Sat.Jan 08, 2022 - Fri.Jan 14, 2022

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Airflow TaskGroups: All you need to know!

Marc Lamberti

Airflow TaskGroups have been introduced to make your DAG visually cleaner and easier to read. They are meant to replace SubDAGs which was the historic way of grouping your tasks. The problem with SubDAGs is that they are much more than that. They bring a lot of complexity as you need to create a DAG in a DAG, import the SubDagOperator which is in fact a sensor, define the parameters properly, and so on.

Coding 130
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A Deep Look Into 13 Data Scientist Roles and Their Responsibilities

KDnuggets

Any modern company of any significant size around the world has a data science department, and a data engineer at one company might have the same responsibilities as a marketing scientist at another company. Data science jobs are not well-labeled, so make sure to cast a wide net.

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5 Common Pitfalls When Using Apache Kafka

Confluent

Whether you’re a seasoned Apache Kafka® developer or just getting started you’re likely to hit a snag at some point or another—either in configuring and understanding your clients or setting […].

Kafka 138
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Avoid Data Sharing Lock-in and Take the Open Road

Teradata

There is a lot of hype today around data sharing and the value it brings to your business. But what exactly is data sharing, and why should you and your company care? Find out more.

Data 97
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Optimizing The Modern Developer Experience with Coder

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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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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Auto-Diagnosis and Remediation in Netflix Data Platform

Netflix Tech

By Vikram Srivastava and Marcelo Mayworm Netflix has one of the most complex data platforms in the cloud on which our data scientists and engineers run batch and streaming workloads. As our subscribers grow worldwide and Netflix enters the world of gaming , the number of batch workflows and real-time data pipelines increases rapidly. The data platform is built on top of several distributed systems, and due to the inherent nature of these systems, it is inevitable that these workloads run into fa

Kafka 96
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Running Redis on Google Colab

KDnuggets

Open source Redis is being increasingly used in Machine Learning, but running it on Colab is different compared to on your local machine or with Docker. Read on for a 2-step tutorial on how to do it.

More Trending

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DataKitchen Introduces DataOps Training and Certification Program

DataKitchen

Cambridge, Mass. – June 16, 2021. Today, DataKitchen announced the release of the latest book in its groundbreaking DataOps series, Recipes for DataOps Success: The Complete Guide to An Enterprise DataOps Transformation. This book follows on the heels of its successful precursor, The DataOps Cookbook , which has been downloaded more than 14,000 times and counting.

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A-Z Guide to Text Summarization in Python for Beginners

ProjectPro

Have you heard of the Inshorts smartphone app? It is a cutting-edge news app that embodies news stories into a concise 60-word summary. Applications like Inshorts allow you to avoid reading long articles by generating a clear and concise summary. An average individual uses Google Search more than three times a day. Thanks to Featured Snippets, or Knowledge Panels, you receive better results for your search queries.

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The Story of the Women in Data Science (WiDS) Datathon

KDnuggets

The author shares their experience of almost winning the competition and the things they have learned from the failures. Learn more about the WiDS Datathon and tips on winning the next challenge.

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Why a Data Platform? The role of Data & Insights at Wolt

Wolt

Data Platforms are an essential part of modern businesses. They enable reporting, low friction decision making, and if used correctly, can power very advanced data products in a compliant and traceable manner. Let us take you from the role of data at Wolt, through the data journey we’ve had so far and finish with a peek into what the future of this discipline may look like.

Data 52
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15 Modern Use Cases for Enterprise Business Intelligence

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?

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Data Lakes vs. Data Warehouses

Grouparoo

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle. There are two main options available, a data lake and a data warehouse.

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Classification vs. Regression Algorithms in Machine Learning

ProjectPro

“Machine Learning” is one of the most trending buzzwords. It is predominant in every industry sector as it empowers various organizations with innovative solutions to automate and increase the efficacy of products by reducing human intervention. You might have heard about the applications of weather forecasting, spam classification, or stock price prediction applications, so what exactly do these applications use ?

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Query Your Pandas DataFrames with SQL

KDnuggets

Learn how to query your Pandas DataFrames using the standard SQL SELECT statement, seamlessly from within your Python code.

SQL 160
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The Top Telecommunications Trends to Look Out for in 2022

Teradata

2021 was the year of expanding 5G coverage, building out 5G use cases and the start of the migration to 5G Stand Alone. What will the year 2022 bring to the Telco industry?

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

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.

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The Customer is Always Wrong – Along with the Rest of Us

Elder Research

The post The Customer is Always Wrong – Along with the Rest of Us appeared first on Elder Research.

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How to Build ARIMA Model in Python for time series forecasting?

ProjectPro

Time series data can be defined as a sequence of data points that need to be seen with respect to the time stamp for each sample. Data samples are indexed by the timestamps or are highly dependent on them in time series. Data for weather forecasting, stock price prediction, user subscriptions, or sales patterns are some examples of time series data.

Python 52
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Is Data Science a Dying Career?

KDnuggets

At the end of the day, the value a data scientist provides to an organization lies in their ability to apply data to real-world use cases.

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RudderStack Product News Vol. #019 - Destination UI

RudderStack

In this update we cover our latest Destination UI feature, our new VDM for Klaviyo, new SDKs and destination integrations, and more.

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How to Drive Cost Savings, Efficiency Gains, and Sustainability Wins with MES

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

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Experimentation is a major focus of Data Science across Netflix

Netflix Tech

Martin Tingley with Wenjing Zheng , Simon Ejdemyr , Stephanie Lane , Colin McFarland , Andy Rhines , Sophia Liu , Mihir Tendulkar , Kevin Mercurio , Veronica Hannan , Ting-Po Lee Earlier posts in this series covered the basics of A/B tests ( Part 1 and Part 2 ), core statistical concepts ( Part 3 and Part 4 ), and how to build confidence in decisions based on A/B test results ( Part 5 ).

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A (Much) Better Approach to Evaluate Your Machine Learning Model

KDnuggets

Using one or two performance metrics seems sufficient to claim that your ML model is good — chances are that it’s not.

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Context, Consistency, And Collaboration Are Essential For Data Science Success

KDnuggets

It’s crucial to investigate the reasons why data science teams require context, consistency, and secure collaboration of their data to ensure data science success. Let's quickly examine each of these requirements so that we can better understand what data science success moving forward may look like.

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KDnuggetsâ„¢ News 22:n02, Jan 12: Is Data Science a Dying Career?; Why Do Machine Learning Models Die In Silence?

KDnuggets

Is Data Science a Dying Career?; Why Do Machine Learning Models Die In Silence?; SQL Interview Questions for Experienced Professionals; Deliver a Killer Presentation in Data Science Interviews; What is Transfer Learning?

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The Cloud Development Environment Adoption Report

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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Top Stories, Jan 3-9: Why Do Machine Learning Models Die In Silence?

KDnuggets

Also: Why are More Developers Using Python for Their Machine Learning Projects?; 3 Tools to Track and Visualize the Execution of Your Python Code; SQL Interview Questions for Experienced Professionals; Deliver a Killer Presentation in Data Science Interviews.

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Transfer Learning for Image Recognition and Natural Language Processing

KDnuggets

Read the second article in this series on Transfer Learning, and learn how to apply it to Image Recognition and Natural Language Processing.

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Interpretable Neural Networks with PyTorch

KDnuggets

Learn how to build feedforward neural networks that are interpretable by design using PyTorch.

Designing 151
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New Online MS in Business Analytics for Managers from University of Rochester

KDnuggets

The new Online MS in Business Analytics for Managers from Simon Business School is the latest advancement in analytically rigorous, leadership-focused education designed to help managers and aspiring managers prepare for the future of business-wherever it may lead. Applications are being accepted now and the first 14-month class will begin August 2022.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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Top Five SQL Window Functions You Should Know For Data Science Interviews

KDnuggets

Focusing on the important concepts for data scientists.

SQL 160
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Fake It Till You Make It: Generating Realistic Synthetic Customer Datasets

KDnuggets

Finding the data you need is hard. So why not fake it?

Datasets 160
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5 Things to Keep in Mind Before Selecting Your Next Data Science Job

KDnuggets

These are some of the most critical questions that I think are important to consider when selecting the next job.