AI, NASA’s JPL, Google, MIT CSAIL, BAIR, The Turing Institute, and Max Planck and more) will deliver talks and lead trainings at ODSC West 2019.

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IT 61

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.

Systems

KDnuggets

JULY 24, 2019

Developers are always searching for answers to questions about their code. But how do they ask the right questions? Facebook is creating new NLP neural networks to help search code repositories that may advance information retrieval algorithms.

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Coding Algorithm Programming Process 56

KDnuggets

JULY 24, 2019

Also: Data Science Jobs Report 2019: Python Way Up, TensorFlow Growing Rapidly, R Use Double SAS; The Hundred-Page Machine Learning Book Book Review; The Evolution of a ggplot; Notes on Feature Preprocessing: The What, the Why, and the How.

Machine Learning 56

Machine Learning Coding Data Science Python 56

KDnuggets

JULY 25, 2019

Analyst firm Cognilytica estimates that as much as 80% of machine learning project time is spent on aggregating, cleaning, labeling, and augmenting machine learning model data. So, how do innovative machine learning teams prepare data in such a way that they can trust its quality, cost of preparation, and the speed with which it’s delivered?

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Machine Learning Data Project IT 51

KDnuggets

JULY 25, 2019

Responsible for operational leadership and management of the Master of Science in Business Analytics programs. Serves as a thought partner with the program Associate Dean to develop and execute program strategy.

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Programming Management 47

Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives

Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri

Manufacturing