Dataconomy
DECEMBER 21, 2016
From Decentralized Model Exchanges to Model Audit Trails [This is based on a talk I first gave on Nov 7, 2016. Here are the slides.] In recent years, AI (artificial intelligence) researchers have finally cracked problems that they’ve worked on for decades, from Go to human-level speech recognition. A key piece. The post How Blockchains could transform Artificial Intelligence appeared first on Dataconomy.
Hacker News
AUGUST 25, 2016
When a friend says something interesting to me, I usually don’t have a reaction until much later. When someone asks me a deep question, I say, “Hmm. I don’t know.” The next day, I have an answer. I’m a disappointing person to try to debate or attack. I just have nothing to say in the moment, except maybe, “Good point.” Then a few days later, after thinking about it a lot, I have a response.
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Eugene Yan
OCTOBER 22, 2016
A card sorting game to discover youl passion by identifying skills you like and dislike.
Distill
DECEMBER 6, 2016
Several interactive visualizations of a generative model of handwriting. Some are fun, some are serious.
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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?
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.
Christian Haschek
OCTOBER 25, 2016
In the end of WW2, when Vienna was overtaken by allied forces, the Wehrmacht was pushed in the w
Dataconomy
DECEMBER 2, 2016
Interest in fintech disruption is at an all-time high, but who will be the winners and who the losers is far from clear. Banks themselves have been sending mixed messages. As a particularly high profile example, JP Morgan Chase CEO Jamie Dimon famously raised the alarm when he said in. The post What are banks telling to their investors about FinTech?
Dataconomy
DECEMBER 27, 2016
The world of business and customer service has changed immensely over the past few years. Whereas once business was largely driven by outbound marketing and advertising, in today’s world you have to consider the customer experience and your customers’ journey as they interact with your brand. Today, thanks to the. The post Using Data to Discover Hidden Value in Your Customer Journey appeared first on Dataconomy.
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.
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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 19, 2016
Fighting fraud, reducing customer churn, improving the bottom line – these are just a few of the promises of data science. Today, we have more data to work with than ever before, thanks to new data-generating technologies like smart meters, vehicle telemetry, RFID, and intelligent sensors. But with all that. The post Driving Value with Data Science appeared first on Dataconomy.
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
DECEMBER 7, 2016
Smartphones have made it possible for businesses to monitor you at all times. Take a company like Google for example. You may look up the name of a restaurant over Google Search, turn on your navigation to the destination using Google Maps and perhaps also check for weather and traffic. The post 4 Ways Predictive Data Analytics Changes How Consumers Behave 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: 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 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
SEPTEMBER 14, 2016
Big data isn’t just a career for the future, it’s a promising field today with room for incredible growth. More businesses have come to realize the numerous benefits they stand to gain through adopting big data analytics, and that has lead to a surge in hiring data scientists and those. The post Getting Off to a Great Start in Your Big Data Career 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
DECEMBER 14, 2016
The term ‘Fintech’, applies to a very broad range of innovative solutions for the financial sector. Because this term is so broad, it doesn’t just impact financial businesses. All kinds of companies must make financial decisions, accept payments, and pay invoices. Since new and cutting-edge financial tools may impact the. The post 4 Things Businesses Need to Know About Fintech appeared first on Dataconomy.
Dataconomy
NOVEMBER 16, 2016
Over the last decade, we have seen massive changes in technology. It now has a role in nearly every aspect of our lives, including health care technology. Since technology is changing every industry, MW Homecare decided to focus their infographic on health care technology and how it is disrupting and changing. The post Infographic: How Tech Is Disrupting The Traditional Healthcare Market 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.
Dataconomy
NOVEMBER 11, 2016
Following the success of our Creating Data-as-a-Service Products at Data Natives, Elizabeth Press from D3M Labs and Dataconomy are joining forces to give your organization the opportunity to jump start your next innovative data product. Contact us to book a training specifically designed for your organization. Even though analysts publish optimistic.
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
NOVEMBER 21, 2016
Nicolas Boudot is the EMEA Director at Softbank Robotics, where he has been responsible for partnerships and for promoting the use of humanoid robots in the B2B, educational and consumer markets, since 2001, when Aldebaran Robotics, the makers of Nao humanoid robots, was acquired by Softbank Mobile. He has. The post “AI is the next step for robots” – A Conversation with Nicolas Boudot 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
NOVEMBER 14, 2016
There’s a long history of industries undergoing massive transformations fueled by the power of digital data. The moment has arrived for data to help reshape one of the largest industries of the digital age: marketing. 2016 has been a challenging year for the marketing community, with an eye-opening media transparency. The post Data Transparency Could Fix Digital Marketing appeared first on Dataconomy.
Dataconomy
SEPTEMBER 12, 2016
Thinking about going the cloud-route for your big data analytics strategy? You’re not alone. Suddenly, the cloud has become a hot topic in the analytics software world and in particular big data analytics. While customer relationship management (CRM) software and other applications, like payroll and expense reporting, have steadily moved. The post Thinking About Cloud Data Analytics?
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 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
NOVEMBER 25, 2016
Kathleen Kennedy is the president of MIT Technology Review and the MIT Enterprise Forum. MIT technology review is MIT’s media platform and it covers emerging technologies and their impact. Their job is to help the audience understand the world shaped by technology, and obviously data is one of those huge. The post “Before big data and all the buzzwords, it was all data mining” – Kathleen Kennedy, MIT Technology Review appeared first on Dataconomy.
Dataconomy
DECEMBER 12, 2016
Springboard launches data science bootcamp with a job guarantee – Springboard is launching its Data Science Career Track — the first online data science bootcamp that offers a job guarantee to its graduates. The company tracked 50 of its graduates and saw that all 50 got a job within six. The post This is the Data Science bootcamp that guarantees a data science job or a 100% tuition refund 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.
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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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