Wed.Jan 04, 2023

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A Solid Plan for Learning Data Science, Machine Learning, and Deep Learning

KDnuggets

Check out this solid plan for learning Data Science, Machine Learning, and Deep Learning. The entire plan is currently available at no cost to KDnuggets readers.

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I talked to DataGen podcast

Christophe Blefari

🎙 A few week ago I did my first podcast with Robin. We talked about data engineering and everything around doing a weekly curation. This is the first episode of Robin's podcast in English and you should follow him because more are coming! In the podcast we talked about 🔥 My journey before launching the newsletter 🔥 Why and how I write 🔥 My main challenges as a Data Engineer 🔥 My favorite contents 🔥 What I like about data 🔥 A few tips f

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Micro, Macro & Weighted Averages of F1 Score, Clearly Explained

KDnuggets

Understanding the concepts behind the micro average, macro average, and weighted average of F1 score in multi-class classification with simple illustrations.

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A Guide to Data Contracts

Striim

Companies need to analyze large volumes of datasets, leading to an increase in data producers and consumers within their IT infrastructures. These companies collect data from production applications and B2B SaaS tools (e.g., Mailchimp). This data makes its way into a data repository, like a data warehouse (e.g., Redshift), and is shown to users via a dashboard for decision-making.

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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Top Data Python Packages to Know in 2023

KDnuggets

These Python packages would improve your data workflow.

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Recycling Kubernetes Nodes

Yelp Engineering

Manually managing the lifecycle of Kubernetes nodes can become difficult as the cluster scales. Especially if your clusters are multi-tenant and self-managed. You may need to replace nodes for various reasons, such as OS upgrades and security patches. One of the biggest challenges is how to terminate nodes without disturbing tenants. In this post, I’ll describe the problems we encountered administering Yelp’s clusters and the solutions we implemented.

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Precisely Women in Techology: Meet Samantha Kastin

Precisely

At Precisely, diversity is an inherent aspect of the company culture. Celebrating each other’s differences makes the team stronger as a whole. The Precisely Women in Technology (PWIT) program is a designated space for women in the company to learn from one another, support each other, provide career-growth advice, and share opportunities. Each month, a member of the PWIT group is featured to learn more about their experience as a woman in technology at Precisely.

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ON-DEMAND WEBINAR: Managing Stress in Data Engineering: Data Quality and Testing Techniques for Data Observability

DataKitchen

Why do 78% of data engineers wish their job came with a therapist to help manage work-related stress? THEY DO NOT TEST. The post ON-DEMAND WEBINAR: Managing Stress in Data Engineering: Data Quality and Testing Techniques for Data Observability first appeared on DataKitchen.

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More 2023 Tech and Industry Predictions from Teradata Experts

Teradata

From advances in AI/ML to the expansion of satellite/cellular services to expand coverage to remote areas, our tech & industry experts weigh in on game-changing predictions for 2023.

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Achieve Your Goals With Databricks Certifications

databricks

Elevate your career in the New Year! Start the new year off right by taking your Databricks enablement to the next level by.

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Understanding User Needs and Satisfying Them

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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Now in Preview: Webhook Data Source | Propel Data Analytics Blog

Propel Data

Easily get your data into Propel to power a variety of customer-facing analytics use cases.

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Selecting the Best Image for Each Merchant Using Exploration and Machine Learning

DoorDash Engineering

In order to inspire DoorDash consumers to order from the platform there are few tools more powerful than a compelling image, which raises the questions: what is the best image to show each customer, and how can we build a model to determine that programmatically using each merchant’s available images? Figure 1: Discovery surfaces with merchant images Out of all the different information presented on the home page (see Figure 1), studies with consumers have repeatedly shown that images play the m

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How Collaborative Imaging Delivers Healthier Data Products with Monte Carlo

Monte Carlo

As a radiologist-owned alliance built by physicians, Collaborative Imaging knows a thing or two about what it means to be healthy. And the same goes for their data. From revenue cycle management to telehealth, Collaborative Imaging ’s physician-conceived platform is solving some of the biggest technology challenges facing modern medical practices. And with hundreds of hospitals utilizing Collaborative Imaging’s data products to optimize their practices, data quality is paramount for the data tea