Tag: data scientist

Feed: Featured Blog Posts - Data Science Central. Author: Dr. Olav Laudy. “We want to predict -X-.” Fill in any desirable topic on the location of the X and you have the formulation of a use-case in the way many companies today think about analytics use-cases. In order of increasing probability of success of such use-cases: X equals the winning lottery number, the future price of crude oil, windows falling from high-rise buildings (not kidding; actual use-case) and finally, a customer buying a mortgage. This post deals with understanding the importance of the use-case identification. The word ‘identification’ here hints ... Read More

Feed: Alation. Author: Stephanie McReynolds. We’ve seen the trend first hand. Organizations who are so successful in their adoption of self-service analytics, that their own business intelligence (BI) evangelists worry that they’ve created an analytics “wild west.” When they see a data catalog for the first time, they’re thrilled that a product exists that can govern the west and increase analyst productivity. This week Dresner Advisory Services released their Data Catalog Market Study and BI end users validated the market for data catalogs.If you’re not familiar with them, Dresner Advisory Services conducts broad-based, end user studies of the BI market ... Read More

Feed: Alation. Author: Satyen Sangani. I’m excited to announce an expansion of our partnership with Trifacta.If you’re someone interested in where the BI/Analytics industry is going, a CIO/CDO trying to pick the stack for your BI/Analytics investments, or if you’re an analyst just trying to figure out which tool is most relevant for your needs, here’s why I think this news is important: You could frame most technological innovations in terms of democratizing access. Publishing used to be the province of big newspapers. With blogs, anyone can now write and distribute an article and with message boards anyone can post ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. Monday newsletter published by Data Science Central. Previous editions can be found here.  The contribution flagged with a + is our selection for the picture of the week. Featured Resources and Technical Contributions Deep Learning with TensorFlow in Python + Using Uninformed & Informed Search Algorithms - to Solve 8-Puzzle (n-Puzzle) in Python  Python: Implementing a k-means algorithm with sklearn  Image and Video Processing: Motion Estimation, Image Restoration  Semi-Supervised Classification using Markov Chain and Random Walk  Data Modelling Topologies of a Graph Database  The 10 Algorithms Machine Learning Engineers Need to Know  ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Roy Wilds, PhD, PHEMI Systems. In the first post in this series on Artificial Intelligence: Monster or Mentor? we saw that there are several key ways in which AI advances can improve human productivity in organizations. In this article, we’ll look at the first: Distillation.Distillation is applying AI approaches to automate making large data volumes interpretable. Just like miners distill tons of raw ore into ounces of gold using machines, the goal is to automate the identification of value in big data. Here, we’ll focus specifically on how Distillation can be ... Read More

Feed: Big Data Made Simple - One source. Many perspectives.. Author: Baiju NT. DJ Patil, the current Chief Data Scientist of the United States and previously the Head of Data Products at Linkedin, is the one who first coined the term “data science”. DJ posits that, “the dominant trait among data scientists is an intense curiosity—a desire to go beneath the surface of a problem, find the questions at its heart, and distill them into a very clear set of hypotheses that can be tested.” There is no mention here of a strict definition of data science, nor of a ... Read More

Feed: Hortonworks Blog – Hortonworks. Author: Saumitra Buragohain. This blog has contributions from: Vinod Vavilapalli, Wangda Tan, Gour  Saha, Priyanka Nagwekar, Sunil Govindan You have probably wondered what makes a self-driving car intelligent to process the live camera feeds, navigate the busy streets and distinguish objects on the streets, such as cars, trucks, traffic lights or pedestrians? A self-driving car is a perfect example of a modern data application that combines big data with smart algorithms. To understand the underpinnings of such a modern data app, we will start with a recap of our blog series titled “Data Lake 3.0” ... Read More

Feed: Planet big data. Author: Irina Peregud. 20 June 2017Author Irina PeregudData scientist remains the “hottest” job of the XXI century. Data Scientists are in high demand in every industry while candidates are in short supply and it’s getting harder to attract the rare talent and make them stay. In the Glassdoor report on the most popular vacancies in the USA, Data Scientist was ranked #1 and was named “the best job in America”!Offering data science as a service, and developing its AI-driven products, InData Labs like no other company feels that there is a shortage of experienced professionals in ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: William Vorhies. Summary:  There’s a three way technology race to bring faster, easier, cheaper, and smarter AI.  High Performance Computing is available today but so are new commercial versions of actual Quantum computers and Neuromorphic Spiking Neural Nets.  These two new entrants are going to revolutionize AI and deep learning starting now.   AI and Deep Learning has a Problem - Three Actually. Time:  The amount of time needed to train a deep net like a CNN or an RNN can be weeks.  This doesn’t count the weeks or months in ... Read More

Feed: Cloudera Engineering Blog » CDH. Author: Justin Kestelyn. Thanks to Michal Malohlava, Amy Wang, and Avni Wadhwa of H20.ai for providing the following guest post about building ML apps using Sparkling Water and Apache Spark on CDH. The Sparkling Water project is nearing its one-year anniversary, which means Michal Malohlava, our main contributor, has been very busy for the better part of this past year. The Sparkling Water project combines H2O machine-learning algorithms with the execution power of Apache Spark. This means that the project is heavily dependent on two of the fastest growing machine-learning open source projects out ... Read More