Search results for deep learning

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  • Marketing Analytics for Data Rich Environments

    A lot is changing in the world of marketing analytics. Marketing scientist Kevin Gray asks Professor Michel Wedel, a leading authority on this topic from the Robert H. Smith School of Business at the University of Maryland, what marketing researchers and data scientists most need to know about it.

  • Data Science Governance - Why does it matter? Why now?

    Everyone is talking about GDPR, Data Governance and Data Privacy, these days. Here we discuss what is it and why does it matter.

  • Exploratory Data Analysis in Python

    We view EDA very much like a tree: there is a basic series of steps you perform every time you perform EDA (the main trunk of the tree) but at each step, observations will lead you down other avenues (branches) of exploration by raising questions you want to answer or hypotheses you want to test.

  • What Advice Would You Give Your Younger Data Scientist Self?">Gold Blog, Jul 2017What Advice Would You Give Your Younger Data Scientist Self?

    I was asked this question recently via LinkedIn message: "What advice would you give your younger data scientist self?" The best piece of advice I honestly think I can give is this: Forget about "data science."

  • Spotlight on the Remarkable Potential of AI in KYC (Know Your Customer)

    Most people would have heard of the headline-making tremendous achievements in artificial intelligence (AI): Systems defeating world champions in board games like GO and winning quiz shows. These are small realizations of AI, but there is a silent revolution taking place in other areas, including Regulatory Compliance in Financial Services.

  • TDWI Accelerate: The Fastest Path to Achieving Your Analytics Goals, Seattle, Oct 16-18

    Accelerate gives data visionaries like you expert guidance and insight to further your business and career goals, in just three days. Super Early Bird till Aug 25 - save 20% with code ACCKD01.

  • Top KDnuggets tweets, Jun 14-20: 5 EBooks to Read Before Getting into A Data Science or Big Data Career

    Also 10 Free Must-Read Books for #MachineLearning and #DataScience; #Keras implementation of a simple Neural Net module for relational reasoning; Applying #deeplearning to real-world problems

  • Best Data Science Courses from Udemy (only $10 till June 21)

    Here are some of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until June 21, 2017.

  • Staples: Data Scientist

    Seeking a Data Scientist, responsible for applying advanced analytical methods to improve decision-making at Staples, using machine learning, statistical analysis, and mathematical optimization and playing a key role in supporting the development of state-of-the-art solutions.

  • The Surprising Complexity of Randomness

    The reason we have pseudorandom numbers is because generating true random numbers using a computer is difficult. Computers, by design, are excellent at taking a set of instructions and carrying them out in the exact same way, every single time.

  • 7 Ways to Get High-Quality Labeled Training Data at Low Cost

    Having labeled training data is needed for machine learning, but getting such data is not simple or cheap. We review 7 approaches including repurposing, harvesting free sources, retrain models on progressively higher quality data, and more.

  • Data Science for Newbies: An Introductory Tutorial Series for Software Engineers

    This post summarizes and links to the individual tutorials which make up this introductory look at data science for newbies, mainly focusing on the tools, with a practical bent, written by a software engineer from the perspective of a software engineering approach.

  • Will Data Science Eliminate Data Science?

    There are elements of what we do which are AI complete. Eventually, Artificial General Intelligence will eliminate the data scientist, but it’s not around the corner.

  • Top KDnuggets tweets, May 17-23: Beginner Guide To Understanding Convolutional Neural Networks; Big Data 2017: Top Influencers and Brands

    #BigData 2017: Top Influencers and Brands; #ICYMI 10 Free Must-Read Books for #MachineLearning and #DataScience; Good Test for #DeepLearning #ImageRecognition? #Chihuahua or #Muffin

  • Best Data Science Courses from Udemy (only $10 till May 27)

    Here a list of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until May 27, 2017.

  • Tala: Data Scientist

    Seeking a Data Scientist who is interested in solving one of the world's largest problems: financial inclusion. Our team is doing cutting-edge work in the field of Machine Learning using unique data.

  • Qventus: Data Scientist

    Seeking a Data Scientist to help predict spikes of incoming patients that could overload a hospital and suggesting solutions, model patient flow through the hospital and better schedule nurses and doctors, and identify patients who appear to be ‘slipping through the cracks’ of the care process.

  • Top 10 Recent AI videos on YouTube

    Top viewed videos on artificial intelligence since 2016 include great talks and lecture series from MIT and Caltech, Google Tech Talks on AI.

  • The Quant Crunch: The demand for data science skills

    This report, created by analyzing millions of job postings using advanced technology, divides Data Science and Analytics roles into 6 broad categories, and answers many questions, including cities, industries, job roles with most growth.

  • Samsung: Senior Data Scientist – Strategic Analytics

    Seeking a Senior Data Scientist for managing the successful design, execution, and measurement of major data initiatives across all customer-facing channels, and providing a critical link between the most technical areas of the organization and our business partners.

  • Top KDnuggets tweets, Apr 26 – May 02: Face Recognition with Python, in under 25 lines of code

    Face Recognition with Python, in under 25 lines of code; Try #DeepLearning in #Python w. a fully pre-configured VM; Homo Bayesians #MachineLearning #humor #cartoon; The Most Popular Language For #MachineLearning, #DataScience Is ...

  • Best Data Science Courses from Udemy (only $10 till Apr 29)

    Here a list of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until April 29, 2017.

  • Industrial Asset Management – Slaying hurdles to get the most from your assets

    A well-structured asset performance management (APM) plan can give real-time visibility of equipment reliability while predicting possible failures.

  • How Automated ML is Transforming the Predictive Analytics Landscape

    Learn how DataRobot automates predictive modeling, and how our platform can deliver these same types of insights and a substantial productivity boost to your machine learning endeavors, on Tuesday, May 2nd at 1:00 pm ET.

  • General Mills: Sr. Associate, Strategic Revenue Management

    Seeking a candidate for a Strategic Revenue Management role, someone who is passionate about Revenue Management / Pricing and energized by working at the intersection of marketing, sales, finance, analysis, and insight.

  • The Value of Exploratory Data Analysis

    In this post, we will give a high level overview of what exploratory data analysis (EDA) typically entails and then describe three of the major ways EDA is critical to successfully model and interpret its results.

  • New Online Data Science Tracks for 2017">Silver Blog, Apr 2017New Online Data Science Tracks for 2017

    In 2017 there are many new and revamped data science tracks that are much more comprehensive for beginners than ever before. The tracks are designed to give you the skills you need to grab a job in data science, and some even have a job guarantee.

  • The Librarian, the Scientist, the Alchemist and the Engineer: Anatomy of a DataOps Expert

    We know various job profiles in data science – data engineer, data scientist, data analyst etc. Here we explain how these roles fits in a real world data science team and what they do.

  • The 42 V’s of Big Data and Data Science">Silver Blog, Apr 2017The 42 V’s of Big Data and Data Science

    It's 2017 now, and we now operate in an ever more sophisticated world of analytics. To keep up with the times, we present our updated 2017 list: The 42 V's of Big Data and Data Science.

  • A Brief History of Artificial Intelligence">Silver Blog, Apr 2017A Brief History of Artificial Intelligence

    This post is a brief outline of what happened in artificial intelligence in the last 60 years. A great place to start or brush up on your history.

  • How to stay out of analytic rabbit holes: avoiding investigation loops and their traps

    Data scientists tend to think that their main job is to answer complex questions and gain in-depth insights, bu in reality it is all about solving problems – and the only way to solve a problem is to act on it.

  • Red Ventures: Data Scientist

    Seeking a Data Scientist with 1 – 2 years experience as a data scientist or equivalent educational training, proficient at collecting and mining data from disparate data sources, and willing to dig deeper and understand the process that creates the data.

  • Samsung: Senior Data Scientist – Strategic Analytics

    Seeking a Senior Data Scientist for managing the successful design, execution, and measurement of major data initiatives across all customer-facing channels, and providing a critical link between the most technical areas of the organization and our business partners.

  • Finding “Gems” in Big Data

    Detecting anomalous cases in large datasets is critical in conducting surveillance, countering credit-card fraud, protecting against network hacking, combating insurance fraud, and many more applications in government, business and healthcare. Learn how to do it online in "Anomaly Detection" course at

  • Top KDnuggets tweets, Mar 22-28: Big #DataScience: Expectation vs. Reality

    Also A Gentle Introduction To Graph Theory; An Overview of #Python #DeepLearning Frameworks; The Great Algorithm Tutorial Roundup.

  • A Beginner’s Guide to Tweet Analytics with Pandas

    Unlike a lot of other tutorials which often pull from the real-time Twitter API, we will be using the downloadable Twitter Analytics data, and most of what we do will be done in Pandas.

  • Senior Data Scientist

    Seeking a Senior Data Scientist to work with the API, Content, and Product teams to translate Live’s locations, events, social, and user data into business value.

  • How to think like a data scientist to become one

    The author went from securities analyst to Head of Data Science at Amazon. He describes what he learned in his journey and gives 4 useful rules based on his experience.

  • Why A/B Testers Have The Best Jobs In Tech

    Learning about what these people do made it clear that when you are deeply involved in A/B testing at scale, there is a tremendous rush from doing so many different things that matter.

  • Aetna: Lead Data Scientist

    Seeking an exceptional Lead Data Scientist to play a pivotal role in the creation and deployment of information products, and to manage and be responsible for the successful delivery of the algorithms, statistical models and reporting tools to meet business needs.

  • Accenture: Artificial Intelligence Experienced Researcher

    Seeking an experienced well-rounded artificial intelligence researcher with a passion for using AI to help us redesign how we solve critical applied business problems for the world’s largest firms.

  • Analytics, Data Science, Data Management Training May 7-12 in Chicago – save 30% with KDnuggets offer

    TDWI comes to Chicago May 7-12, and KDnuggets readers get special savings! Save 30% through next Friday, March 24 using priority code KDSAVE30. Did you know that teams of 3+ save an extra 10%?

  • LeapYear: Lead Data Scientist

    Seeking a Lead Data Scientist, responsible for conceptualizing, developing, testing, and deploying machine learning products on customer data sets. You and our data science team will use LeapYear's platform to create value from the world's most sensitive, siloed data sources.

  • Best Data Science Courses from Udemy (only $19 till Mar 31)

    Here a list of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $19 until March 31, 2017.

  • Top KDnuggets tweets, Mar 01-07: Google Unveils Neural Network with “Superhuman” Ability to Determine the Location of Almost Any Image

    Also Deep Forest: Towards An Alternative to Deep #NeuralNetworks; An Overview of #Python #DeepLearning Frameworks; The Gentlest Introduction to Tensorflow - Part 2.

  • A Simple XGBoost Tutorial Using the Iris Dataset

    This is an overview of the XGBoost machine learning algorithm, which is fast and shows good results. This example uses multiclass prediction with the Iris dataset from Scikit-learn.

  • Stylight: Senior Data Scientist

    Seeking a Senior Data Scientist to become part of our outstanding team in Munich. Along with your colleagues you are responsible for optimizing the algorithms which power our search results and product recommendations.

  • Every Intro to Data Science Course on the Internet, Ranked">Silver Blog, March 2017Every Intro to Data Science Course on the Internet, Ranked

    For this guide, I spent 10+ hours trying to identify every online intro to data science course offered as of January 2017, extracting key bits of information from their syllabi and reviews, and compiling their ratings.

  • Top KDnuggets tweets, Feb 22-28: 50 Companies Leading the #AI Revolution; #AI Nanodegree Program Syllabus

    50 Companies Leading the #AI Revolution; #AI Nanodegree Program Syllabus: Term 1, In Depth; What is a Support Vector Machine, and Why Would I Use it?; 6 Easy Steps to Learn Naive #Bayes Algorithm (with code in #Python).

  • What is Customer Churn Modeling? Why is it valuable?

    Getting new customers is much more more expensive than retaining existing ones, so reducing churn is a top priority for many firms. Understanding why customers churn and estimating the risks are powerful components of a data-driven retention strategy.

  • The Data Science Project Playbook">Silver Blog, March 2017The Data Science Project Playbook

    Keep your development team from getting mired in high-complexity, low-return projects by following this practical playbook.

  • What I Learned Implementing a Classifier from Scratch in Python

    In this post, the author implements a machine learning algorithm from scratch, without the use of a library such as scikit-learn, and instead writes all of the code in order to have a working binary classifier algorithm.

  • The Human Data Scientist: Safeguarding Your Career in the World of Automation

    "Data scientist" continues to be recognized as a top career, but does this mean unending spoils for the data scientist? With large scale mass automation on the horizon for numerous professions, what can we do to safeguard our positions?

  • The 6 Best Data Science Courses from Udemy (only $10 till Feb 28)

    Here a list of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until Feb 28, 2017.

  • Machine 4.0: Making your Factory, Production and Maintenance Data Work

    To leverage the potential of Big Data the manufacturing firms should intelligently integrate and connect their data sources on a unified platform and use machine learning to extract insights, analyze them, and derive results.

  • Why Go Long on Artificial Intelligence?

    We are now at the right place and time for AI to be the set of technology advancements that can help us solve challenges where answers reside in data. While we have already seen a few AI bull and bear markets since the 50’s, this time it’s different. If I and others are right, the implications are immensely valuable for all.

  • KDnuggets Top Blogger: An Interview with Brandon Rohrer, Top Data Scientist

    Read an interview with Top KDnuggets Blogger Brandon Rohrer, and get his thoughts on data science, newcomers to the field, and his ambitious pet project.

  • Aetna: Lead Data Scientist

    Manages and is responsible for the successful delivery of the algorithms, statistical models and reporting tools to meet business needs. Acts as the analytic team lead for large and complex projects involving multiple resources and tasks, providing individual mentoring in support of company objectives.

  • How to get your first job in Data Science?

    We provide guidelines for the most important questions, including the key data scientist skills and tools, how to get them, how to learn and practice, and where to send your application.

  • Stylight: Senior Data Scientist

    Seeking a Senior Data Scientist to become part of our outstanding team in Munich. Along with your colleagues you are responsible for optimizing the algorithms which power our search results and product recommendations.

  • Top KDnuggets tweets, Jan 04-10: Cartoon: When Self-Driving Car takes you too far; A massive collection of free programming books

    Also AI #DataScience #MachineLearning: Main Developments 2016, Key Trends 2017; Scikit-Learn Cheat Sheet: #Python #MachineLearning

  • Citizen Data Scientist, Jumbo Shrimp, and Other Descriptions That Make No Sense

    No one would say “Citizen Lawyer” or “Citizen Nuclear Physicists” or “Citizen Physician.” I guess a “Citizen Physician” would be someone who “practices medicine but whose primary job function is outside of the field of medicine (meaning that they’ve had no training in medicine or medical procedures).”

  • Top KDnuggets tweets, Dec 14-20: False positives versus false negatives: Best explanation ever

    Also #MachineLearning, #AI experts: Main Developments 2016, Key Trends 2017; Official code repository for #MachineLearning with #TensorFlow book; Top 10 Essential Books for the #Data Enthusiast.

  • Cambia Health Solutions: Data Science Engineer

    Seeking a Data Engineer to design, develop, and implement end-to-end cloud based machine learning production pipelines with high availability for a wide variety of health related projects.

  • CDO: to stay or to go?

    The Chief Digital Officer role has grown 1000-fold in the last 9 years, but will it remain popular in 2025? We examine the parallels between the electric and digital revolutions.

  • Smart Data Platform – The Future of Big Data Technology

    Data processing and analytical modelling are major bottlenecks in today’s big data world, due to need of human intelligence to decide relationships between data, required data engineering tasks, analytical models and it’s parameters. This article talks about Smart Data Platform to help to solve such problems.

  • 10 Tips to Improve your Data Science Interview

    Interviewing is a skill. Here are 10 tips and resources to improve your Data Science interviews.

  • Ethical Implications Of Industrialized Analytics

    Analytics & Big Data will be involved in every aspect of our lives and we should handle the ethical dilemmas wisely to let innovation contribute more to our lives.

  • Top KDnuggets tweets, Nov 9-15: #Trump, limits of #prediction; #TensorFlow French-to-English machine translation

    #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

  • How Bayesian Inference Works">Gold BlogHow Bayesian Inference Works

    Bayesian inference isn’t magic or mystical; the concepts behind it are completely accessible. In brief, Bayesian inference lets you draw stronger conclusions from your data by folding in what you already know about the answer. Read an in-depth overview here.

  • Ten Take-Aways from IBM World of Watson

    “Enterprise applications, Cloud, Cognitive computing and IBM Watson”, Yes, you guessed it right. This article talks about highlights of 2016 World of Watson conference organised at Las Vegas,NV.

  • For AI Engineers/Data Scientists: Implementing Enterprise AI course

    This unique course that is focussed on AI Engineering / AI for the Enterprise. Created in partnership with , the course uses Open Source technology to work with AI use cases. It is offered online and also in London and Berlin, starting January 2017.

  • Data Science 101: How to get good at R

    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.

  • NVIDIA: Technical Account Manager

    Seeking a Technical Account Manager/Sales Engineer to join the team supporting development and sales activities for the Facebook account with a focus across multiple domains including: Artificial Intelligence, Video, Virtual Reality, Server Design and Data Center Integration.

  • NVIDIA: Director for Autonomous Vehicle Localization and Mapping

    Seeking a Director for Autonomous Vehicle Localization and Mapping, requiring someone who can formulate and execute a technical roadmap from architectural specification through the full lifecycle of the product in the field.

  • What is emotion analytics and why is it important?

    In today’s Internet world, humans express their Emotions, Sentiments and Feelings via text/comments, emojis, likes and dislikes. Understanding the true meanings behind the combinations of these electronic symbols is very crucial and this is what this article explains.

  • European Machine Intelligence Landscape

    This post outlines the European machine intelligence landscape, which, until recently, has been under-appreciated in its contribution to the innovation and commercialisation of machine intelligence technologies.

  • Strata Hadoop 2016: Fast Data and Robots

    Did you miss Strata Hadoop World conference this year?? No worries! Want to know “how exciting it was”? Lets hear it from an expert in her own words.

  • K2 Data Science Bootcamp

    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.

  • Top KDnuggets tweets, Oct 05-11: Most Active #DataScientists on #Github; Why Not So Hadoop?

    Most Active #DataScientists, Free Books, Notebooks & Tutorials on #Github; Why Not So Hadoop?; Free #MachineLearning text PDF, from theory to algorithms; Top @reddit #MachineLearning Posts September.

  • University of Notre Dame: Data Science Consultant

    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.

  • Data Science of Sales Calls: The Surprising Words That Signal Trouble or Success

    While not as profound a problem as uncovering the secrets of the universe, how to conduct a successful sales conversation is an age-old problem, impacting millions of people every day.

  • Top KDnuggets tweets, Sep 21-27: What is the #Blockchain and Why is it So Important? Watch #StrataHadoop #NYC Keynotes Live Sep 28-29

    Top #DataScientists to follow on Twitter: @geoff_hinton @ylecun @SebastianThrun; What is the #Blockchain and Why is it So Important? The (Not So) New Data Scientist Venn Diagram; 9 Key #DeepLearning Papers, Explained.

  • Why people love PAW

    Reading a case study doesn't compare to hearing from its author, and asking questions. Tutorials aren't the same as live walkthroughs. And networking is more personal. That's why people keep coming back to Predictive Analytics World. Use KDN150 to save.

  • Fusion Media Group – Univision Communications: Data Scientist

    Help develop groundbreaking data-driven solutions and products to advance our growing digital and linear businesses.

  • 7 Steps to Mastering Apache Spark 2.0">Silver Blog7 Steps to Mastering Apache Spark 2.0

    Looking for a comprehensive guide on going from zero to Apache Spark hero in steps? Look no further! Written by our friends at Databricks, this exclusive guide provides a solid foundation for those looking to master Apache Spark 2.0.

  • Top KDnuggets tweets, Sep 07-13: Dask for #Parallel Programming; Computationally generated Average Face

    Computationally generated Average Face; Dask for #Parallel Programming; The (Not So) New #DataScientist Venn Diagram; Human in #AI loop - #DeepLearning lets you take an image of a dress and show...

  • Driving Data Science Productivity Without Compromising Quality

    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.

  • Top KDnuggets tweets, Aug 31 – Sep 06: Everyone else data is smaller than you think

    Everyone else data is smaller than you think; Cartoon: Data Scientist - the sexiest job of the 21st century until ... ; Amazon gets new UK presence, hires top #MachineLearning researcher Neil Lawrence, his team.

  • Top KDnuggets tweets, Aug 24-30: #DataScientist – sexiest job of the 21st century until …; Activation Function in #NeuralNetworks.

    Cartoon: #DataScientist - sexiest job of the 21st century until ...; What is the Role of the Activation Function in Neural Networks?; LinkedIn Machine Learning team tutorial on building #Recommender system; Create a #Chatbot for #Telegram in #Python to Summarize Text.

  • Introduction to Local Interpretable Model-Agnostic Explanations (LIME)

    Learn about LIME, a technique to explain the predictions of any machine learning classifier.

  • A Primer on Logistic Regression – Part I

    Gain an understanding of logistic regression - what it is, and when and how to use it - in this post.

  • How to Become a Data Scientist – Part 1">2016 Silver BlogHow to Become a Data Scientist – Part 1

    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!

  • Top KDnuggets tweets, Aug 10-16: 5 EBooks to Read Before Getting into a #DataScience or #BigData Career

    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

  • Does Data Scientist Mean What You Think It Means?

    Do we have an accurate idea of what "data scientist" actually means? Read this thought-provoking opinion on the topic.

  • Top KDnuggets tweets, Aug 03-09: Understanding the Bias-Variance Tradeoff: An Overview

    Understanding the Bias-Variance Tradeoff: An Overview; Cartoon: Facebook #DataScience experiments and Cats; Bayesian #Machine Learning, Explained; Deep Reinforcement Learning for Keras.

  • Top KDnuggets tweets, Jul 27 – Aug 2: Understanding neural networks with Google TensorFlow Playground; Getting Started with Data Science in Python

    Understanding neural networks with Google TensorFlow Playground; The 100 Best-Funded #Analytics #DataScience #Startups; Great tutorial: Getting Started with #DataScience - #Python; #MachineLearning over 1M hotel reviews: interesting insights.

  • WeWork: Principal Data Scientist

    Lead and grow a team of data scientists; work with the team to propose, choose, scope, tackle, and ultimately deliver impactful data products that drive value across the organization.

  • Data Science Statistics 101

    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.

  • O’Reilly AI: Last chance to get Best Price

    This week is your last chance to get the Best Price for the O'Reilly Artificial Intelligence Conference happening in New York September 26-27. Register with your KDnuggets discount code now!

  • KDnuggets Interview: Inderpal Bhandari, IBM Global Chief Data Officer on 4 key ideas of Cognitive Computing

    In this wide-ranging interview, we discuss the role of IBM global chief data officer, 4 key ideas of cognitive computing, risks of AI, IBM Data Science Experience, healthcare, basketball, sports analytics, and more.

  • 4 Major Trends Disrupting the Data Science Market

    An interesting excerpt from Burtch Works' recently published Burtch Works Study: Salaries of Data Scientists 2016, focusing on trends disrupting the data science market.

  • 10 Algorithm Categories for AI, Big Data, and Data Science

    With a focus on leveraging algorithms and balancing human and AI capital, here are the top 10 algorithm categories used to implement A.I., Big Data, and Data Science.

  • AI for Fun & Profit: Using the new Genie Cognitive Computing Platform for P2P Lending

    This tutorials uses the recently-released Genie (an acronym for General Evolving Networked Intelligence Engine) platform to learn from P2P (peer-to-peer) loan data. Experts and non-experts alike can leverage Genie to analyze Big Data, recognize objects, events, and patterns, and more.

  • Storytelling: The Power to Influence in Data Science

    Data scientists need to share results, which is different than talking shop with other data scientists. Read about influencing people and telling stories as a data scientist.

  • How to Compare Apples and Oranges ? : Part III

    In the previous article, look at techniques to compare categorical variables with the help of an example. In this article, we shall look at techniques to compare mixed type of variables i.e. numerical and categorical variables together.

  • Getting Started with Analytics: What’s the Upfront Investment?

    Everyone wants to leverage analytics, but should everyone dive into the deep end right away? Heed some sensible advice on getting started with analytics, and assessing the true upfront investment.

  • Top KDnuggets tweets, Jun 22-28: #Bayesian #Statistics explained in Simple English; Brexit

    #Bayesian #Statistics explained to Beginners in Simple English; Amazing analysis of #Brexit with #MachineLearning - it is sad; 18 Useful Mobile Apps for #DataScientist; Sharp divisions between England, #Scotland in #Brexit vote suggest future UK split.

  • Civis Analytics: Data Scientist, Statistics

    Seeking a Data Scientist to work closely and collaboratively with analysts and engineers to develop and operationalize the techniques that quantify and solve big, meaningful problems.

  • Improving Nudity Detection and NSFW Image Recognition

    This post discussed improvements made in a tricky machine learning classification problem: nude and/or NSFW, or not?

  • Microsoft: Sr. Applied Data Scientist.

    Microsoft is innovating rapidly in online advertising by providing the industry with the state-of-the-art online advertising platform and service. Bing Ads Marketplace and Serving (MnS) team is at the core of this effort, responsible for research & development of all the algorithmic components in our paid search advertising technology stack.

  • Predicting purchases at retail stores using HPE Vertica and Dataiku DSS

    The retail industry has been data centric for a while. With the rise of loyalty programs and digital touch points, retailers have been able to collect more and more data about their customers over time, opening up the ability to create better personalized marketing offers and promotions.

  • Top KDnuggets tweets, Jun 15-21: Predicting UEFA Euro2016; Visual Explanation of Backprop for Neural Nets

    Building statistical model to predict UEFA #Euro2016; A Visual Explanation of Back Propagation Algorithm for #NeuralNetworks; Scala is the new golden child for coding and #DataScience.

  • Apache Spark Key Terms, Explained

    An overview of 13 core Apache Spark concepts, presented with focus and clarity in mind. A great beginner's overview of essential Spark terminology.

  • How Do You Identify the Right Data Scientist for Your Team?

    Have you been trying to answer the question of what type of a data scientist would be the best fit for your team? Is there a single all-encompassing answer or does it vary based on the client objectives? Read on for some insight.

  • Infinite Data Overlap Detection Arrives to Speed Business Insights

    Infinite Data Overlap Detection(IDOD) is a new, Spark-based technology that empowers non-technical business users to automatically discover data patterns and blendany data type for any set of values from multiple sources – both inside and outside the enterprise.

  • Microsoft: Sr. Applied Data Scientist

    What if your job description were simply "Make tomorrow better?" Every day, we bring an insatiable curiosity to the table, challenging ourselves to reimagine what is and what can be. We drive machine intelligence. We help shape the future. We empower billions of people around the globe.

  • A Brief Primer on Linear Regression – Part 1

    This introduction to linear regression discusses a simple linear regression model with one predictor variable, and then extends it to the multiple linear regression model with at least two predictors.

  • Top May stories: What software you used for Analytics, Data Mining, Data Science?

    Poll: What software you used for Analytics, Data Mining, Data Science? How to Explain Machine Learning to a Software Engineer; Meet 11 Big Data & Data Science Leaders on LinkedIn.

  • Top KDnuggets tweets, May 25-31: 19 Free eBooks to learn #programming with #Python; Awesome collection of public datasets on Github

    Introducing Hybrid lda2vec Algorithm via Stitch Fix; #DeepLearning and Deep #Gaussian Processes - explainer; Awesome collection of public #datasets on Github; #DataScience foundations: 19 Free eBooks to learn #programming with #Python.

  • Hyundai: Quality Data Analytics Manager

    Seeking a Quality Data Analytics Manager to apply deep analytical skills to blend, process, and explore complex datasets for the Product Quality department to aid in knowledge discovery, and to assist with performing root-cause analysis, survival analysis, time series forecasting and other analytical activities.

  • Doing Data Science: A Kaggle Walkthrough Part 2 – Understanding the Data

    This is the second post in a fantastic 6 part series covering the process of data science, and the application of the process to a Kaggle competition. Read on for a great overview of practicing data science.

  • Be Part of Spark Summit 2016, the Premier Big Data Event Dedicated to Apache Spark

    Whether you’re an Apache Spark newbie or a hardcore enthusiast, Spark Summit, June 6-8 in San Francisco, is the place to be to gain new insights and make valuable connections. Use promo code KDNuggets to save 15%

  • Bain: Data Architect Manager

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