2019

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10 Best and Free Machine Learning Courses, Online

KDnuggets

Getting ready to leap into the world of Data Science? Consider these top machine learning courses curated by experts to help you learn and thrive in this exciting field.

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Uber Infrastructure in 2019: Improving Reliability, Driving Customer Satisfaction

Uber Engineering

Every day around the world, millions of trips take place across the Uber network, giving users more reliable transportation through ridesharing, bikes, and scooters, drivers and truckers additional opportunities to earn, employees and employers more convenient business travel, and hungry … The post Uber Infrastructure in 2019: Improving Reliability, Driving Customer Satisfaction appeared first on Uber Engineering Blog.

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Exploring ksqlDB with Twitter Data

Confluent

When KSQL was released, my first blog post about it showed how to use KSQL with Twitter data. Two years later, its successor ksqlDB was born, which we announced this […].

Data 27
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Python at Netflix

Netflix Tech

By Pythonistas at Netflix, coordinated by Amjith Ramanujam and edited by Ellen Livengood As many of us prepare to go to PyCon, we wanted to share a sampling of how Python is used at Netflix. We use Python through the full content lifecycle, from deciding which content to fund all the way to operating the CDN that serves the final video to 148 million members.

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Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

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.

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Our Commitment to Open Source Software

Cloudera

Open source has been core to the missions of both Hortonworks and Cloudera and central to our values and culture. With more than 700 engineers in the new Cloudera, our company writes a prodigious amount of open source code each year that’s contributed to more than 30 different open source projects. We’re also a very innovative open source company, having collectively launched more than a dozen new open source projects since the founding of the two companies. .

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Building The DataDog Platform For Processing Timeseries Data At Massive Scale

Data Engineering Podcast

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

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Open Source Projects by Google, Uber and Facebook for Data Science and AI

KDnuggets

Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.

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Getting Started with Automated Text Summarization

KDnuggets

This article will walk through an extractive text summarization process, using a simple word frequency approach, implemented in Python.

Python 160
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A Doomed Marriage of Machine Learning and Agile

KDnuggets

Sebastian Thrun, the founder of Udacity, ruined my machine learning project and wedding.

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Data Science Curriculum Roadmap

KDnuggets

What follows is a set of broad recommendations, and it will inevitably require a lot of adjustments in each implementation. Given that caveat, here are our curriculum recommendations.

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

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.

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Market Basket Analysis: A Tutorial

KDnuggets

This article is about Market Basket Analysis & the Apriori algorithm that works behind it.

Algorithm 159
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10 Free Top Notch Machine Learning Courses

KDnuggets

Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.

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What is the most important question for Data Science (and Digital Transformation)

KDnuggets

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.

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Interpretability part 3: LIME and SHAP

KDnuggets

The third part in a series on leveraging techniques to take a look inside the black box of AI, this guide considers methods that try to explain each prediction instead of establishing a global explanation.

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How to Modernize Manufacturing Without Losing Control

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

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The 4 fastest ways not to get hired as a data scientist

KDnuggets

Ready to try to get hired as a data scientist for the first time? Avoiding these common mistakes won’t guarantee an offer, but not avoiding them is a sure fire way for your application to be tossed into the trash bin.

Data 154
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Explainability: Cracking open the black box, Part 1

KDnuggets

What is Explainability in AI and how can we leverage different techniques to open the black box of AI and peek inside? This practical guide offers a review and critique of the various techniques of interpretability.

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Top KDnuggets tweets, Nov 20-26: How to Speed up Pandas by 4x with one line of code

KDnuggets

Also: Deep Learning for Image Classification with Less Data; How to Speed up Pandas by 4x with one line of code; 25 Useful #Python Snippets to Help in Your Day-to-Day Work; Automated Machine Learning Project Implementation Complexities.

Coding 150
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Automatic Text Summarization in a Nutshell

KDnuggets

Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about Automatic Text Summarization and the various ways it is used.

IT 149
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The Ultimate Guide to Apache Airflow DAGS

With Airflow being the open-source standard for workflow orchestration, knowing how to write Airflow DAGs has become an essential skill for every data engineer. This eBook provides a comprehensive overview of DAG writing features with plenty of example code. You’ll learn how to: Understand the building blocks DAGs, combine them in complex pipelines, and schedule your DAG to run exactly when you want it to Write DAGs that adapt to your data at runtime and set up alerts and notifications Scale you

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5 Techniques to Prevent Overfitting in Neural Networks

KDnuggets

In this article, I will present five techniques to prevent overfitting while training neural networks.

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What is a Data Scientist Worth?

KDnuggets

What is the Salary of a Data Scientist in 2019? Let's have a look at some data to see how we can answer that question.

Data 145
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The Essential Toolbox for Data Cleaning

KDnuggets

Increase your confidence to perform data cleaning with a broader perspective of what datasets typically look like, and follow this toolbox of code snipets to make your data cleaning process faster and more efficient.

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Uber’s Data Platform in 2019: Transforming Information to Intelligence

Uber Engineering

Uber’s busy 2019 included our billionth delivery of an Uber Eats order, 24 million miles covered by bike and scooter riders on our platform, and trips to top destinations such as the Empire State Building, the Eiffel Tower, and the … The post Uber’s Data Platform in 2019: Transforming Information to Intelligence appeared first on Uber Engineering Blog.

Data 144
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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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A Non-Technical Reading List for Data Science

KDnuggets

The world still cannot be reduced to numbers on a page because human beings are still the ones making all the decisions. So, the best data scientists understand the numbers and the people. Check out these great data science books that will make you a better data scientist without delving into the technical details.

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Optimizing Observability with Jaeger, M3, and XYS at Uber

Uber Engineering

When something goes wrong with a piece of code, engineers want to know all the relevant details of the error immediately so they can get right to work remedying the malfunction. . However, as technology has advanced, measuring system metrics and … The post Optimizing Observability with Jaeger, M3, and XYS at Uber appeared first on Uber Engineering Blog.

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Alternative Cloud Hosted Data Science Environments

KDnuggets

Over the years new alternative providers have risen to provided a solitary data science environment hosted on the cloud for data scientist to analyze, host and share their work.

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Apache Kafka Producer Improvements with the Sticky Partitioner

Confluent

The amount of time it takes for a message to move through a system plays a big role in the performance of distributed systems like Apache Kafka®. In Kafka, the […].

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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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Industry AI, Analytics, Machine Learning, Data Science Predictions for 2020

KDnuggets

Predictions for 2020 from a dozen innovative companies in AI, Analytics, Machine Learning, Data Science, and Data industry.

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Google’s New Explainable AI Service

KDnuggets

Google has started offering a new service for “explainable AI” or XAI, as it is fashionably called. Presently offered tools are modest, but the intent is in the right direction.

IT 126
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How To “Ultralearn” Data Science: summary, for those in a hurry

KDnuggets

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.

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Advice for New and Junior Data Scientists

KDnuggets

If you are a new Data Scientists early in your professional journey, and you’re a bit confused and lost, then follow this advice to figure out how to best contribute to your company.

Data 124
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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

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.