How banks can beat new finance boys with data

Previous post Next post            Tweet Tags: Banking, Data, Finance, Fintech The rise of Apple/Google smartphone payments and new fintech start ups present challenges to traditional banks. Banks can fight back, but they need to understand how to better use their data to understand its customers. comments By Adrian Kingwell, Founder and MD of Mezzo Labs. Marketers in…
Original Post: How banks can beat new finance boys with data

Details on First Data Science Job Salary

Previous post Next post            Tweet Tags: Advice, Career, ChangeFields, Data Science, Job, Salary A person new to the Data Science field details their salary and the negotiation process. By ChangeFields.comIn this post I want to talk money.  What I used to make, how the offer/negotiation process went and some tips for doing your own negotiation.  When I…
Original Post: Details on First Data Science Job Salary

Is Deep Learning Overhyped?

Previous post Next post            Tweet Tags: Deep Learning, Hype, Matthew Mayo, Quora, Yoshua Bengio With all of the success that deep learning is experiencing, the detractors and cheerleaders can be seen coming out of the woodwork. What is the real validity of deep learning, and is it simply hype? comments By Matthew Mayo. Editor: vote in new…
Original Post: Is Deep Learning Overhyped?

Useful Data Science: Feature Hashing

Previous post Next post            Tweet Tags: Feature Engineering, Hashing, Python, Will McGinnis Feature engineering plays major role while solving the data science problems. Here, we will learn Feature Hashing, or the hashing trick which is a method for turning arbitrary features into a sparse binary vector. comments By Will McGinnis. In the previous post about categorical encoding we…
Original Post: Useful Data Science: Feature Hashing

Deep Feelings On Deep Learning

           Tweet Previous post Next post Tags: Artificial Intelligence, Deep Learning, Emotion A thoughtful opinion piece on deep learning and its role in Strong AI. A pragmatic view of deep learning and its comparison to competing learning strategies is presented. comments By Carlos Argueta.So I want to build Artificial Emotional Intelligence (AEI), and I already wrote about a possible application…
Original Post: Deep Feelings On Deep Learning

Sentiment Analysis & Predictive Analytics for trading. Avoid this systematic mistake

           Tweet Previous post Next post Tags: Johan Bollen, Mistakes, Sentiment Analysis, Stocks The financial market is the ultimate testbed for predictive theories. With this post we want to highlight the common mistakes, observed in the world of predictive analytics, when computer scientists venture into the field of financial trading and quantitative finance. comments By Lars Hamberg. Many…
Original Post: Sentiment Analysis & Predictive Analytics for trading. Avoid this systematic mistake

Data Analytics Boosting Digital Engagement at Australian Open 2016

           Tweet Previous post Tags: Advanced Analytics, Classification, Cloud Computing, IBM, IBM Watson, Predictive Analytics, Real-time, Sports Advanced analytics and visualization is enhancing fan experience and operational excellence at Australian Open 2016 By Anmol Rajpurohit, @hey_anmol Australian Open 2016 will be an unprecedented experience for every fan, thanks to the partnership between Tennis Australia and IBM. The next-generation…
Original Post: Data Analytics Boosting Digital Engagement at Australian Open 2016

Beyond the Fence, and the Advent of the Creative Machines

           Tweet Previous post Tags: AI, Art, Deep Neural Network, Matthew Mayo Creative machines have been making their influence felt for some time, but an upcoming stage production challenges preconceived notions of what art is. comments By Matthew Mayo.Computers being involved in the creation of art is not a new development.(Consider my use of the word computer throughout…
Original Post: Beyond the Fence, and the Advent of the Creative Machines

Spark and the Remorseless Recrystallization of the Open Source Analytics Ecosystem

           Tweet Previous post Next post Tags: Apache Spark, Hadoop, James Kobielus Apache Spark had robust machine learning, graph, streaming, and in-memory capability to the Hadoop-centric ecosystem. In 2016, we expect adoption in diverse big data, advanced analytics, data science, Internet of Things, and other application domains. comments By James Kobielus, Big Data Evangelist, IBM Software. Open source…
Original Post: Spark and the Remorseless Recrystallization of the Open Source Analytics Ecosystem

Hadoop and Big Data: The Top 6 Questions Answered

Hadoop and Big Data: The Top 6 Questions Answered            Tweet Previous post Next post Tags: Apache Spark, Big Data, Data Warehouse, Hadoop, Implementation 6 questions surrounding Hadoop and Big Data are posed and answered, including those related to implementation, management, and practical uses. Find out where Hadoop currently sits in the world of Big Data. comments By…
Original Post: Hadoop and Big Data: The Top 6 Questions Answered