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

PostgreSQL 100

PostgreSQL MongoDB Metadata Media 100

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

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.

Systems 77

Systems Engineering Building IT 77

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.

Coding 52

Coding Accessibility Accessible Management 52

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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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

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

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 116

Data Science IT Data Analytics Data 116

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 109

Coding Python 109

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 120

Deep Learning Building 120

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 101

Coding Algorithm Machine Learning IT 101

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 99

Data Science Process Data IT 99

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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?

Business Intelligence

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 107

Python Machine Learning 107

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 97

Data Analysis Python Datasets Data 97

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.

Algorithm 99

Algorithm Python 99

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 97

Data Science Data IT 97

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.

Data

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.

Aggregated Data 95

Aggregated Data Data Python 95

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 104

Machine Learning 104

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.

Process 92

Process IT Machine Learning Coding 92

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 90

Systems 90

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.

Manufacturing

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.

Deep Learning 88

Deep Learning 88

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.

Deep Learning 87

Deep Learning Technology Data Machine Learning 87

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 84

Data Science Management Machine Learning Project 84

KDnuggets

AUGUST 9, 2019

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

Coding 91

Coding Python 91

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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.

Cloud

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 56

Project Building 56

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 48

Data Science Deep Learning Programming Data 48

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 46

Data Science Machine Learning Data Analytics Data 46

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 45

Management Data 45

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.

Systems

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.

Kafka 18

Kafka Java Coding Project 18

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