- Does Machine Learning allow opposites to attract? - Feb 11, 2016.
Most online dating sites use 'Netflix-style' recommendations which match people based on their shared interests and likes. What about those matches that work so well because people are so different - here is my example.
- 21 Must-Know Data Science Interview Questions and Answers - Feb 11, 2016.
KDnuggets Editors bring you the answers to 20 Questions to Detect Fake Data Scientists, including what is regularization, Data Scientists we admire, model validation, and more.
- Auto-Scaling scikit-learn with Spark - Feb 11, 2016.
Databricks gives us an overview of the spark-sklearn library, which automatically and seamlessly distributes model tuning on a Spark cluster, without impacting workflow.
- Big Data Innovation Summit, San Francisco, Apr 21-22, 2016 – Early bird, KDnuggets discount - Feb 11, 2016.
Hear groundbreaking presentations on Big Data Analytics, Retail, Finance, Data-Driven Product Innovation, and Healthcare. Early Bird rates end Feb 19 - get extra 10% off with code KD10.
- 9 Must-Have Datasets for Investigating Recommender Systems - Feb 11, 2016.
Gain some insight into a variety of useful datasets for recommender systems, including data descriptions, appropriate uses, and some practical comparison.
- Geneva Trading: Data Scientist - Feb 10, 2016.
Seeking an experienced Data Scientist to focus on automated trading strategy development on a variety of horizons.
- Data Scientist Valentine Day Card from Anaconda - Feb 10, 2016.
Data Scientist Valentine Day Card: I VISUALIZE US TOGETHER; I HAVE NO OPEN ISSUES WITH YOU; while TRUE: print "I love you". Download and send to significant other!
- Big Data 2016: Top Influencers and Brands - Feb 10, 2016.
Onalytica gives us a new list of the top 100 Big Data influencers and brands, and provides some insight into both the relationships between influencers and their selection methodology.
- 4 Reasons Why We Need More Women In Big Data - Feb 10, 2016.
Gender imbalance in the workforce has been highlighted alarmingly during the recent years. Here, we are providing you a couple of reasons, including the inherent advantage and lack of stereotype for role to hire women data scientists.
- HackSummit Virtual Event, Feb 22-24 - Feb 10, 2016.
hack.summit() is a virtual conference, uniting renowned programming language creators, open-source contributors and other top experts. Free registration to all KDnuggets readers - use the code KDNUGGETS.
- KDnuggets™ News 16:n05, Feb 10: Deep Learning is not Enough; Apache Spark: RDD, DataFrame or Dataset? - Feb 10, 2016.
Deep Learning is not Enough; Apache Spark: RDD, DataFrame or Dataset?; New Tools Predict Markets with 99.9% certainty; Avoid These Common Data Visualization Mistakes;
- ADMA Data Day, Apr 27 Sydney, Apr 29 Melbourne, Australia - Feb 9, 2016.
ADMA Data Day brings together international and local leaders in the data and marketing spaces - the perfect event for those analysts that advise senior decision makers or work within a marketing department.
- Change in Perspective with Process Mining - Feb 9, 2016.
Process mining is focused on the analysis of processes, and is an excellent tool in particular for the exploratory analysis of process-related data. Understand how effectively use it as an exploratory analysis tool, which can rapidly and flexibly take different perspectives on your processes.
- Umea University: PhD and Postdoctoral positions, Federated Database System/Data Mining - Feb 9, 2016.
Join our efforts to academic federated database construction and cross-database analysis for research purposes of data from distributed databases. Develop data analysis methods with focus of data integration and privacy preservation.
- Deep Learning is not Enough - Feb 9, 2016.
Deep Learning has real successes, but is not enough to reach artificial intelligence, according to latest KDnuggets Poll. For more complex problems, should pure neural-net approaches be combined with symbolic, knowledge-based methods?
- Top 10 TED Talks for the Data Scientists - Feb 9, 2016.
TEDTalks have been a great platform for sharing ideas and inspirations. Here, we have sifted ten interesting talks for the data scientist from statistics, social media and economics domains.
- Financial service apps featured at Predictive Analytics World, San Francisco - Feb 9, 2016.
Predictive Analytics World for Business in San Francisco, April 3-7, features a full 2-day Financial Services track, featuring experts from Chase, Capital One, Experian, Microsoft, Paypal, and other leading companies. Sign up with code KDN150 & save up to $350.
- New Jersey City University: Tenure-track position in Business Data Analytics / Data Science - Feb 8, 2016.
Candidates with an interest and expertise in Business Analytics, Data Science and Decision Analytics are preferred. All areas of finance and real estate will be considered.
- Top KDnuggets tweets, Feb 1-7: On Facebook people are separated by only 3.5 degrees; Tribute to Marvin Minsky, co-founder of AI - Feb 8, 2016.
The Most Funded #Tech #Startup In every US state; Tableau, Qlik, Microsoft leaders in Gartner 2016 BI, #Analytics Platforms; Tribute to Marvin Minsky 1927-2016, co-founder of Artificial Intelligence; No more #6degrees! On Facebook people are separated by only 3.5 degrees.
- Aetna: Senior Informatics Scientist in Data Science - Feb 8, 2016.
Help provide critical healthcare insights using big data analytics on billions of records, with our Hadoop cluster using Hive, Pig, Scala, Spark, Python, R, H20, etc.
- New Tools Predict Markets with 99.9% certainty - Feb 8, 2016.
Predicting financial markets is a relatively new field of of research, it is cross-disciplinary, it is difficult and requires some insight into trading, computational linguistics, behavioral finance, pattern recognition, and learning models.
- Avoid These Common Data Visualization Mistakes - Feb 8, 2016.
Data Visualization is a handy tool which can lead to interesting discoveries about the data, which otherwise wouldn’t have been possible. But, there are common mistakes which could produce the misdirecting results. Learn what are they and how you can avoid them.
- Top stories for Jan 31 – Feb 6: Data scientists keep forgetting the one rule; Apache Spark: RDD, DataFrame or Dataset? - Feb 7, 2016.
20 Q to Detect Fake Data Scientists; TensorFlow Disappoints - Google Deep Learning falls shallow; Data scientists keep forgetting the one rule; Apache Spark: RDD, DataFrame or Dataset?
- NewsWhip (Dublin): Java Machine Learning Engineer - Feb 5, 2016.
Work on developing new algorithms and approaches that will harness our technology and surface the most relevant stories and events to our clients every day.
- Top January stories: 20 Questions to Detect Fake Data Scientists, Machine Intelligence vs. Machine Learning vs. Deep Learning vs. AI - Feb 5, 2016.
20 Questions to Detect Fake Data Scientists; What Is Machine Intelligence Vs. Machine Learning Vs. Deep Learning Vs. Artificial Intelligence (AI)? 7 Common Data Science Mistakes and How to Avoid Them; What questions can data science answer?
- The WebMiner Filter – Beta - Feb 5, 2016.
Filtering through companies, blogs, shops or social media websites we can make a better use of our search results and therefore add value to our internet searches. TheWebMiner is a company that offers enterprise web crawling, web scraping and many other data processing solutions.
- TMA Predictive Analytics Data Mining Training, [Orlando, Feb 18-26] - Feb 5, 2016.
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.
- Webinar: Visualizing 1 Billion Points Of Data, Feb 9 - Feb 5, 2016.
As data grows to include millions and billions of points, traditional visualization techniques break down. Join Continuum Analytics on Feb 9 for a webinar on Big Data visualization with the new datashader library.
- American Family Insurance: Data Science Manager - Feb 4, 2016.
Providing strategic direction and expertise to understand key business questions that can be addressed using data; Leading, designing, developing and fielding data driven solutions.
- Wharton: Successful Applications of Customer Analytics, April 29, Philadelphia - Feb 4, 2016.
Now in its third year, the conference continues to gain momentum with industry practitioners. This year will feature a great line-up of expert speakers, new format and two keynotes.
- 62 upcoming February – October Meetings in Analytics, Big Data, Data Mining, Data Science - Feb 4, 2016.
Coming soon: #PASanDiego, KNIME Summit Berlin, WSDM 2016, JMP Discovery Summit, Big Data Paris, Strata + Hadoop San Jose, PAW San Francisco, and many more.
- Data Warehouse Architecture 2016, March 21-23, Washington, DC - Feb 4, 2016.
Data Warehouse Architecture 2016 offers you the first completely vendor-neutral forum to share best practice on the crucial day-to-day issues such as design, project management and funding, ETL, integration, data quality, Hadoop and upgrades.
- RapidMiner Webinar: Extracting Insight from Superbowl Sentiments, Feb 16 - Feb 4, 2016.
The webinar explores the power of social content by analyzing data captured from tweets about Super Bowl 50 ads to determine sentiments and predict potential trends in brand adoption.
- Money does buy votes, unless you are Jeb Bush - Feb 3, 2016.
Can money buy votes? In Iowa republican caucuses Jeb Bush spent about $2,700/per vote, with little to show. However, without Jeb, there is a strong correlation between money and votes, with $210/vote on average. We also find that spending more time in Iowa does not help.
- Dow Chemical: Advanced Analytics Data Scientist - Feb 3, 2016.
Help build a specific mathematical models to address a particular problem creating a value opportunity for Dow. Lead projects effectively and independently.
- On Why Sequels Are Bad and Red Light Cameras Aren’t As Effective - Feb 3, 2016.
Regression to the mean is a statistical phenomenon whereby extreme observations will tend to decrease (regress) towards the mean on subsequent readings. Regression to the mean is essentially a result of selection bias, learn more about it.
- Apache Spark: RDD, DataFrame or Dataset? - Feb 3, 2016.
There are now 3 Apache Spark APIs. Here’s how to choose the right one.
- Strata Hadoop World London 2016 - Feb 3, 2016.
Strata + Hadoop World is the leading event on how big data and ubiquitous, real-time computing is shaping the course of business and society. Make plans to join Strata + Hadoop World in London 31 May-3 June 2016. Save 20% with code PCKDNG.
- SanDisk: Senior Big Data Engineer/Hadoop Developer - Feb 3, 2016.
Planning and designing next-generation Big Data System architectures, managing the development and deployment of Hadoop applications.
- KDnuggets™ News 16:n04, Feb 3: Is Deep Learning Overhyped? Businesses Will Need 1M Data Scientists - Feb 3, 2016.
New Poll: Deep Learning - does reality match the hype?; Is Deep Learning Overhyped?; Businesses Will Need One Million Data Scientists by 2018; KDnuggets New Responsive, Mobile-Friendly Design.
- Webinar: The Role of Text Mining at Boehringer Ingelheim Pharmaceuticals, Feb 23 - Feb 2, 2016.
Learn how text mining enables life science researchers to quickly analyze massive amounts of literature, conference abstracts, patents and clinical data to help inform and guide R&D.
- Four Major Predictions for Predictive Analytics and Big Data in 2016 - Feb 2, 2016.
2016 will usher in some unmissable results of the Information Age’s latest contribution, the more effective execution of major operations across sectors with predictive analytics.
- Data scientists keep forgetting the one rule - Feb 2, 2016.
“Correlation does not imply causation”. Yet data scientists often confuse the two, succumbing to the temptation to over-interpret. And that can lead us to make some really bad decisions from data.
- Peering into the Black Box and Explainability - Feb 2, 2016.
In many domains, where data science can be a game changer, and the biggest hurdle is not collecting data or building the models, it is Understanding what they mean.
- The Top A.I. Breakthroughs of 2015 - Feb 2, 2016.
Learn about the biggest developments of 2015 in the field of Artificial Intelligence.
- Microsoft Deep Learning Brings Innovative Features – CNTK Shows Promise - Feb 2, 2016.
Microsoft releases CNTK, a deep learning tool kit which shows promise. While a few innovative features set it apart from its competitors, a major drawback may hurt its adoption.
- Simplilearn Special: 30% off on Big Data and Analytics courses - Feb 2, 2016.
Get access to Simplilearn R, Big Data, Hadoop and other Data Science-related courses at unbeatable prices with code GetAhead. This offer good till 7 Feb, 2016.
- KDnuggets New Responsive, Mobile-Friendly Design - Feb 2, 2016.
Check KDnuggets new responsive, mobile-friendly design and different new features, including more ways to access our rich content.
- Top 10 tweets Jan 25-31: DataViz: how a decision tree works; Nice and Brief Tutorial on Python - Feb 1, 2016.
DataViz - how a decision tree makes classifications; Very Nice and Brief Tutorial on #Python #DataScience #DataViz; Per Einstein, time flows slower in Meetings than in empty space #hum; Top 10 Skills for #DataScience professionals.
- PAW: Early bird ends Feb. 5th for 4 converging analytics events - Feb 1, 2016.
The powerhouse gathering of data scientists and analysts in North America this spring is San Francisco, Apr 3-7, with Predictive Analytics World for Business, Workforce, the eMetrics Summit, and PA Times Executive Breakfast. Early bird ends Feb 5. Use KDN150 for extra savings.
- Cartoon: Deeper Deep Learning - Feb 1, 2016.
New KDnuggets Cartoon looks at a creative new way of achieving even better results and breaking through Machine Learning barriers with even "deeper" Deep Learning approach.
- Machine Learning Course for R&D Specialists, 4-8 April, Delft, The Netherlands - Feb 1, 2016.
Do you want to go beyond theory and learn how to create working Machine Learning solutions? This 5-day course provides you with practical step-by-step methodology.
- AI Supercomputers: Microsoft Oxford, IBM Watson, Google DeepMind, Baidu Minwa - Feb 1, 2016.
In the world of AI, this is the equivalent of the US and USSR competing to put their guy on the moon first. Here is a profile of some of the giants locked into the AI space race.
- Google’s Great Gains in the Grand Game of Go - Feb 1, 2016.
The game of Go has long stumped AI researchers, and, as such, solving it was thought to be years off. That is, until Google solved it earlier this week. Or did it?
- Top /r/MachineLearning Posts, January: Google Masters Go, Deep Learning Laughs, OpenAI AMA - Feb 1, 2016.
In January on /r/MachineLearning: Go gets mastered, deep learning laughs, an OpenAI team AMA, convolutional neural nets colorize black and white photos, and the AI community loses a leader.
- Top stories for Jan 24-30: 7 Common Data Science Mistakes; Businesses Will Need 1M Data Scientists by 2018 - Jan 31, 2016.
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.
- FirstFuel Software: Data Scientists, Senior/Junior positions - Jan 30, 2016.
Developing and deploying the core statistical/machine learning algorithms with the Research group; coding these algorithms in production quality software with the engineering team.
- Data ScienceTech Institute, online (off-campus) education, starting March 2016 - Jan 30, 2016.
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 in Business Analytics, Data Science, Machine Learning in January - Jan 30, 2016.
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.
- How banks can beat new finance boys with data - Jan 29, 2016.
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.
- Details on First Data Science Job Salary - Jan 29, 2016.
A person new to the Data Science field details their salary and the negotiation process.
- New Poll: Deep Learning – does reality match the hype? - Jan 29, 2016.
New KDnuggets Poll looks at the very hot field of Deep Learning and asks: does reality match the hype? Please vote!
- Python Data Science with Pandas vs Spark DataFrame: Key Differences - Jan 29, 2016.
A post describing the key differences between Pandas and Spark's DataFrame format, including specifics on important regular processing features, with code samples.
- Is Deep Learning Overhyped? - Jan 29, 2016.
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?
- Explore Data Science – self-paced online learning - Jan 28, 2016.
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.
- Geisinger Health System: Senior Data Scientist - Jan 28, 2016.
Seeking a researcher with a strong background in applied mathematics or computer science, and active interest in multidisciplinary studies in social/life sciences.
- U. Delaware Certificate in Analytics: Optimizing Big Data - Jan 28, 2016.
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.
- Deep Learning with Spark and TensorFlow - Jan 28, 2016.
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.
- Businesses Will Need One Million Data Scientists by 2018 - Jan 28, 2016.
Deepening shortage of Data Science talent and cybersecurity challenges are trends shaping business in 2016.
- How to Check Hypotheses with Bootstrap and Apache Spark - Jan 28, 2016.
Learn how to leverage bootstrap sampling to test hypotheses, and how to implement in Apache Spark and Scala with a complete code example.
- Useful Data Science: Feature Hashing - Jan 28, 2016.
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.
- Implementing Your Own k-Nearest Neighbour Algorithm Using Python - Jan 27, 2016.
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.
- How to Tackle a Lottery with Mathematics - Jan 27, 2016.
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.
- Strategic Business Analytics – n5 Most Coveted Coursera Certificate in 2015 - Jan 27, 2016.
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.
- KDnuggets™ News 16:n03, Jan 27: Secret to winning Kaggle; Better Dataviz; Where Analytics is applied - Jan 27, 2016.
Learning to Code Neural Networks; The secrets to winning Kaggle; 3 Simple Resolutions to Design Better DataViz; Data Scientist - best job in America.
- Jan 27 Webinar: 3 Ways to Improve your Regression, Part 2 - Jan 26, 2016.
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!
- Google Launches Deep Learning with TensorFlow MOOC - Jan 26, 2016.
Google and Udacity have partnered for a new self-paced course on deep learning and TensorFlow, starting immediately.
- Webinar: Data Mining: Failure to Launch [Feb 9] - Jan 26, 2016.
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 Data Science and Evolution of BI - Jan 26, 2016.
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.
- 7 Common Data Science Mistakes and How to Avoid Them - Jan 26, 2016.
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.