KDnuggets

JANUARY 3, 2020

Why do most data scientists love Python? Learn more about how so many well-developed Python packages can help you accomplish your crucial data science tasks.

Data Science 160

Data Science Python Data Programming Language 160

Data Engineering Podcast

DECEMBER 30, 2019

Summary DataDog is one of the most successful companies in the space of metrics and monitoring for servers and cloud infrastructure. In order to support their customers, they need to capture, process, and analyze massive amounts of timeseries data with a high degree of uptime and reliability. Vadim Semenov works on their data engineering team and joins the podcast in this episode to discuss the challenges that he works through, the systems that DataDog has built to power their business, and how

Process 100

Process Building Hadoop Java 100

Confluent

DECEMBER 30, 2019

During the holiday season, it’s a particularly relevant time to pause, reflect, and celebrate, both the days past and those ahead. Here at Confluent, it’s a noticeably nostalgic moment, given […].

19

19

Teradata

DECEMBER 29, 2019

How do you organize your business for analytics? Here are six steps your enterprise should take when creating an analytics team. Read more!

59

59

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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 2, 2020

Time series forecasting is a technique for the prediction of events through a sequence of time. In this post, we will be taking a small forecasting problem and try to solve it till the end learning time series forecasting alongside.

IT 160

IT Python 160

KDnuggets

DECEMBER 31, 2019

With so many buzzwords surrounding AI and machine learning, understanding which can bring business value and which are best left in the lab to mature is difficult. While machine learning offers significant power in driving digital transformations, a business must start with the right questions and leave the math to the development teams.

Data Science 158

Data Science Machine Learning Data 158

KDnuggets

JANUARY 2, 2020

In this use case, available to the public on GitHub, we’ll see how a data scientist, project manager, and business lead at a retail grocer can leverage automated machine learning and Azure Machine Learning service to reduce product overstock.

Machine Learning 137

Machine Learning Project Retail Management 137

KDnuggets

DECEMBER 30, 2019

For those of you in a hurry and interested in ultralearning (which should be all of you), this recap reviews the approach and summarizes its key elements -- focus, optimization, and deep understanding with experimentation -- geared toward learning Data Science.

Data Science 135

Data Science Data IT 135

KDnuggets

JANUARY 2, 2020

Delivering accurate insights is the core function of any data scientist. Navigating the development road toward this goal can sometimes be tricky, especially when cross-collaboration is required, and these lessons learned from building a search application will help you negotiate the demands between accuracy and speed.

Data 108

Data Building Engineering 108

KDnuggets

DECEMBER 31, 2019

AI scientist Francois Chollet proposes a better framework for measuring the intelligence of AI systems.

Systems 105

Systems 105

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

DECEMBER 30, 2019

AI scientist Francois Chollet proposes a better framework for measuring the intelligence of AI systems.

Systems 99

Systems 99

KDnuggets

DECEMBER 31, 2019

A Gentle Introduction to #Math Behind #NeuralNetworks; Learn How to Quickly Create UIs in Python; I wanna be a data scientist, but. how!?; I created my own deepfake in two weeks.

Python 88

Python Data 88

KDnuggets

JANUARY 3, 2020

The gender gap can extend to the lack of equal representation in certain industries or career paths, and there's an extraordinarily long way to go before people will be on equal footing in the labor market. Human resources professionals can rely on data analytics to make progress.

Data Science 67

Data Science Data Analytics Data 67

KDnuggets

DECEMBER 30, 2019

Also: Let’s Build an Intelligent Chatbot; 10 Best and Free Machine Learning Courses, Online; Build Pipelines with Pandas Using pdpipe; Alternative Cloud Hosted Data Science Environments.

Machine Learning 65

Machine Learning Data Science Cloud Data 65

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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

Teradata

DECEMBER 29, 2019

How do you organize your business for analytics? Here are six steps your enterprise should take when creating an analytics team. Read more!

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58

Teradata

DECEMBER 29, 2019

Are you a budding data scientist? Learn why Kaggle only offers a limited view of data science and is not the optimal place to learn data science skills.

Data Science 8

Data Science Data 8