KDnuggets

AUGUST 8, 2019

Graph Machine Learning uses the network structure of the underlying data to improve predictive outcomes. Learn how to use this modern machine learning method to solve challenges with connected data.

Machine Learning 123

Machine Learning Data 123

Confluent

AUGUST 8, 2019

We’re excited to announce Tutorials for Apache Kafka ® , a new area of our website for learning event streaming. Kafka Tutorials is a collection of common event streaming use cases, with each tutorial featuring an example scenario and several complete code solutions. It’s the fastest way to learn how to use Kafka with confidence. We’re building this because we know that event streaming is a radically different way of thinking.

Kafka 22

Kafka Data Warehouse Programming Coding 22

Data Engineering Podcast

AUGUST 5, 2019

Summary Data is only valuable if you use it for something, and the first step is knowing that it is available. As organizations grow and data sources proliferate it becomes difficult to keep track of everything, particularly for analysts and data scientists who are not involved with the collection and management of that information. Lyft has build the Amundsen platform to address the problem of data discovery and in this episode Tao Feng and Mark Grover explain how it works, why they built it, a

MongoDB 100

MongoDB PostgreSQL Metadata Media 100

Uber Engineering

AUGUST 7, 2019

A common axiom among Uber engineers states that building new features is like fixing a car’s engine while driving it. As we scaled up to our present level of support for 14 million trips per day, the car in that … The post Migrating Functionality Between Large-scale Production Systems Seamlessly appeared first on Uber Engineering Blog.

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Systems Engineering Building IT 97

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.

Data

KDnuggets

AUGUST 7, 2019

Learn about Artificial Neural Networks, Deep Learning, Recurrent Neural Networks and LSTMs like never before and use NLP to build a Chatbot!

Deep Learning 123

Deep Learning Building 123

Confluent

AUGUST 6, 2019

One of KSQL’s most powerful features is allowing users to build their own KSQL functions for processing real-time streams of data. These functions can be invoked on individual messages (user-defined functions or UDFs) or used to perform aggregations on groups of messages (user-defined aggregate functions or UDAFs). The previous blog post How to Build a UDF and/or UDAF in KSQL 5.0 discussed some key steps for building and deploying a custom KSQL UDF/UDAF.

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Kafka Java Coding Project 18

nodeSWAT

AUGUST 6, 2019

This post will walk you through the process of how to turn this awesome chat tool into a handy monitoring & alerting tool for your application. All this without any 3rd party modules and minimal code to keep the footprint small. Note: This post is using now outmoded integration method. Slack has introduced new ways to manage and send messages via Apps.

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Coding Accessible Accessibility Management 52

KDnuggets

AUGUST 7, 2019

Benford’s law is a little-known gem for data analytics. Learn about how this can be used for anomaly or fraud detection in scientific or technical publications.

Data Science 123

Data Science IT Data Analytics Data 123

KDnuggets

AUGUST 6, 2019

In this story, we’re going to take an aerial tour of optimization with Lagrange multipliers. When do we need them? Whenever we have an optimization problem with constraints.

Coding 123

Coding Python 123

KDnuggets

AUGUST 6, 2019

Feature selection is one of the most important tasks in machine learning. Learn how to use a simple random search in Python to get good results in less time.

Python 123

Python Machine Learning 123

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.

Systems

KDnuggets

AUGUST 7, 2019

There are dozens of machine learning algorithms out there. It is impossible to learn all their mechanics; however, many algorithms sprout from the most established algorithms, e.g. ordinary least squares, gradient boosting, support vector machines, tree-based algorithms and neural networks.

Coding 121

Coding Algorithm Machine Learning IT 121

KDnuggets

AUGUST 8, 2019

Simply put, data science is an attempt to understand given data using the scientific method. That's why data science is a scientific discipline. You are free (and encouraged!) to apply data science to business use cases, just as you are encouraged to apply it to many other domains.

Data Science 120

Data Science Process Data IT 120

KDnuggets

AUGUST 9, 2019

Image segmentation is the classification of an image into different groups. Many kinds of research have been done in the area of image segmentation using clustering. In this article, we will explore using the K-Means clustering algorithm to read an image and cluster different regions of the image.

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Algorithm Python 120

KDnuggets

AUGUST 5, 2019

Over the past many months, I’ve received hundreds of messages from people asking me how they could get started with Data Science. Therefore, I thought it would be useful to write down a framework for those wanting to get started with Data Science.

Data Science 119

Data Science Data IT 119

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

Manufacturing

KDnuggets

AUGUST 7, 2019

In this tutorial, you’ll use Python and Pandas to explore a dataset and create visual distributions, identify and eliminate outliers, and uncover correlations between two datasets.

Data Analysis 118

Data Analysis Python Datasets Data 118

KDnuggets

AUGUST 6, 2019

Check out this video (and Jupyter notebook) which outlines a number of Pandas tricks for working with and manipulating data, covering topics such as string manipulations, splitting and filtering DataFrames, combining and aggregating data, and more.

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Aggregated Data Data Python 117

KDnuggets

AUGUST 7, 2019

Also: Ten more random useful things in R you may not know about; 5 Probability Distributions Every Data Scientist Should Know; Machine Learning is Happening Now: A Survey of Organizational Adoption, Implementation, and Investment; Programmers rejoice! Deep TabNine offer code autocompletion with #deeplearning.

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Process IT Machine Learning Coding 113

KDnuggets

AUGUST 5, 2019

This is an excerpt from a survey which sought to evaluate the relevance of machine learning in operations today, assess the current state of machine learning adoption and to identify tools used for machine learning. A link to the full report is inside.

Machine Learning 112

Machine Learning 112

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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

Data Engineering

KDnuggets

AUGUST 9, 2019

A gentle introduction to callbacks in Keras. Learn about EarlyStopping, ModelCheckpoint, and other callback functions with code examples.

Coding 111

Coding Python 111

KDnuggets

AUGUST 8, 2019

The reasons why Pluribus represents a major breakthrough in AI systems might result confusing to many readers. After all, in recent years AI researchers have made tremendous progress across different complex games. However, six-player, no-limit Texas Hold’em still remains one of the most elusive challenges for AI systems.

Systems 109

Systems 109

KDnuggets

AUGUST 9, 2019

Who is this guide for? Anyone working on non-trivial deep learning models in Pytorch such as industrial researchers, Ph.D. students, academics, etc. The models we're talking about here might be taking you multiple days to train or even weeks or months.

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Deep Learning 104

KDnuggets

AUGUST 5, 2019

Generative Adversarial Networks are driving important new technologies in deep learning methods. With so much to learn, these two videos will help you jump into your exploration with GANs and the mathematics behind the modelling.

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Deep Learning Technology Data Machine Learning 99

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

AUGUST 5, 2019

This workshop, Aug 14 @ 12 PM ET, will give you the proper tools and tactics to manage the entire lifecycle of your machine learning projects, from research to exploration to development and production.

Data Science 90

Data Science Management Machine Learning Project 90

Teradata

AUGUST 6, 2019

Digital transformation & regulatory requirements have long challenged Banks. Teradata has deep experience in ushering them through the transformation process.

Banking 15

Banking Process 15

Teradata

AUGUST 7, 2019

Teradata partners Microsoft & Informatica announced that they are taking on cloud analytic migrations. Find out what this means for our on-premises customers.

Cloud 15

Cloud 15

KDnuggets

AUGUST 9, 2019

The position requires a passion for research, a proven research track record in computer vision, an ability to work independently as well as lead a team, and a willingness to work on inter-disciplinary research projects and seek external funding. The successful candidate will align with the group goal on building a world-class computer vision team.

Project 61

Project Building 61

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

Software Engineer

KDnuggets

AUGUST 7, 2019

This week on KDnuggets: What 70% of Data Science Learners Do Wrong; Pytorch Cheat Sheet for Beginners and Udacity Deep Learning Nanodegree; How a simple mix of object-oriented programming can sharpen your deep learning prototype; Can we trust AutoML to go on full autopilot?; Ten more random useful things in R you may not know about; 25 Tricks for Pandas; and much more!

Data Science 60

Data Science Deep Learning Programming Data 60

KDnuggets

AUGUST 5, 2019

Also: GPU Accelerated Data Analytics & Machine Learning; Understanding Tensor Processing Units; Top 13 Skills To Become a Rockstar Data Scientist; Five Command Line Tools for Data Science; Ten more random useful things in R you may not know about.

Data Science 55

Data Science Machine Learning Data Analytics Data 55

KDnuggets

AUGUST 6, 2019

Waste Management is seeking a Data Scientist in Houston, TX, to support their digital marketing, customer and other business segment teams with insights gained from analyzing customer data.

Management 49

Management Data 49