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

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 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.

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Cloud IT Technology 69

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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

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!

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Kafka Hadoop Media Software Engineer 18

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.

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Data Science Data Accessibility Accessible 74

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.

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Education Big Data SQL Data 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.

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Deep Learning 123

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

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.

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Deep Learning IT Data 106

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 75

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.

IT 70

IT 70

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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

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 62

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.

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Machine Learning Coding Data Science Python 62

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 56

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 50

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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