An explanation of how classification developed as a learning machine, from LDA to the perceptron, on to logistic regression, and through to support vector machines.
The Chief Data Officer Summit is coming to San Francisco on May 26 & 27 with speakers from Amazon, eBay, The World Bank, Bing, PayPal, US. Dept of Commerce and many more. Get a 10% discount with code KD10.
Any company that has decided to put efforts in data has to face bringing these projects from the design and development phase to the production phase at some point. So tell us how you do it. And we’ll tell you what we learned from you.
The summit will feature 2 leaders in the field as keynote speakers, and 17 companies presenting in the all-day industry tracks focusing on retail and consumer analytics, healthcare analytics, supply chain analytics, finance and insurance analytics and a special "bonus" track.
The classic guide for entrepreneurs preparing a pitch is Sequoia’s Business Plan Template. This post aims to be a mere addendum to that in the age of machine learning.
A survey requesting feedback from data scientists on their opinion of what an interesting result is. The survey is anonymous, has only a single mandatory question, and takes only 5 minutes.
On May 5th, Dr. Kristopher Overholt and Dr. Matthew Rocklin of Continuum Analytics will present a webinar on High Performance Hadoop with Python. Reserve your spot today!
The idea of citizen data scientists is being for more than a year, which suggests businesses to put the people from the business side in the work of exploring and analyzing data. Understand how you and your organisation can be benefitted by this.
Art has always been deep for those who appreciate it... but now, more than ever, deep learning is making a real impact on the art world. Check out this graduate course, and its freely-available resources, focusing on this very topic.
Today is the 80th anniversary of the death of Karl Pearson, one of the founding father of statistics (correlation coefficient, principal components, the p-value, and much more). He was also deeply involved with eugenics, a jarring reminder that truth often comes bundled with a measure of darkness.
Data Science helps see where your country will stand in WW 3; Recommender Systems: New Comprehensive Textbook; Good read: Deep Learning in Neural Networks - extreme summary; The Race For #AI: Google, Facebook, Amazon, Apple rush to grab #AI startups.
Dealing with huge datasets can be tricky, especially the data cleaning process. One of such processing is de-duplication, find out how you can solve this using the statistical techniques.
An overview of the very best that Udemy has to offer in data science education. Includes courses covering machine learning, Python, Hadoop, visualization, and more.
People have a tendency to blindly trust claims from any source that they deem credible, whether or not it conflicts with their own experiences or common sense. Basic stats - common sense = dangerous conclusions viewed as fact.
This post summarizes Schmidhuber's now-classic (and still relevant) 35 page summary of 900 deep learning papers, giving an overview of the state of deep learning as of 2014. A great introduction to a great paper!
This post is an overview and discussion of Microsoft's increasing investment in, and approach to, artificial intelligence, and how their philosophy differs from their competitors.
When Does Deep Learning Work Better Than SVMs or Random Forests?; Comprehensive Guide to Learning Python for Data Analysis and Data Science; Top 15 Frameworks for Machine Learning Experts; Top 10 IPython Notebook Tutorials for Data Science and Machine Learning
See how machine learning is making bots more human than ever - read the interview with a 17-year-old Chinese girl named XiaoIce who is actually a artificially intelligent chatbot.
Transforming your business with (big) data analytics and data-driven insights is not a one-time event, but a journey. Here are 6 steps to help enterprises become data-science driven business and enjoy benefits along the way.
As the rampant growth of data science continues across industries, the opportunities are plenty for both aspiring and expert data scientists. Here is an overview of data science industries, opportunities and work locations.
Chicago is whirling together four great analytics events on June 20-23, but early bird rates will blow away after May 6. Use KDN150 for additional savings.
Kdb+ time-series database provides high performance analytics on very large-scale datasets. Kdb+ users and coders will gather for KxCon2016, 3 days of presentations and hands-on workshops.
Gartner officially deemed 2016 the year of Modern BI and with this new era of BI changes are inevitable. Understand how the traditional BI is reshaping in this data century with Scrollytelling, citizen data scientist and new BI approaches.
A list of 10 useful Github repositories made up of IPython (Jupyter) notebooks, focused on teaching data science and machine learning. Python is the clear target here, but general principles are transferable.
Learn how to set up a modern pipeline that collects, processes, and analyzes high-volume, machine-generated data. We’ll talk about popular collection mechanisms, do a hands-on log-parsing example in Spark, and discuss how to use Looker to get insights from event data.
Exciting addition to Data Day: CMO of The Walt Disney Company Australia/New Zealand will speak about re-igniting the iconic Star Wars brand, and how his team used insights to target marketing activities to a broad range of consumers, leading up to the launch of Star Wars: The Force Awakens.
Successful analytics in the big data era does not start with data and software, but with hands-on, immersive training and goal-driven strategy - get it from The Modeling Agency in Washington, DC, May 16-20 and May 23-24.
The second of 2 posts expanding upon a now-classic neural network blog post and demonstration, guiding the reader through the workings of a simple neural network.
The MS in Analytics at Pacific develops students’ technical skills though courses such as Data Wrangling, Machine Learning, and Dynamic Visualization. Students gain hands-on experience and industry connections to become game changers across multiple industries.
A collection of company data science blogs to follow and read. Top blogs have links to, and excerpts from, recent quality posts of particular interest.
The first part of this 2 part series expands upon a now-classic neural network blog post and demonstration, guiding the reader through the foundational building blocks of a simple neural network.
Want to make a career change to Data Science using python? Well learning anything on your own can be a challenge & a little guidance could be a great help, that is exactly what this article will provide you with.
Your company needs a data scientist... doesn't it? It very well may not, but you need to know either way. Read on to determine whether or not your company could benefit from the skills of an on-board data scientist.
The first in a series of tutorial posts on using Deep Learning for chatbots, this covers some of the techniques being used to build conversational agents, and goes from the current state of affairs through to what is and is not possible.
At Chicago's Predictive Analytics World for Business conference, June 20-23, 2016, and at New York’s PAW Business conference, uplift modeling will be covered in eight ways: across keynotes, sessions, and an article by PAW founder Eric Siegel. KDnuggets subscribers enjoy $150 off!
Either you are a researcher, start-up or big organization who wants to use machine learning, you will need the right tools to make it happen. Here is a list of the most popular frameworks for machine learning.
A great guide for the MBA, or any relatively non-technical convert, for getting comfortable with the command line and other technical skills required to excel in data science.
New Deep Learning Book Finished; A Pocket Guide to Data Science; 7 Steps to Mastering Machine Learning With Python; From Science to Data Science, a Comprehensive Guide for Transition; Automated Machine Learning: Changing the Game
"Connected" and "smart" are not synonyms, and bridging the gap takes a lot of upfront work; but with work invested in identifying, understanding and supporting the key decisions, the more productive the data science will be.
We are proud to introduce our GraphDB 7.0, the newest generation of semantic graph databases - it makes Powerful for Big Data Analytics a lot easier. Learn more at Apr 21 and Apr 28 webinars.
The idea of using artificial intelligence for the crime prevention has been around for more than a decade. In this post, we present four examples, including how using analytics, we can prevent a criminal from re-offending.
This is a fast paced, vendor agnostic, technical overview of the Big Data landscape. No prior knowledge of databases or programming is assumed. Use code KDNUGGETS to save.
Do you have free time for reading this weekend? Here are a few new (or refreshed) selections of varying length for your leisure, along with a pair of papers, one cutting edge, and one classic.
KDnuggets is happy to introduce another tool for our readers in the process of looking for jobs: the @KDnuggetsJobs Twitter account, dedicated to sharing our Analytics, Data Science, and Big Data job listings.
Chicago is whirling together four analytics events, June 20-23, 2016. Don't let the bird rates fly away - register by May 6 for best rates and getting extra saving with code KDN150.
It’s been well documented that women don’t come close to parity in STEM fields with their counterparts. Could the rise of big data and data science offer women a clearer path to success in technology? Here’s a list of 12 inspiring women who work in big data and data
Covers recommender systems comprehensively, both fundamentals and advanced topics, organized into: Algorithms and evaluation, recommendations in specific domains and contexts, and advanced topics and applications.
Making sense of the mountains of data collected on a daily basis requires specialized data science skills that are hard to come by, and hard to keep. Augmented or even eliminated some of these specialized tasks with machine learning.
How Zynga is “home growing” its own data science talent from the inside, by retraining some of our top analysts and engineers to become data scientists.
Delivering data and analytics to your customers should be straightforward. The Looker Data Platform allows for easy access to data through a robust API and embeddable charts, tables and dashboards.
Deep Learning for Beginners - notes by research leaders ; Here is how Matt Harvey used #MachineLearning to predict #Villanova win; Brilliant #Dilbert cartoon: Management class on NOT listening finally pays off; #DeepLearning: 5 People To Know @AndrewYNg @Ylecun @karpathy @Peteskomoroch;
#use Text Control: No formatting, No Character Formatting, Template: Default
For data exploration, discovery, and collaborative analytics, AirBnB have built and open sourced, a data exploration and dashboarding platform named Caravel. It allows data exploration through rich visualizations while performing fast and intuitive “slicing and dicing” of your dataset.
Self-service analytics is likely to spread in all the business layers, and with proper care to avoid certain risks, the culture of self-service analytics will help all organizations.
What are the use cases for machine learning? What's the typical analytics workflow? Should we have a data science team? Should we outsource our analytics? Help IDC and KDnuggets answer these questions and read the results on KDnuggets and in other places.
An in-depth, multifaceted, and all-around very helpful roadmap for making the switch from 'science' to 'data science,' yet generally useful for data science beginners or anyone looking to get into data science.
What will likely become known as the seminal book on deep learning is finally finished, with the online version finalized and freely-accessible to all those interested in mastering deep neural networks.
Spots are limited for the upcoming training workshops at Predictive Analytics World for Business, June 20-23, 2016 in Chicago. Check the new Hadoop workshop and instruction about advanced methods, modeling methods, R, and more – reserve your spot today.
The IoT is one of a number of new sources, along with social media and wearable computing, which can be combined with data science, collectively as the Big Data Killer App for organizations.
A pocket guide overview of how to get started doing data science, with a focus on the practical, and with concrete steps to take to get moving right away.
A new data science report with survey results related to the success and challenges of data scientists, and where data science is going as a discipline.
ACM SIGKDD Innovation and Service Awards recognize outstanding technical innovations and outstanding professional contributions to the field of Big data, Data Mining, Knowledge Discovery, and Predictive Analytics.
7 Steps to Mastering Machine Learning With Python; Top 10 Essential Books for the Data Enthusiast; Deep Learning for Internet of Things Using H2O; Basics of GPU Computing for Data Scientists.
My very-high level overview of Deep Learning for Delta Sky Magazine, including neurons, a conspiracy, games, amazing feats of superhuman ability, and more - appropriate for reading at 30,000 feet.
Very few "All-access" passes remain for the Big Data Festival in San Francisco, Apr 21-22, which let to access Big Data Innovation (Keynotes: Uber, US Dept of Commerce, Airbnb, LinkedIn), Internet of Things Summit (Keynotes: Apple, Samsung, ...), and Data Visualization Summit (Keynotes: MasterCard, NASA, Pinterest).
Deep neural networks have had remarkable success with many tasks including image recognition. Read this overview regarding deep learning trickery, and why you should be cognizant.
Online open data repository and browser-based interaction site Our World in Data, from the University of Oxford, is a fantastic site for data-driven exploration.
if you are an analyst working within or supporting the marketing department or advising senior decision makers, you'll definitely want to attend ADMA Data Day - Sydney, April 27 or Melbourne, April 29.
JSU is among the first minority serving institutions to create a Big Data focused doctoral and graduate program for MS and PhD in Computational and Data-Enabled Science and Engineering - apply now.
If you're interested in a career in data science, check new full-time 12-week hands-on program offered by Logit, taught by data scientists from top institutions in Southern California, including UCLA, USC and Caltech.
Read about the presentation and overview of a new deep neural network architectural method, and the response to some strong reaction that it brought about.
Join industry leaders at the inaugural Marketing Analytics & Data Science conference, San Francisco, June 8-10. KDnuggets readers enjoy a 20% discount.
With the rise of neural network in data science, the demand for computationally extensive machines lead to GPUs. Learn how you can get started with GPUs & algorithms which could leverage them.
This year’s 2016 ODSC East brings together the most influential data scientists, practitioners, innovators, and thought leaders in data science and big data, including many open source data science pioneers.
Top 10 Essential Books for #Data Enthusiast; If Hollywood Made #Movies About #MachineLearning; Learning to Code Diminishing Returns - coders training their digital replacements.
Linkurious is a partner of the International Investigative Journalist Consortium (ICIJ) since the Swiss Leaks scandal. ICIJ network of 370 journalists is using Linkurious to investigate the Panama Papers. Learn the inside story of the biggest data leak investigation in history.
H2O is feature-rich open source machine learning platform known for its R and Spark integration and it’s ease of use. This is an overview of using H2O deep learning for data science with the Internet of Things.
With the number of people claiming to be a data scientist growing, the “true” data scientists are becoming hard to find. Here your guide identify the clues to catch a bad data scientists.
R Learning Path: From beginner to expert in 7 steps; R or Python? Consider learning both; Distributed TensorFlow Has Arrived; The Data Science Process, Rediscovered.
We are pleased to announce the outstanding program for Predictive Analytics World for Business, June 20-23 in Chicago. KDnuggets readers get reduced rate with code KDN150.
With the rising wave of IoT devices, businesses everywhere are faced yet with another challenge: to ensure an adequate security level while also continuously integrating new technologies.
Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Apr 14.
This article makes a case for the importance of innovating using open data, its also proves that adapting open data principles with visual design can enhance transparency, foster accountability, and aid citizen and voter education in elections.
The Penn State World Campus online MPS in Data Analytics – Business Analytics Option curriculum focuses on exploring and analyzing large data sets to support data-driven business decisions. Apply by July 1 to take classes in August.
Successful analytics in the big data era does not start with data and software, but with hands-on, immersive training and goal-driven strategy - get it from The Modeling Agency in Washington, DC, May 16-20 and May 23-24.
Learn how to solve more scientific, engineering and business problems correctly and faster by extracting powerful insights from existing data using proven, simple statistical modeling methods. Watch the webcast.
Could Data Science in the insurance industry actually reduce the price of policies, as individual companies and people are no longer being judged against the average, and might be incentivised to change their lifestyle to improve their policy?
So your March Madness bracket is busted. Maybe that new algorithm can through the first round next year. It's never too early to start building your analytics Dream Team.
What's huggable, adversarial images for deep learning, overview of real-time 3D face capture and reenactment, deep learning quadcopter navigation, and a whole lot of AlphaGo!
Coming soon: MLConf NYC, PAKDD, Big Data Innovation Summit West, SDM 16, PASS Business Analytics Conference, TDWI Chicago, Apache Big Data North America, RE.WORK Deep Learning Summit, and many more.
100 Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning; How To Become A Machine Learning Expert In One Simple Step; R Learning Path: From beginner to expert in R in 7 steps; 7 Steps to Mastering Machine Learning With Python.
How Shutterstock created computer-vision and Deep Learning technology that understands their 70 million-plus images and takes away the need for customers to type in descriptions and unreliable keywording. The technology relies on pixel data as its language of choice.
A unique top 10 list of book recommendations, for each of 10 categories this list provides a top paid and top free book recommendation. If you're interested in books on data, this diverse list of top picks should be right up your alley.
When Does Deep Learning Work Better Than SVMs or Random Forests®?
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