KDnuggets

MARCH 9, 2020

Upgrading your machine learning, AI, and Data Science skills requires practice. To practice, you need to develop models with a large amount of data. Finding good datasets to work with can be challenging, so this article discusses more than 20 great datasets along with machine learning project ideas for you to tackle today.

Datasets 160

Datasets Machine Learning Project Data Science 160

Uber Engineering

MARCH 11, 2020

The performance of Uber’s services relies on our ability to quickly and stably launch new features on our platform , regardless of where the corresponding service lives in our tech stack. Foundational to our platform’s power is its microservice-based architecture … The post Why We Leverage Multi-tenancy in Uber’s Microservice Architecture appeared first on Uber Engineering Blog.

Architecture 145

Architecture Engineering IT 145

Data Engineering Podcast

MARCH 9, 2020

Summary Data governance is a complex endeavor, but scaling it to meet the needs of a complex or globally distributed organization requires a well considered and coherent strategy. In this episode Tim Ward describes an architecture that he has used successfully with multiple organizations to scale compliance. By treating it as a graph problem, where each hub in the network has localized control with inheritance of higher level controls it reduces overhead and provides greater flexibility.

Data Governance 100

Data Governance Government Architecture Data 100

Confluent

MARCH 11, 2020

In the Apache Kafka® ecosystem, ksqlDB and Kafka Streams are two popular tools for building event streaming applications that are tightly integrated with Apache Kafka. While ksqlDB and Kafka Streams […].

Kafka 113

Kafka Process Building 113

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Data Science

KDnuggets

MARCH 10, 2020

Has coronavirus impacted your conference or other travel plans, and do you anticipate it causing further professional or educational disruption in the near future? Take part in the new KDnuggets poll and have your say.

Machine Learning 142

Machine Learning Data Science Education Data 142

Rockset

MARCH 12, 2020

At Rockset we strive to make building modern data applications easy and intuitive. Data-backed applications come with an inherent amount of complexity - managing the database backend, exposing a data API (often using hard-coded SQL or an ORM to write queries), keeping the data and application code in sync. the list goes on. Just as Rockset has reimagined and dramatically simplified the traditional ETL pipeline on the data-loading side , we’re now proud to release a new product feature - Query La

SQL 52

SQL Coding Database Python 52

Confluent

MARCH 9, 2020

Every year on March 8th, Confluent is proud to celebrate International Women’s Day, a global holiday dedicated to honoring the accomplishments of women and advocating for gender equality around the […].

84

84

KDnuggets

MARCH 8, 2020

For the international women's day, we feature resources to help more women enter and succeed in AI, Big Data, Data Science, and Machine Learning fields.

Machine Learning 151

Machine Learning Data Science Big Data Data 151

Zalando Engineering

MARCH 12, 2020

This document is heavily informed by remote work guidance from other companies and authors. Notable sources include FYI's 11 Best Practices for Working Remotely and Laurel Farrer’s How to Design Powerful Rituals for Successful Distributed Companies. Special thanks to Timo from GiantSwarm for sharing learnings in an ad-hoc phone call. Other sources are linked in the appendix.

Electronics 40

Electronics Management Building Designing 40

Teradata

MARCH 8, 2020

In the final part of this 3-part series, Tim Miller describes how to run R and Python in-database in Vantage using SCRIPT Table Operators.

Python 52

Python Database 52

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

Engineering

Confluent

MARCH 10, 2020

Given the growing concern and global impact of COVID-19 (better known as the coronavirus), we’ve made the decision to cancel the upcoming Kafka Summit London. While this decision was incredibly […].

Kafka 78

Kafka 78

KDnuggets

MARCH 9, 2020

In this article, we are listing down some excellent data science books which cover the wide variety of topics under Data Science.

Data Science 156

Data Science Data 156

Preset

MARCH 12, 2020

Stay up to date on the Coronavirus cases with **Superset** dashboard & Public Data

Data 40

Data 40

Teradata

MARCH 10, 2020

Monica Woolmer recaps her career in technology and business as an homage to Women's History Month.

Technology 59

Technology Data 59

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

Building

Confluent

MARCH 13, 2020

As the impact of COVID-19 (coronavirus) continues to spread, our top priority is the health and well-being of our customers, employees, and community. We are acutely aware that these are […].

65

65

KDnuggets

MARCH 9, 2020

Game theory is experiencing a renaissance driven by the evolution of AI. What are some classic and new ideas that data scientists should be aware of.

Machine Learning 136

Machine Learning Data 136

Netflix Tech

MARCH 10, 2020

by Damir Svrtan and Sergii Makagon As the production of Netflix Originals grows each year, so does our need to build apps that enable efficiency throughout the entire creative process. Our wider Studio Engineering Organization has built more than 30 apps that help content progress from pitch (aka screenplay) to playback: ranging from script content acquisition, deal negotiations and vendor management to scheduling, streamlining production workflows, and so on.

Architecture 138

Architecture Transportation Java Database 138

KDnuggets

MARCH 13, 2020

After spending a lot of time thinking about the paths that software companies take toward ML maturity, this framework was created to follow as you adopt ML and then mature as an organization. The framework covers every aspect of building a team including product, process, technical, and organizational readiness, as well as recognizes the importance of cross-functional expertise and process improvements for bringing AI-driven products to market.

Machine Learning 121

Machine Learning Building Process Data Science 121

Advertisement

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

Project

KDnuggets

MARCH 13, 2020

I train a series of Machine Learning models using the iris dataset, construct synthetic data from the extreme points within the data and test a number of Machine Learning models in order to draw the decision boundaries from which the models make predictions in a 2D space, which is useful for illustrative purposes and understanding on how different Machine Learning models make predictions.

Machine Learning 119

Machine Learning Datasets Data 119

KDnuggets

MARCH 12, 2020

Automating the analysis of customer feedback will sound like a great idea after reading a couple hundred reviews. Building an NLP solution to provide in-depth analysis of what your customers are thinking is a serious undertaking, and this guide helps you scope out the entire project.

Building 110

Building Project 110

KDnuggets

MARCH 13, 2020

This articles outlines 5 sets of tools every lazy full-stack data scientist should use.

Machine Learning 152

Machine Learning Data 152

KDnuggets

MARCH 10, 2020

Just getting started with Python's Pandas library for data analysis? Or, ready for a quick refresher? These 7 steps will help you become familiar with its core features so you can begin exploring your data in no time.

Python 105

Python Data Analysis Data Data Preparation 105

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

Building

KDnuggets

MARCH 11, 2020

Let's talk about covid-19; the reality, the numbers, and the data science.

Data Science 157

Data Science Data Data Analysis 157

KDnuggets

MARCH 12, 2020

A new optimization framework helps to incorporate fairness constraints in machine learning models.

Machine Learning 132

Machine Learning Building 132

KDnuggets

MARCH 11, 2020

Math for Programmers teaches you the math you need to know for a career in programming, concentrating on what you need to know as a developer.

Programming 107

Programming Education 107

KDnuggets

MARCH 10, 2020

This article contain a brief intro to Generative Adversarial Network(GAN) and how to build a Human Face Generator.

Building 109

Building Python 109

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

Certification

KDnuggets

MARCH 12, 2020

Here is how you can teach your model to learn quickly from a few examples.

Machine Learning 116

Machine Learning 116

KDnuggets

MARCH 11, 2020

Also: Recreating Fingerprints using Convolutional Autoencoders; A simple and interpretable performance measure for a binary classifier; Resources for Women in AI, Data Science, and Machine Learning; Trends in Machine Learning in 2020; A Crash Course in Game Theory for Machine Learning; and much more.

Machine Learning 66

Machine Learning Data Science Data 66

KDnuggets

MARCH 10, 2020

This post presents an analysis of Berlin online real estate listings, investigating a controversial law capping rents in the state, which went into effect on February 23. Are current landlords already respecting the new rent cap?

Data Analysis 64

Data Analysis Data Science Data 64

KDnuggets

MARCH 11, 2020

While building a machine learning model might be the fun part, it won't do much for anyone else unless it can be deployed into a production environment. How to implement machine learning deployments is a special challenge with differences from traditional software engineering, and this post examines a fundamental first step -- how to create software interfaces so you can develop deployments that are automated and repeatable.

Machine Learning 63

Machine Learning Software Engineer Software Engineering Engineering 63

Advertisement

“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.

Building