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.
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.
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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?
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.
Christian Haschek
OCTOBER 25, 2016
In the end of WW2, when Vienna was overtaken by allied forces, the Wehrmacht was pushed in the w
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.
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.
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.
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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.
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.
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.
Speaker: Scott Sehlhorst
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
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.
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.
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.
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.
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.
Speaker: Kevin Kai Wong, President of Emergent Energy Solutions
In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.
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.
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.
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.
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.
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 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.
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. As of spaCy v2.0 , the displaCy ENT visualizer is integrated into the core library.
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Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.
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