Dataconomy
OCTOBER 31, 2016
Relational databases have been in place for decades, but many organizational owners as well as administrators have come across the concept of big data. Big data defies the laws of relational databases and lets you store unstructured data. Basically, you can store anything and everything. As your data requirements increase, The post 7 Signs You Should Move to Big Data Storage appeared first on Dataconomy.
Eugene Yan
OCTOBER 22, 2016
A card sorting game to discover youl passion by identifying skills you like and dislike.
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Distill
OCTOBER 13, 2016
Although extremely useful for visualizing high-dimensional data, t-SNE plots can sometimes be mysterious or misleading.
Christian Haschek
OCTOBER 25, 2016
In the end of WW2, when Vienna was overtaken by allied forces, the Wehrmacht was pushed in the w
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.
Explosion
OCTOBER 22, 2016
This is a guest post by Wah Loon Keng , the author of spacy-nlp , a client that exposes spaCy ’s NLP text parsing to Node.js (and other languages) via Socket.IO. Natural Language Processing and other AI technologies promise to let us build applications that offer smarter, more context-aware user experiences. However, an application that’s almost smart is often very, very dumb.
Ines Montani
OCTOBER 2, 2016
Today, we launched the website for our new company, Explosion AI. Explosion is a digital studio specialising in Artificial Intelligence and Natural Language Processing. We design algorithms, applications and data assets, and develop custom solutions to today’s AI problems. The past year has been pretty exciting and eventful. Things haven’t always been easy, but it feels good to finally be moving forward again.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Eugene Yan
OCTOBER 10, 2016
Parsing json and formatting product titles and categories.
Distill
OCTOBER 17, 2016
When we look very closely at images generated by neural networks, we often see a strange checkerboard pattern of artifacts.
Dataconomy
OCTOBER 18, 2016
Katharine Jarmul and Data Natives are joining forces to give you an amazing chance to delve deeply into Python and how to apply it to data manipulation, and data wrangling. By the end of her workshop, Learn Python for Data Analysis, you will feel comfortable importing and running simple Python analysis on your. The post Introduction to Data Science: How to “Big Data” with Python appeared first on Dataconomy.
Dataconomy
OCTOBER 7, 2016
Due to the advances of modern technology, there has been a great change in the academic landscape. This substantial change has already had a great impact on the overall performance of students due to the more sophisticated approach to learning in general. Historically speaking, traditional teaching methods had a great. The post How Big Data Can Improve Student Performance and Learning Approaches appeared first on Dataconomy.
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.
Dataconomy
OCTOBER 12, 2016
Whether it be diagnostics, treatment, or even a rehabilitation process, all medical procedures have an obvious goal: bringing benefits to patients. For instance, sonography requires using ultrasound waves for examining soft tissues; magnetic resonance, in turn, involves magnetic fields to make images. Neither waves nor magnets have negative influence on.
Dataconomy
OCTOBER 28, 2016
There is general agreement that language is the key to AI, but who holds the key to language – algorithms or people? According to the hype, the key to automated natural language understanding lies in vast data collections containing millions of words coupled with machine learning algorithms. If you believe. The post The key to AI with human-like language understanding?
Dataconomy
OCTOBER 17, 2016
This is a follow up to an article Per wrote last year, Machine Learning in a Week, on how he kickstarted his way into machine learning (ml) by devoting five days to the subject. Follow him on Medium and check out his archive. First intro: Hacker News and Udacity My interest in ml stems. The post Machine Learning in A Year, by Per Harald Borgen appeared first on Dataconomy.
Dataconomy
OCTOBER 14, 2016
Big Data and the Internet of Things are currently being lauded in many industries as the new frontier for business and, with seemingly ground-breaking solutions being rolled out for innumerable different use cases daily, it’s certainly not all hyperbole. At this moment, an estimated 4.9 billion sensors are connected to. The post Turning Big Data from Cost to Revenue appeared first on Dataconomy.
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
Dataconomy
OCTOBER 3, 2016
The Great Recession may have made many Millennials more sober about their job prospects but for the most talented of my generation, the economic difficulties of 2008 hardly registered as anything more than steeper online shopping discounts. In fact, in the last 8 years, they have become increasingly difficult to court. The post Why Employers Miss Millennial Data Scientists appeared first on Dataconomy.
Dataconomy
OCTOBER 16, 2016
For businesses to stay relevant in the 21st century and survive in an ultra competitive era, they have to continually be willing to change to stay ahead of the market curve. Change is always based on decisions and just about every Fortune 500 company knows that any important decision is. The post How Organizations Build Back-Ends for Big Data appeared first on Dataconomy.
Dataconomy
OCTOBER 20, 2016
When attending an Open Data Conference in Germany these days, one might wonder whether the participants have discovered a new type of species. A mysterious species that knows what to do with data. An intelligent species that is able to find treasures on confusing websites and to understand government speech. The post The State of Open Data in Germany: From Missed Opportunities to Great Successes appeared first on Dataconomy.
Dataconomy
OCTOBER 26, 2016
Subscription box businesses are more popular than ever, with average site visits growing by 3,000% over the past three years and revenue skyrocketing (Loot Crate, a DataScience customer, was ranked No.1 on the Inc 5000 fastest growing companies list this year with a whopping 66,789% growth in revenue since 2013). The post 3 Steps Data-Savvy Innovators use to Retain Customers appeared first on Dataconomy.
Speaker: Frank Taliano
Documents are the backbone of enterprise operations, but they are also a common source of inefficiency. From buried insights to manual handoffs, document-based workflows can quietly stall decision-making and drain resources. For large, complex organizations, legacy systems and siloed processes create friction that AI is uniquely positioned to resolve.
Dataconomy
OCTOBER 24, 2016
The recent explosion in data, connectivity and computing power – combined with powerful, new analytics tools – has sparked huge interest in data science. In response, forward-thinking businesses are looking at how they can derive insights from big data analytics to better understand their customer base and give them a. The post Mind the gap: What lessons can be learned to upskill the UK’s workforce in data science?
Dataconomy
OCTOBER 21, 2016
Migrating from an on-premise server to a cloud server will offer you a wide range of benefits. They range from a reduction to your involvement in database management to getting more advanced features from a third party whose main job is to offer the best database services. All in all, The post How-To: Migrate A Database from On-Premise to the Cloud appeared first on Dataconomy.
Dataconomy
OCTOBER 5, 2016
With over 20 years growing and leading technology companies, Frank Bien built his career on nurturing strong corporate culture and highly efficient teams. Prior to Looker, Frank was SVP of Strategy for storage vendor Virsto (acquired by VMware) and VP of Strategic Alliances at big-data pioneer Greenplum, leading their acquisition. The post “Companies are finally able to start a data culture” – Interview with Frank Bien, CEO of Looker appeared first on Dataconomy.
Dataconomy
OCTOBER 17, 2016
Last chance to buy tickets! Go to datanatives.io and register, and get instant access to speaker and schedule information on Data Natives Berlin 2016. Data Natives is just around the corner now, and so is the end of this series of Reasons Why You Should Attend Data Natives. If you are just joining, The post 5 Reasons to Attend Data Natives 2016: #4.
Speaker: Chris Townsend, VP of Product Marketing, Wellspring
Over the past decade, companies have embraced innovation with enthusiasm—Chief Innovation Officers have been hired, and in-house incubators, accelerators, and co-creation labs have been launched. CEOs have spoken with passion about “making everyone an innovator” and the need “to disrupt our own business.” But after years of experimentation, senior leaders are asking: Is this still just an experiment, or are we in it for the long haul?
Dataconomy
OCTOBER 21, 2016
Last chance to buy tickets! Go to datanatives.io and register, and get instant access to speaker and schedule information on Data Natives Berlin 2016. 5 days away from the conference, we have arrived at the fifth and last of the Reasons to Attend Data Natives – After Building A Strong. The post 5 Reasons to Attend Data Natives 2016: #5: Best Kept Secrets appeared first on Dataconomy.
Dataconomy
OCTOBER 17, 2016
Elizabeth Press from D3M Labs and Data Natives are joining forces to give you the opportunity to jump start your next innovation in one day during our 1-day workshop on October 26th Creating Innovative Data-as-a-Service Products. What is Data-as-a-Service? Data-as-a-Service (DaaS) can be described as productized data-driven insight on demand. The post Creating your data-as-a-service customer appeared first on Dataconomy.
Dataconomy
OCTOBER 10, 2016
This is the second instalment of a series about the second edition of Data Natives. I guess that ‘Doubles’ is the theme of this post. This time, we’ll talk about the conference schedule. By the way, the conference is approaching soon, so don’t sleep on the last chances to attend. The post 5 Reasons to Attend Data Natives 2016: #2. The Schedule appeared first on Dataconomy.
Dataconomy
OCTOBER 11, 2016
Ticket prices go up this Friday, October 14! Go to datanatives.io and register for a ticket, or get instant access to speaker and schedule information on Data Natives Berlin 2016. Welcome back to the 5 Reasons to Attend Data Natives Series. We started with Building a Strong Professional Network, went on to mention. The post 5 Reasons To Attend Data Natives 2016: #3.
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Dataconomy
OCTOBER 17, 2016
As of October 4th, the STORM team is traveling the US, with exciting events such as a visit to Tesla and Google, driving on the Golden Gate bridge – and a hackathon on the STORM data at Stanford University. What was the hackathon about? A simple task: let’s crunch some. The post Data Around The World Part VI: Hackathon at Stanford appeared first on Dataconomy.
Explosion
OCTOBER 18, 2016
I’m pleased to announce the 1.0 release of spaCy, the fastest NLP library in the world. By far the best part of the 1.0 release is a new system for integrating custom models into spaCy. This post introduces you to the changes, and shows you how to use the new custom pipeline functionality to add a Keras -powered LSTM sentiment analysis model into a spaCy pipeline.
Explosion
OCTOBER 18, 2016
I'm pleased to announce the 1.0 release of spaCy, the fastest NLP library in the world. By far the best part of the 1.0 release is a new system for integrating custom models into spaCy. This post introduces you to the changes, and shows you how to use the new custom pipeline functionality to add a Keras-powered LSTM sentiment analysis model into a spaCy pipeline.
Explosion
OCTOBER 4, 2016
Named Entity Recognition is a crucial technology for NLP. Whatever you're doing with text, you usually want to handle names, numbers, dates and other entities differently from regular words. To help you make use of NER, we've released displaCy-ent.js. This post explains how the library works, and how to use it.
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!
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