Category: Python

Feed: Featured Blog Posts - Data Science Central. Author: Venkat Raman. Many of us are bombarded with various recommendations in our day to day life, be it on e-commerce sites or social media sites. Some of the recommendations look relevant but some create range of emotions in people, varying from confusion to anger. There are basically two types of recommender systems, Content based and Collaborative filtering. Both have their pros and cons depending upon the context in which you want to use them. Content based: In content based recommender systems, keywords or properties of the items are taken into consideration ... Read More

Feed: Planet big data. Author: Julie Steele. November 21st, 2017 Many of us here at SVDS rely on Caltrain, Silicon Valley’s commuter rail line, to commute to and from the office every day. As part of an ongoing R&D effort, we have been collecting and analyzing various sources of Caltrain-related data with the goal of determining where each train is, and how far behind schedule it’s currently running. In addition to video cameras and microphones, we use social networking platforms as sources of signal to detect service disruptions or delays as they’re reported on by the affected passengers. Twitter is ... Read More

Feed: R-bloggers. Author: Kathryn Bryant. Introduction Residential real estate prices are fascinating… and frustrating. The homebuyer, the home-seller, the real estate agent, the economist, and the banker are all interested in housing prices, but they’re sufficiently subtle that no one person or industry has a complete understanding. For our third overall project and first group project we were assigned Kaggle’s Advanced Regression Techniques Competition. The goal, for the project and the original competition, was to predict housing prices in Ames, Iowa. While this particular competition is no longer active, the premise proved to be a veritable playground for testing our ... Read More

Feed: All - O'Reilly Media. Author: Simon Chan. Yin, yang (source: Pixabay) To learn more about applying data science to your business, check out the machine learning sessions at the Strata Data Conference in San Jose, March 5-8, 2018. Registration is now open. The promises of AI are great, but taking the steps to build and implement AI within an organization is challenging. As companies learn to build intelligent products in real production environments, engineering teams face the complexity of the machine learning development process—from data sourcing and cleaning to feature engineering, modeling, training, deployment, and production infrastructure. Core to ... Read More

Feed: MemSQL Blog. Author: Mike Boyarski. Data growth and diversity has put new pressures on traditional data warehouses, resulting in a slew of new technology evaluations. The data warehouse landscape offers a variety of options, including popular cloud solutions that offer pay-as-you-go pricing in an easy-to-use and scale package. Here are some considerations to help you select the best cloud data warehouse. A cloud data warehouse support numerous use cases for a variety of business needs. Here are some common use cases along with the notable capabilities required for each.   Ad Hoc Analysis Ad hoc analysis provides guided or ... Read More

Feed: Cloudera Engineering Blog » Cloudera Manager. Author: Justin Kestelyn. The new cluster templates feature in Cloudera Manager 5.7 makes creating clusters faster and easier. Often, after an Apache Hadoop cluster has been configured correctly, its admin will want to replicate the configuration in one or more clusters—whether for promoting a dev or staging cluster to production, or setting up a new production cluster with the same configuration as an existing one. For Cloudera customers, until recently the process for replicating cluster configurations was manual and error-prone. Starting in Cloudera Manager 5.7, the cluster templates feature make this process faster, ... Read More

Feed: Redis Labs. Author: Jay Johnson. Utilizing a machine learning API to create a scalable model artifact pipeline Managing large, pre-trained predictive models across an organization and ensuring the same version is in production can be a challenge with the rapid pace of changes in the AI/machine learning space. Here, we have an approach that demonstrates how to automate building, storing, and deploying predictive models from a Remote Machine Learning Data Store hosted on Redis Labs. This approach is focused on showing how DevOps CI/CD artifact pipelines can be used to build and manage machine learning model artifacts with Jupyter ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Emmanuelle Rieuf. Jupyter notebook content for my OReilly book, the Python Data Science Handbook. This repository contains the full listing of IPython notebooks used to create the book, including all text and code. The code was written and tested with Python 3.5, though most (but not all) snippets will work correctly in Python 2.7. See also the free companion project, A Whirlwind Tour of Python: a fast-paced introduction to the Python language aimed at researchers and scientists. Table of Contents Preface 1. IPython: Beyond Normal Python Help and Documentation in IPython Keyboard Shortcuts ... Read More

Feed: AWS Big Data Blog. Air travel can be stressful due to the many factors that are simply out of airline passengers’ control. As passengers, we want to minimize this stress as much as we can. We can do this by using past data to make predictions about how likely a flight will be delayed based on the time of day or the airline carrier.In this post, we generate a predictive model for flight delays that can be used to help us pick the flight least likely to add to our travel stress. To accomplish this, we will use Apache ... Read More

Feed: Planet big data. Author: Guest Blogger. by Lixun Zhang (Data Scientist), Ye Xing (Senior Data Scientist) and Tao Wu (Principal Data Scientist Manager), all at Microsoft Editor's Note: To learn more about migrating from SAS to R, there will be a live webinar presented by Lixun and Ye tomorrow (Tuesday, November 15). Register to attend the webinar here. R has been gaining in popularity among data professionals in recent years in industries such as financial services, as shown for example in this survey from executive search firm Burtch Works. In this blog post we share some key considerations in migrating ... Read More