- Some Data Scientist New Year Resolutions for 2017 - Jan 17, 2017.
Do you make any new year resolutions? Hit the gym more often? Lose that last 10 pounds? While personal resolutions often get a bad rap, setting professional goals at the start of the new year is not necessarily a bad idea. Check out one data scientist's new year resolutions for 2017.
- 90 Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning (updated) - Jan 17, 2017.
Stay up-to-date in the data science with active blogs. This is a list of 90 recently active blogs on Big Data, Data Science, Data Mining, Machine Learning, and Artificial intelligence.
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- Big Data and the Internet of Things don’t make business smarter, Analytics and Data Science do - Jan 12, 2017.
Big Data does not convert data into actionable information. Big Data does not create value. But Data Science does, and it does not have to be complex or expensive, or even big.
- The Most Popular Language For Machine Learning and Data Science Is … - Jan 11, 2017.
When it comes to choosing programming language for Data Analytics projects or job prospects, people have different opinions depending on their career backgrounds and domains they worked in. Here is the analysis of data from indeed.com with respect to choice of programming language for machine learning and data science.
- A Non-comprehensive List of Awesome Things Other People Did in 2016 - Jan 10, 2017.
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.
- AI, Data Science, Machine Learning: Main Developments in 2016, Key Trends in 2017 - Jan 10, 2017.
2017 is here. Check out an encore installation in our "Main Developments in 2016 and Key Trends in 2017" series, where experts weigh in with their opinions.
- A Tasty approach to data science - Jan 7, 2017.
Data scientists at Foodpairing help brands cut down on the fuzzy front end of product development. The so-called Consumer Flavor Intelligence combines internet data and food science to create timely flavor line extensions.
- Syracuse University, School of Information Studies: Open Rank Faculty Position Data Science - Jan 6, 2017.
Join renowned and interdisciplinary faculty of Syracuse U. School of Information Studies (The iSchool) in Data science, Cloud management, and or Cloud/distributed computing.
- Sound Data Science: Avoiding the Most Pernicious Prediction Pitfall - Jan 5, 2017.
Data science and predictive analytics can provide huge value, but they can mislead and backfire if not used with fail-safe measures. The author gives examples of such problems and provides guidelines to avoid them.
- Supercharge Your Data Science Team with AnacondaCON Team Discount, till Jan 16 - Jan 3, 2017.
AnacondaCON '17 will help you conquer your biggest data science challenges. Learn from industry experts sharing what #OpenDataScienceMeans and their best practices. Get 2 for 1 ticket price thru Jan 16, 2017.
- Apple: Data Science Engineer - Dec 21, 2016.
Changing the world is all in a day's work at Apple. If you love innovation, here's your chance to make a career of it. You'll work hard. But the job comes with more than a few perks.
- Data Science Basics: Power Laws and Distributions - Dec 21, 2016.
Power laws and other relationships between observable phenomena may not seem like they are of any interest to data science, at least not to newcomers to the field, but this post provides an overview and suggests how they may be.
- Supercharge Your Data Science Team, Dec 21 Webinar - Dec 20, 2016.
On December 21st, Continuum Analytics CTO Peter Wang will share how you can supercharge your Data Science team by simplifying the building process for even the most complicated dashboards and display streaming data in real time.
- 3rd Annual Global Data Science Conference, Santa Clara, March 27-29, 2017 - Dec 19, 2016.
Get ready for one of the leading and vendor agnostic Global Big Data Conference, happening at Santa Clara, CA on March 27-29 2017. Register now with promo code: KDNUGGETS and save upto $200.
- Data Science & Ancestry - Dec 17, 2016.
Ancestry is curious topic for many people to find out their origin and history. Today, data science is used to help these people to dig into their family history and build the family trees.
- The 5 Basic Types of Data Science Interview Questions - Dec 16, 2016.
Data science interviews are notoriously complex, but most of what they throw at you will fall into one of these categories.
- 50+ Data Science, Machine Learning Cheat Sheets, updated - Dec 14, 2016.
Gear up to speed and have concepts and commands handy in Data Science, Data Mining, and Machine learning algorithms with these cheat sheets covering R, Python, Django, MySQL, SQL, Hadoop, Apache Spark, Matlab, and Java.
- Data Science Basics: What Types of Patterns Can Be Mined From Data? - Dec 14, 2016.
Why do we mine data? This post is an overview of the types of patterns that can be gleaned from data mining, and some real world examples of said patterns.
- KDnuggets™ News 16:n44, Dec 14: Key Data Science 2016 Events, 2017 Trends; Where Data Science was applied; Bayesian Basics - Dec 14, 2016.
Data Science, Predictive Analytics Main Developments in 2016, Key Trends in 2017; Where Analytics, Data Mining, Data Science were applied in 2016; Bayesian Basics, Explained; Data Science Trends To Look Out For In 2017; Artificial Neural Networks (ANN) Introduction
- Data Science, Predictive Analytics Main Developments in 2016 and Key Trends for 2017 - Dec 13, 2016.
Key themes included the polling failures in 2016 US Elections, Deep Learning, IoT, greater focus on value and ROI, and increasing adoption of predictive analytics by the "masses" of industry.
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- Springboard launches data science bootcamp with a job guarantee - Dec 12, 2016.
Springboard Data Science Career Track is the first online data science bootcamp that offers a job guarantee to its graduates. Springboard tracked 50 graduates and saw that all got a job within 6 months, with a median increase of $18,000 in first-year salary.
- Data Science and Big Data: Definitions and Common Myths - Dec 12, 2016.
A well-set data strategy is becoming fundamental to every business, regardless the actual size of the datasets used. However, in order to establish a data framework that works, there are a few misconceptions that need to be clarified.
- Data Science Trends To Look Out For In 2017 - Dec 8, 2016.
Machine Learning is here to stay, with more firms following Google and Facebook in the race to attract the best machine learning experts and Data Scientists. We also see a merger of IoT and Data Science. Read on for more trends.
- KDnuggets™ News 16:n43, Dec 7: Where did you use Data Science? The hard thing about Deep Learning; Big Data Main Events in 2016, Key Trends for 2017 - Dec 7, 2016.
Where did you apply Analytics, Data Science in 2016? Big Data Main Developments in 2016 and Key Trends in 2017; The Data Science Delusion; The hard thing about deep learning.
- Kobielus Predictions for Data Science in 2017 - Dec 5, 2016.
IBM Data Evangelist James Kobielus predictions for 2017, including key role of data scientists in survival of their companies. Join industry experts for a live #MakeDataSimple Crowdchat on Thursday December 8 at 1:00pm EST.
- Academic/Research positions in Business Analytics, Data Science, Machine Learning in November 2016 - Dec 2, 2016.
Faculty/Postdoc positions in Data Science/Machine Learning at DePaul, UCSB, Virginia Tech, Barcelona U, Aarhus U, Georgia State U, U. of Innsbruck, Drexel, CMU, Oregon State U, Iowa State, and more.
- Upcoming Meetings in Analytics, Big Data, Data Mining, Data Science: December 2016 and Beyond - Dec 2, 2016.
Coming soon: IEEE Big Data, Big Data/Business Analytics Innovation Summits Las Vegas, AnacondaCON Austin, WSDM 2017 Cambridge, TDWI Las Vegas, and more.
- Interviews with Data Scientists: Claudia Perlich - Dec 2, 2016.
In this wide-ranging interview, Roberto Zicari talks to a leading Data Scientist Claudia Perlich about what they must know about Machine Learning and evaluation, domain knowledge, data blending, and more.
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- Data Science Deployments With Docker - Dec 1, 2016.
With the recent release of NVIDIA’s nvidia-docker tool, accessing GPUs from within Docker is a breeze. In this tutorial we’ll walk you through setting up nvidia-docker so you too can deploy machine learning models with ease.
- Top Reasons Why Big Data, Data Science, Analytics Initiatives Fail - Dec 1, 2016.
We examine the main reasons for failure in Big Data, Data Science, and Analytics projects which include lack of clear mandate, resistance to change, and not asking the right questions, and what can be done to address these problems.
- The Data Science Delusion - Nov 30, 2016.
Gleanings from observed technical misunderstandings between business leaders and data scientists (and among data scientists themselves) so dramatic that one could start wondering whether there is something wrong with data science as it is being practiced.
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- Industries / Fields where you applied Analytics, Data Mining, Data Science in 2016? - Nov 29, 2016.
New KDnuggets Poll is asking: What are the Industries/Fields where you applied Analytics, Data Science, Data Mining in 2016? Please vote and we will publish the analysis and trends.
- 10 Tips to Improve your Data Science Interview - Nov 29, 2016.
Interviewing is a skill. Here are 10 tips and resources to improve your Data Science interviews.
- RCloud – DevOps for Data Science - Nov 28, 2016.
After almost two decades of software development, term – DevOps was coined and officially given importance to collaboration between development and deployment of software systems. In this early stage of Data Science field, use of standardized and empirical practises like DevOps will definitely speed up its evolution.
- Why We Need Data Science - Nov 26, 2016.
A gentle reminder as to why we need Data Science, reasons for which even you may have been guilty of offending at some point. A basic topic, to be sure, making it all the more important.
- Top 10 Facebook Groups for Big Data, Data Science, and Machine Learning - Nov 23, 2016.
Social media now not only shares friendship connections or photos of “selfies” but also spreads from political media to science information. Social network members are tending to more eagerly learn about big data, data science and machine learning through groups. We review the ten largest Facebook groups in this area.
- DePaul University: Assistant Professor in Data Science - Nov 22, 2016.
Seeking an Assistant Professor in Data Science to be part of one of the fastest growing and most highly recognized data science programs in the country.
- Predictive Science vs Data Science - Nov 22, 2016.
Is Predictive Science accurately represented by the term Data Science? As a matter of fact, are any of Data Science's constituent sciences well-represented by the umbrella term? This post discusses a few of these points at a high level.
- The Experience of Being a High-Performing Data Scientist - Nov 21, 2016.
Now in open beta, IBM Data Science Experience (DSX) delivers Machine Learning, Collaboration, and Creative capabilities in an open and integrated environment for team data science, including many productivity features for next-generation data science,
- Data Avengers… Assemble! - Nov 19, 2016.
The Avengers are perfectly capable of defending the Earth from our worst enemies. But are they up to the task of taking care of our data? Read this terribly punny "opinion" piece to find out.
- Questions To Ask When Moving Machine Learning From Practice to Production - Nov 18, 2016.
An overview of applying machine learning techniques to solve problems in production. This articles covers some of the varied questions to ponder when incorporating machine learning into teams and processes.
- KDD 2016: Watch Talks by Top Data Science Researchers - Nov 17, 2016.
Watch the innovative talks and researches from top researchers in Data Science, presented at KDD 2016, San Francisco conference.
- Top KDnuggets tweets, Nov 9-15: #Trump, limits of #prediction; #TensorFlow French-to-English machine translation - Nov 16, 2016.
#Trump, limits of #prediction, and lessons for #DataScience of #polls; A #TensorFlow implementation of French-to-English machine translation using @DeepMindAI ByteNet; 18 top women in #DataScience to follow on Twitter; A complete daily plan for studying to become a #MachineLearning #Engineer
- Combining Different Methods to Create Advanced Time Series Prediction - Nov 16, 2016.
The results from combining methods for time series prediction have been quite promising. However, the degree of error for long-term predictions is still quite high. Sounds like a challenge, so some new experiments are forthcoming!
- Data Science and Big Data, Explained - Nov 14, 2016.
This article is meant to give the non-data scientist a solid overview of the many concepts and terms behind data science and big data. While related terms will be mentioned at a very high level, the reader is encouraged to explore the references and other resources for additional detail.
- R Systems: Director, Data Science - Nov 11, 2016.
Seeking a senior leader to grow existing and acquire new accounts across verticals, leveraging differentiated offerings combining process, statistics, data science and technology for predictive analytics initiatives.
- Top 10 Amazon Books in Data Mining, 2016 Edition - Nov 11, 2016.
Given the ongoing explosion in interest for all things Data Mining, Data Science, Analytics, Big Data, etc., we have updated our Amazon top books lists from last year. Here are the 10 most popular titles in the Data Mining category.
- Reasons Why Data Projects Fail - Nov 10, 2016.
Many companies seem to go through a pattern of hiring a data science team only for the entire team to quit or be fired around 12 months later. Why is the failure rate so high?
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- Top KDnuggets tweets, Nov 2-8: 35 #OpenSource tools for Internet of Things; An Introduction to Ensemble Learners - Nov 9, 2016.
21 Must-Know #DataScience Interview Questions with Answers; Big Data Science: Expectation vs. Reality; Big #DataScience: Expectation vs. Reality; The 10 Algorithms #MachineLearning Engineers Need to Know.
- How to Rank 10% in Your First Kaggle Competition - Nov 9, 2016.
This post presents a pathway to achieving success in Kaggle competitions as a beginner. The path generalizes beyond competitions, however. Read on for insight into succeeding while approaching any data science project.
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- Practical Data Science: Building Minimum Viable Models - Nov 8, 2016.
Data Science for startups based on data: Minimum Valuable Model, a new concept to avoid a full scale 95% accurate data science model. Want to know more about MVM? Have a look at this interesting article.
- Data Science Basics: An Introduction to Ensemble Learners - Nov 8, 2016.
New to classifiers and a bit uncertain of what ensemble learners are, or how different ones work? This post examines 3 of the most popular ensemble methods in an approach designed for newcomers.
- Agilience Top Data Mining, Data Science Authorities - Nov 4, 2016.
Agilience developed a new way to find authorities in social media across many fields of interest. We review the top authorities in Data Mining and Data science, which include KDnuggets, Kirk. D. Borne, Kaggle, Vincent Granville, and more.
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- Chief Data Officer Toolkit: Leading the Digital Business Transformation – Part 2 - Nov 4, 2016.
Read the second and final part of this overview of the CDO Toolkit, which integrates the disciplines of economics and analytics to help the CDO to ascertain the economic value of the organization’s data and data sources.
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- KDnuggets™ News 16:n39, Nov 2: Machine Learning: A Complete and Detailed Overview; Learn Data Science in 8 (Easy) Steps - Nov 2, 2016.
Machine Learning: A Complete and Detailed Overview; Cartoon: Scary Big Data; Learn Data Science in 8 (Easy) Steps; Is Your Code Good Enough to Call Yourself a Data Scientist?; Using Machine Learning to Detect Malicious URLs; Frequent Pattern Mining and the Apriori Algorithm
- Data Science 101: How to get good at R - Nov 1, 2016.
Everybody talks about R programming, how to learn, how to be good at it. But in this article, Ari Lamstein tells us his story about why and how he started with R along with how to publish, market and monetise R projects.
- Is Your Code Good Enough to Call Yourself a Data Scientist? - Oct 28, 2016.
Is your code good enough to be calling yourself a Data Scientist? Figure out how to determine the answer to this question... and gain some suggestions on ensuring that the answer is "yes!"
- Learn Data Science in 8 (Easy) Steps - Oct 27, 2016.
Want to learn data science? Check out these 8 (easy) steps to set out in the right direction!
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- Big Data Science: Expectation vs. Reality - Oct 27, 2016.
The path to success and happiness of the data science team working with big data project is not always clear from the beginning. It depends on maturity of underlying platform, their cross skills and devops process around their day-to-day operations.
- Mind of a Data Scientist – Part 2 - Oct 26, 2016.
First part of this series was about formulation of the business problem and engineering the data points. This is the last part of the series and it tells us about exploratory data analysis and feature engineering.
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- Mind of a Data Scientist – Part 1 - Oct 25, 2016.
By now, many people are aware of which technical skills are required for a Data Scientist, but do you know what mindset or thinking is required to be a good data scientist? Let’s read this two parts series by an industry expert.
- Inside Industry 4.0: What’s Driving The Fourth Industrial Revolution? - Oct 24, 2016.
In the history of mankind and past three major industrial revolutions, horizontal innovations like wheel, steam engine, electricity and integrated chips have always been the crux of it and they changed the world dramatically. Well, fourth one is on its way! Want to know what’s driving it? Have a read at this crisp article.
- Chief Data Officer Toolkit: Leading the Digital Business Transformation – Part 1 - Oct 24, 2016.
CDOs are the new hot role to rock. Read about the CDO Toolkit, which integrates the disciplines of economics and analytics to help the CDO to ascertain the economic value of the organization’s data and data sources.
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- Big Data and Data Science hands-on education in Austin – KDnuggets Offer - Oct 24, 2016.
Join us for the Industry’s Leading Data Management Conference Dec 4-9 in Austin, TX, with a special 20% discount for KDnuggets readers.
- 5 EBooks to Read Before Getting into A Machine Learning Career - Oct 21, 2016.
A carefully-curated list of 5 free ebooks to help you better understand the various aspects of what machine learning, and skills necessary for a career in the field.
- KDnuggets Top Blogger: An Interview with Ajit Jaokar, on IoT and Data Science - Oct 21, 2016.
Ajit Jaokar, a leading expert in the field, shares his views on evolution of IoT, Data Science, Smart Cities, the promise and dangers of AI, and encouraging young people.
- Jupyter Notebook Best Practices for Data Science - Oct 20, 2016.
Check out this overview of Jupyter notebook best practices as pertains to data science. Novice or expert, you may find something of use here.
- KDnuggets™ News 16:n37, Oct 19: Top Data Science Videos; 12 Interesting Big Data Careers; Deep Learning Key Terms - Oct 19, 2016.
Top 10 Data Science Videos on YouTube; Top 12 Interesting Careers to Explore in Big Data; Deep Learning Key Terms, Explained; Artificial Intelligence, Deep Learning, and Neural Networks, Explained; MLDB: The Machine Learning Database
- Top 10 Data Science Videos on Youtube - Oct 17, 2016.
Learning and the future are the key topics in the recent Youtube videos on Data Science. The main questions revolve around: “how to become a Data Scientist”, “what is a data scientist”, and “where data science is going”. But why there is so little explanation of data science to the masses?
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- Data Science + Criminal Justice - Oct 17, 2016.
The nation needs brilliant, creative minds to lead the next generation of crime forecasting. Enter the competition sponsored by National Institute of Justice to help improve policing and public safety with data science. $1.2 Million will be awarded.
- Rexer Analytics Data Science Survey Highlights - Oct 14, 2016.
Regression, Decision Trees, and Cluster analysis remain the most commonly used algorithms in the field, R continues to ascend, job satisfaction remains high, but customer understanding still needs improvement.
- K2 Data Science Bootcamp - Oct 14, 2016.
This online, part-time immersive data science bootcamp is geared to help working professional become data scientists in 24 weeks, with live lectures, one-on-one supports, group study sessions, and more. Next session starts Jan 9, 2017.
- EDISON Data Science Framework to define the Data Science Profession - Oct 14, 2016.
EDISON Data Science Framework provides conceptual, instructional and policy components required to establish the Data Science profession.
- Top 12 Interesting Careers to Explore in Big Data - Oct 12, 2016.
From data driven strategies to decision making, the true worth of Big Data has been realized, and has led to opening up of amazing career choices. Check out these 12 interesting careers to explore in Big Data.
- KDnuggets™ News 16:n36, Oct 12: Battle of the Data Science Venn Diagrams; 9 Bizarre and Surprising Insights; ROI in Big Data Analytics - Oct 12, 2016.
Battle of the Data Science Venn Diagrams; Top September Stories in KDnuggets; Open Images Dataset; Still Searching for ROI in Big Data Analytics?
- Humans & Machines Ethics Framework: Assessing Machine Learning Influence - Oct 11, 2016.
Humans & Machines Ethics Canvas’ main goal is to be a guide for critical thinking throughout the ethical decision-making process. It acts as a value system and an ethics framework to assess the influence of machine learning and software development while developing a system for individuals, teams, and organisations.
- Data Natives, Europe Data Science conference, Oct 26-28, Berlin – KDnuggets Offer - Oct 10, 2016.
Join us as we explore key areas of technology driving innovation and the next wave of billion dollar startups. Register now with the code DN2016KDN35 and get a 35% discount on tickets.
- Temple University: Data Science Faculty Positions - Oct 7, 2016.
Seeking data scientists who are developing methods and systems to collect, process, and analyze large amounts of data, as well as techniques to extract and visualize knowledge for various application domains.
- Still Searching for ROI in Big Data Analytics? You’re Not Alone! - Oct 7, 2016.
Are businesses getting the ROI they desire given the hype around big data analytics? With all the promises of big data analytics, why are more than half the companies still in the red with respect to analytics investments?
- UMBC: Data Science/Big Data Faculty Positions - Oct 6, 2016.
UMBC is seeking qualified candidates with research interests and experience in Data Science, a research area with high growth and impact in environmental sciences, health care, security, applied statistics and others.
- Battle of the Data Science Venn Diagrams - Oct 6, 2016.
First came Drew Conway's data science Venn diagram. Then came all the rest. Read this comparative overview of data science Venn diagrams for both the insight into the profession and the humor that comes along for free.
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- Top KDnuggets tweets, Sep 28-Oct 4: 7 Steps to Mastering SQL for #DataScience; Biggest Issues in #DataScience - Oct 5, 2016.
7 Steps to Mastering SQL for #DataScience; New Andrew Ng #MachineLearning #Book Under Construction, #Free Draft Chapters; Top #DataScientist Claudia Perlich on Biggest Issues in #DataScience; Awesome Public Datasets on GitHub
- University of Notre Dame: Data Science Consultant - Oct 5, 2016.
Seeking a Data Science Consultant with expertise in a quantitative social science discipline and advanced technical skills to support research activities undertaken at the University of Notre Dame.
- 9 Bizarre and Surprising Insights from Data Science - Oct 5, 2016.
The petabytes of information currently available to analysts amounts to a boundless playing field of possible truths.
- KDnuggets™ News 16:n35, Oct 5: Biggest Issues in Data Science; Data Science for IoT: 10 differences - Oct 5, 2016.
Biggest Issues in Data Science; Data Mining vs. Statistics; Data Science for Internet of Things (IoT): 10 Differences; Active Big Data, Data Science Leaders on LinkedIn.
- ODSC West 2016 Applied Data Science Conference (Nov 4-6, Santa Clara), Reveals Keys to Being A Great Data Scientist - Oct 4, 2016.
Being a good data scientist takes a lot of effort. Staying relevant, making the right connections and consistently upgrading your skill set is essential. So, what steps have you taken this year to launch your data science career to the highest level? Use code ODSC-KDN to save.
- Data Science Camp Silicon Valley, Oct 29 – almost free - Oct 3, 2016.
This SF Bay ACM annual event combines sessions, keynote, and optional tutorial - great opportunity to learn about Data Science and connect with others, and almost free.
- Top Data Scientist Claudia Perlich on Biggest Issues in Data Science - Sep 29, 2016.
Find out what top data scientist Claudia Perlich believes are - and are not - the biggest issues in data science today, and why spending 80% of their time with data preparation is not a problem.
- Call for bids to host KDD-2019, Premier Research Conference on Data Science and Data Mining - Sep 28, 2016.
ACM SIGKDD Executive Committee hereby invites proposals to host the annual KDD Conference in 2019. The conference should take place in August 2019.
- Brainwaves hackathon on Machine Learning - Sep 28, 2016.
This hackathon aims at attracting top developers for a 30-hour build session focused on Machine Learning. The first qualifying event will be held online in October.
- Data Science for Internet of Things (IoT): Ten Differences From Traditional Data Science - Sep 26, 2016.
The connected devices (The Internet of Things) generate more than 2.5 quintillion bytes of data daily. All this data will significantly impact business processes and the Data Science for IoT will take increasingly central role. Here we outline 10 main differences between Data Science for IoT and traditional Data Science.
- Top 16 Active Big Data, Data Science Leaders on LinkedIn - Sep 23, 2016.
Who are the most active Big Data, Data Science Influencers and Leaders on LinkedIn? We analyze the data and bring you the list of key people to follow.
- Top KDnuggets tweets, Sep 14-20: Why we need #DataScience: brain wont let us see 12 black dots at intersection - Sep 21, 2016.
Why we need #DataScience: brain won't let us see 12 black dots at intersections; #Blurring sensitive info no longer safe! #MachineLearning can recover originals ;Pokemon Go Data; The #NeuralNetwork Zoo - Great chart of different configurations.
- WPI: Professor (Open Rank) – Data Science - Sep 21, 2016.
The Data Science program invites applications for a tenure track (open rank) Professor position with a research focus in Data Science to begin in the Fall of 2017 to strengthen this important interdisciplinary area.
- 7 Ways How Data Science Fuels The FinTech Revolution - Sep 16, 2016.
Here are 7 ways how data science is at the core of the current transformation of the financial sector.
- Meet Data Science graduates – Metis Career Day Sep 22, San Francisco - Sep 15, 2016.
During a 12-week intensive program, Metis data science students build five projects using machine learning and statistical modeling techniques in Python, industry-level visualizations in D3, and real-world data in cloud-based SQL, no-SQL, and Hadoop databases.
- Data Scientist Pay and Location: Indeed’s Tech Salary Report Overview - Sep 14, 2016.
An overview of Indeed.com's 2016 Tech Salary Report, and summary details of top cities for data-centric professions vis-a-vis adjusted salary.
- Driving Data Science Productivity Without Compromising Quality - Sep 14, 2016.
How will data science teams maintain quality standards in the face of advancing automation? Attend the IBM DataFirst Launch Event on Sep 27 in NYC and learn how to drive greater productivity from your data science teams without compromising the quality of the mission-critical business assets they produce.
- Behind the Dream of Data Work as it Could Be - Sep 13, 2016.
This post is an insider's overview of data.world, and their attempt to build the most meaningful, collaborative, and abundant data resource in the world.
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- Evolving Education with Cognitive and Data Science, Oct 23 - Sep 12, 2016.
Evolving Education with Cognitive and Data Sciences brings together faculty, academic and industry leaders to explore how to rapidly evolve academic programs and research to satisfy the exploding demand for graduates skilled in cognitive and data sciences. Register today!
- Webinar: Breaking Data Science Open, Sep 15 - Sep 12, 2016.
Learn how to drive collaboration and data science teamwork; how to mitigate legal risk through open source assurance and appropriate package selection, and how to democratize innovation through broad access to open data science tools.
- The (Not So) New Data Scientist Venn Diagram - Sep 12, 2016.
This post outlines a (relatively) new(er) Data Science-related Venn diagram, giving an update to Conway's classic, and providing further fuel for flame wars and heated disagreement.
- Data Science for IoT course: Strategic foundation for decision makers - Sep 9, 2016.
The course is based on an open problem solving methodology for IoT analytics which we are developing within the course. The course starts in Sept 2016. To sign up or learn more email firstname.lastname@example.org.
- Introducing Dask for Parallel Programming: An Interview with Project Lead Developer - Sep 7, 2016.
Introducing Dask, a flexible parallel computing library for analytics. Learn more about this project built with interactive data science in mind in an interview with its lead developer.
- How to Become a Data Scientist – Part 3 - Sep 6, 2016.
This is the third and final part of a thorough, in-depth overview of becoming a data scientist, written by a recruiter in the field. This part focuses on the job market.
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- The Acceleration of Data Science Excellence - Sep 6, 2016.
If you’re a working data scientist, data engineering, or data application developer, attend IBM DataFirst Launch Event on Sep 27 in New York City. Engage with open-source community leaders and practitioners and learn how to accelerate your processes for putting data to work.
- 7 Big Data Steps in Health Science - Sep 1, 2016.
Our doctors are now getting help from Big Data, which is becoming more entrenched and more crucial to reducing the investment needed to keep us healthy. But, how does Big Data actually do this?
- How to Become a Data Scientist – Part 2 - Aug 30, 2016.
Check out part 2 of this excellent series of articles on becoming a data scientist, written by someone who spends their day recruiting data scientists. This installation focuses on learning.
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- New Poll: Which methods/algorithms you used for a Data Science or Machine Learning application? - Aug 26, 2016.
Which methods/approaches you used in the past 12 months for an actual Data Science-related application? Please vote and we will analyze and publish the results.
- A Tutorial on the Expectation Maximization (EM) Algorithm - Aug 25, 2016.
This is a short tutorial on the Expectation Maximization algorithm and how it can be used on estimating parameters for multi-variate data.
- How to Become a (Type A) Data Scientist - Aug 23, 2016.
This post outlines the difference between a Type A and Type B data scientist, and prescribes a learning path on becoming a Type A.
- How to Become a Data Scientist – Part 1 - Aug 22, 2016.
Check out this excellent (and exhaustive) article on becoming a data scientist, written by someone who spends their day recruiting data scientists. Do yourself a favor and read the whole way through. You won't regret it!
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- Join Us for the Top Analytics Conference - Aug 18, 2016.
Sign up now for the industry's leading analytics and data management conference. Get an extra $100 off TDWI San Diego with exclusive KDnuggets discount code.
- Top KDnuggets tweets, Aug 10-16: 5 EBooks to Read Before Getting into a #DataScience or #BigData Career - Aug 17, 2016.
5 EBooks to Read Before Getting into a #DataScience or #BigData Career; Visualizing 1 Billion Points of #Data Webinar; #Cartoon: Make Data Great Again!; The role of the activation function in a #NeuralNetwork
- Data Science Challenges - Aug 17, 2016.
This post is thoughts for a talk given at the UN Global Pulse lab in Kampala, and covers the challenges in data science.
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- KDnuggets™ News 16:n30, Aug 17: Why Deep Learning Works; Neural Networks with R; Central Limit Theorem for Data Science - Aug 17, 2016.
3 Thoughts on Why Deep Learning Works So Well; A Beginner's Guide to Neural Networks with R!; Central Limit Theorem for Data Science; Cartoon: Make Data Great Again
- Making Data Science Accessible – Neural Networks - Aug 11, 2016.
This post attempts to make the underlying concepts of neural networks more accessible to everyone. Gain a high level view of their working here.
- Cartoon: Facebook data science experiments and Cats - Aug 8, 2016.
In honor of International Cat Day, we revisit KDnuggets cartoon that looks at the Facebook data science experiment on emotion manipulation and the importance of happy kittens.
- Making Data Science Accessible – HDFS - Aug 4, 2016.
This post explains some basic Big Data concepts and offers some insight into when HDFS can be useful, employing basic analogies to do so.
- Getting Started with Data Science – R - Aug 3, 2016.
A great introductory post from DataRobot on getting started with data science in R, including cleaning data and performing predictive modeling.
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- Data Science for Beginners: Fantastic Introductory Video Series from Microsoft - Aug 3, 2016.
The remaining videos in Microsoft's Data Science for Beginners video series are available now. Have a look at what they offer.
- KDnuggets™ News 16:n28, Aug 3: Data Science Stats 101; Understanding NoSQL Databases; Core of Data Science - Aug 3, 2016.
Data Science Statistics 101; 7 Steps to Understanding NoSQL Databases; The Core of Data Science; Data Science for Beginners 2: Is your data ready?
- Data Science Automation: Debunking Misconceptions - Aug 2, 2016.
This opinion piece aims to clear up some proposed misconceptions surrounding data science automation.
- Getting Started with Data Science – Python - Aug 1, 2016.
A great introductory post from DataRobot on getting started with data science in the Python ecosystem, including cleaning data and performing predictive modeling.
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- The Core of Data Science - Aug 1, 2016.
This post provides a simplifying framework, an ontology for Machine Learning and some important developments in dynamical machine learning. From first hand Data Science product experience, the author suggests how best to execute Data Science projects.
- Dataiku DSS 3.1 – Now with 5 ML Backends & Scala! - Aug 1, 2016.
Introducing Dataiku DSS 3.1, with new visual machine learning engines that allow users to create incredibly powerful predictive applications within a code-free interface.
- Data Science of Visiting Famous Movie Locations in San Francisco - Jul 30, 2016.
Using the Google Places API and IMDb API, we selected movie locations in The Golden City which every movie fan should visit while they are in town, and optimize sightseeing by solving the travelling salesman problem.
- Theoretical Data Discovery: Using Physics to Understand Data Science - Jul 29, 2016.
Data science may be a relatively recent buzzword, but the collection of tools and techniques to which it refers come from a broad range of disciplines. Physics has a wealth of concepts to learn from, as evidenced in this piece.
- Data Science Statistics 101 - Jul 28, 2016.
Statistics can often be the most intimidating aspect of data science for aspiring data scientists to learn. Gain some personal perspective from someone who has traveled the path.
- Data Science for Beginners 2: Is your data ready? - Jul 28, 2016.
This second video and write-up in the Data Science for Beginners series discusses what is required of your data before it can be useful.