20 Questions to Detect Fake Data Scientists; TensorFlow Disappoints - Google Deep Learning falls shallow; 7 Common Data Science Mistakes and How to Avoid Them; Businesses Will Need One Million Data Scientists by 2018.
Data ScienceTech Institute announces the upcoming online education, allowing off-campus education in its programs MSc Data Scientist Designer and MSc Executive Big Data Analyst.
Academic/Research positions Analytics and Data Science at INRIA, U. Texas, U. Mannheim, Eindhoven U. of Technology, IBM Social Good Fellowship, Yale, Xavier, U. Western Switzerland, U. Paris-Est Marne-la-Vallee, and U. Tampere.
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.
A post describing the key differences between Pandas and Spark's DataFrame format, including specifics on important regular processing features, with code samples.
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?
Originally created by Booz Allen Hamilton for its team of nearly 600 data science professionals, Explore Data Science is now available exclusively from Metis for $99 for 2 months access.
Understand why big data is so important in business decisions, improve your data management skills, and join the rapidly growing analytics field. Classes Feb 18 - May 25, 2016 in Wilmington, DE.
The integration of TensorFlow with Spark leverages the distributed framework for hyperparameter tuning and model deployment at scale. Both time savings and improved error rates are demonstrated.
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.
A detailed explanation of one of the most used machine learning algorithms, k-Nearest Neighbors, and its implementation from scratch in Python. Enhance your algorithmic understanding with this hands-on coding exercise.
With mathematical rigor and narrative flair, Adam Kucharski reveals the tangled history of betting and science. The house can seem unbeatable. In this book, Kucharski shows us just why it isn't. Even better, he shows us how the search for the perfect bet has been crucial for the scientific pursuit of a better world.
ESSEC Specialization on “Strategic Business Analytics” was ranked #5 most coveted Coursera certificate on LinkedIn in 2015. The course is aimed at students, business analysts and data scientists who want to apply statistical knowledge and techniques to business contexts.
How to take data science techniques even further to extract actionable insight and take advantage of advanced modeling features. You will walk away with several different methods to turn your ordinary regression into an extraordinary regression!
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 Feb 9.
Modern big data discovery tools enable all employees to access the data, streamlining the data prep process, and allowing data scientists to spend more time on advanced analytics. The infographics in this post show the evolution of the data scientist from data drudgery to modern data science for all.
Data scientist in business is as similar as to that of a detective: discovering the unknown. But, while venturing onto this journey they do tend to fall into the pitfalls. Understand, how these mistakes are made and how you can avoid them.
Lights, camera, and analytics action! Early bird rates end Feb 5th for three incredible analytics conferences in San Francisco. Save with KDnuggets code KDN150.
TextAnalytics examines: Is #Quran really more violent that #Bible? Why R Users will inevitably become #Bayesians; Next #MachineLearning problem: what to do with 80% accurate algorithm? ;Learning to Code #NeuralNetworks #MachineLearning Tutorial;
Listen to some of the greatest data scientists to speak about their use of KNIME software to solve complex data problems in life sciences, manufacturing, marketing, retail sales, and many other areas. Register and save with code KDNUGGETS_KNIME_SUMMIT2016.
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.
Two upcoming webinars show how to use the powerful GraphDB from Ontotext: Powerful Searches and Data Visualization in Graph Database (Jan 28) and Transforming your Graph Analytics with GraphDB (Feb 4). Check also GraphDB free version.
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.
Creative machines have been making their influence felt for some time, but an upcoming stage production challenges preconceived notions of what art is.
20 Questions to Detect Fake Data Scientists; Google Deep Learning TensorFlow Disappoints; Yahoo Releases the Largest-ever Machine Learning Dataset for Researchers; Research Leaders on Data Mining, Data Science and Big Data.
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.
Consumer Analytics is still the leading application area for analytics & data mining (although losing its share), followed by Finance, and Banking. Highest growth is in Games, Entertainment/Music, and Social Good/Non-profit applications. 3-year comparison shows surprising stability.
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.
R vs Python for Data Science: The Winner is ...; 60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning; Top 20 Python Machine Learning Open Source Projects; 50+ Data Science and Machine Learning Cheat Sheets.
A top Big Data influencer lists, outlines, and summarizes his favorite blog posts of 2015. Gain some additional insight into various data science topics with some of these great entries.
AirBnB has brought together unmatched supply and demand and allowed for market-driven evaluation of assets. We are sharing lessons learnt from them for digital startups and big data organisations.
Currently, only global corporations like Google or Facebook can maintain a vast knowledge graph about the world. Little companies which rely on knowing world context need to unite to create a Public Knowledge Graph, or they will fall further behind the big guys.
Data Scientist is the best job in America, according to Glassdoor, with median base salary $117K, and high career prospects. Analytics Manager ranks n. 11. However, the number of available positions is much less than predicted shortage of 140-190,000.
Menlo technologies compiled a list of Data Analytics thought leaders and companies they follow on Twitter. Spend some time on their informative and as entertaining Twitter Feeds, web and blogs.
A discussion of why deep neural networks are captivating imaginations everywhere, specifically their abilities to model many natural functions well and to learn surprisingly useful representations.
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.
Working professionals from anywhere in the world can apply the skills and strategies they learn in class to their current jobs right away and to graduate in as little as 18 months.
Quora is launching a new format for interacting with domain experts and sharing knowledge, and its first topic is Machine Learning. Yoshua Bengio is the first expert, and he is accepting questions now.
FlyElephant wishes you a Happy New Year. We started this year with an expansion of our platform, new webinars, and the formation of a community around the platform.
Research and development of a single drug can take 10 years and cost billions. Learn about applications and business value of text mining in the life sciences through a series of real world examples.
At PAW for Business in San Francisco, April 3-7, uplift modeling will be covered in three sessions and one workshop - plus, check out an on-topic article by PAW founder Eric Siegel.
Are you interested in massive amounts of data for research? Yahoo has just released the largest-ever machine learning dataset to the research community.
Research Leaders in Data Science and Big Data reflect on the most important research advances in 2015 and the key trends expected to dominate throughout 2016.
Camelyon16 challenge in conjugation with IEEE International Symposium on Biomedical Imaging is here! You have to design and develop a system which can detect and localize metastatic regions in whole slide microscopic images.
A small collection of introductory scikit-learn and Python stack tutorials for those with an existing understanding of machine learning looking to jump right into using a new set of tools.
The Apache Hadoop, Predictive Analytics and Data Science Innovation Summits will be in San Diego, Feb 18-19. Get 20% off all two-day passes with code KD20.
20 Questions to Detect Fake Data Scientists; TensorFlow Disappoints - Google Deep Learning falls shallow; Machine Intelligence vs Machine Learning vs Deep Learning vs AI; What To Expect from Deep Learning in 2016.
December's ICCV 2015 conference in Santiago, Chile has come and gone, but that's no reason not to know about its top papers. Get an update on which computer vision papers and researchers won awards.
Learn Azure ML Studio through this brief hands-on tutorial. This step-by-step guide will help you get a quick-start and grasp the basics of this Predictive Modeling tool.
Apache Spark went through a lot in 2015. Get a solid review from Databricks, the steward organization founded by the creators of Spark and the drivers of its innovation.
Boost your career by learning how to leverage technology to maximize business value with this certificate - only 3 months to complete. Info Session, Jan 21, Wilmington, DE.
A discussion of three major approaches to building smart machines - Classic AI, Simple Neural Networks, and Biological Neural Networks - and examples as to how each approach might address the same problem.
How solid is your strategy for managing data from the Internet of Things (IoT)? A leading analyst firm reveals the smart, new approach - get the white paper.
Twitter is great place to learn about what data scientists, business intelligence practitioners, and analytics experts are thinking. Here are 11 of InformationWeek favorites.
Global warming has been argued in depths and breadths and arguments for and against are championed too.Here, with a simple data science we obtained a simple (and increasingly accepted) conclusion: the global warming is real.
We have tracked the activity on Twitter around the release date to gain insight into the reactions of people and their feelings about the latest episode of the most famous movie franchise in history.
The top 10 deep learning projects on Github include a number of libraries, frameworks, and education resources. Have a look at the tools others are using, and the resources they are learning from.
Instead of proceeding with a mediocre analysis, join us for this 2-part webinar series. We will show you how modern algorithms can take your regression model to the next level and expertly handle your modeling woes
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 Orlando, February 18-26.
Get the Revised and Updated Edition of Eric Siegel’s acclaimed Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Free audiobook with order,
Wikipedia data mining may reveal changes over time in the human perception of the world, and may also serve as an independent reliable quantitative method of investigation of historical events.
An overview of attention mechanisms and memory in deep neural networks and why they work, including some specific applications in natural language processing and beyond.
Building, tuning, sharing, deploying, and scaling predictive models is challenging, and rarely covered in statistics class. Learn how to make data science work in the real world in this webinar.
#NIPS2015 #DeepLearning Tutorial by top researchers Bengio, LeCun, Hinton; Understanding Rare Events and streak patterns; Most Influential Data Scientists on Twitter and Quora; 12 Tips for Data-Driven Research.
The industry is in the midst of the biggest change in enterprise computing in decades. Schroeder sees an acceleration in big data deployments, and has crystallized his view of market trends into these five major predictions for 2016.
Eric will be delivering his keynote as part of the PAW Business San Francisco agenda on Weird Science: How to Know Your Predictive Discovery Is Not BS. Save with code KDN150.
Predictions from some of the top names in deep learning, including Ilya Sutskever and Andrej Karpathy, about what to expect in the field over the next 5 years.
There are many deep learning resources freely available online, but it can be confusing knowing where to begin. Go from vague understanding of deep neural networks to knowledgeable practitioner in 7 steps!
20 Questions to Detect Fake Data Scientists; 5 More arXiv Deep Learning Papers, Explained; TensorFlow is Terrific - A Sober Take on Deep Learning; 55 upcoming January - September Meetings.
A top statistics professor and statistical researcher reflects on a number of awesome accomplishments by individuals in, and related to, the fields of statistics and data science, with a focus on the world of academia but with resonance far beyond.
We often look back at the past year and an overall history of rare events, and try to then extrapolate future odds of the same rare event, based on that. We illustrate here, that rare past events have no usefulness in understanding the rarity of the same events in the future!
New year has just begun and for the year ahead is a good opportunity to consider the passage of time, how much is left to each of us. We’re presenting some of the best visualizations of lifespans and life expectancy.
A well-built resume is key to get through the first door – in the process of getting hired as a Data Scientist. Learn more, about how to present yourself as a true DS and which pitfalls to avoid.
Through real-world case studies, this technical primer will help you: find best practices to interactively explore the patterns in your data, build useful statistical models, and visually interact with these models.
New, fresh Predictive Analytics World events feature prominent predictive analytics experts to learn from. Join us this spring in San Francisco as part of the leading, world-renowned events in predictive analytics. Use code KDN150 to save on top of early bird rates.
Through lectures and hands-on sessions, the summer school will cover the state of the art in using deep learning methods within our two disciplines, Computer Vision and Natural Language Processing. The school is open to anyone interested, free of charge. Researchers resident in COST countries are eligible to apply for financial support.
Jake Porway is a machine learning and technology enthusiast, and founder of DataKind nonprofit which helps organizations use the power of data science in the service of humanity. He will do Reddit AMA on Jan 13, 2016.
There is an increasing volume of deep learning research, articles, blog posts, and news constantly emerging. Our Deep Learning Reading List aims to make this information easier to digest.
Top 10 Machine Learning Projects on Github; 50 Useful Machine Learning, Prediction APIs; Free Data Science Curriculum; The Star Wars social networks - who is the central character?
AI, machine learning, speech recognition and NLP technologies are converging to allow creation of Intelligent Virtual Assistants, explored in the first ever Virtual Assistant Summit, Jan 28-29, in SF. Use code KDNUGGETS to save 20% off.
We witness an explosion of Big Data in finance, biology, medicine, marketing, and other fields. This book describes the important statistical ideas for learning from large and sparse data in a common conceptual framework.
While “quick wins” are desirable, getting them in a predictive project can be difficult. We review 2 major obstacles to quick wins in predictive analytics projects.
During his recent AMA, machine learning star Nando de Freitas answers a host of questions on a number of topics, including Bayesian methods in deep learning, harnessing AI for the good of humanity, and what the future holds for machine learning.
Strata + Hadoop World is the leading event on how big data and ubiquitous, real-time computing is shaping the course of business and society. Get KDnuggets discount to Strata + Hadoop World San Jose.
Learn Hadoop and Spark, two key Big Data technologies, with an evening course in New York City, starting Jan 19. Special KDnuggets discount with code 09P8W01CUP7B.
There are many ways to compute the best solution to a problem, but not all of them can be put into production. The Portable Format for Analytics (PFA) provides a way of formalizing and moving models.
NASA Juno mission will arrive at Jupiter. The Summer Olympics will take place in Rio de Janeiro. The US will have a presidential election. And prescriptive analytics will take center stage as the ultimate destination on the analytics journey.
TensorFlow is Terrific - A Sober Take on Google Deep Learning; Data Science in Python 100 Interview Questions and Answers; 20 Questions to Detect Fake Data Scientists; There are only 5 questions #MachineLearning can answer.
The terrorism threat advisory system was designed to give the public prior warning to when terrorist plots are about to unfold. However, the analysis shows that this system is not more helpful than monkey throwing a dart.
We look at projects from Chicago University Data Science for Social Good (DSSG) Program which help make the world a better place, and in particular at measure to help predict obesity.
December on /r/MachineLearning: Is TensorFlow Google's "secret sauce?", AI leaders unite, an extensive curated list of machine learning resources grows, Google vs. Facebook, and Deep Q Pong.
The Art of Data Science: The Skills You Need and How to Get Them; 20 Questions to Detect Fake Data Scientists; TensorFlow is Terrific - A Sober Take on Deep Learning Acceleration; What questions can data science answer?
Coming soon: EGC 2016, RapidMiner Wisdom, #BALasVegas, #PASanDiego, WSDM 2016, KNIME Summit, Strata + Hadoop San Jose, PAW San Francisco, and many more.
Hiring Data Scientists is no easy job, particularly when there are plenty of fake posers. Here is a handy list of questions to help separate the wheat from the chaff.
There are only five questions machine learning can answer: Is this A or B? Is this weird? How much/how many? How is it organized? What should I do next? We examine these questions in detail and what it implies for data science.
20 Questions to Detect Fake Data Scientists
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