Search results for deep learning

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  • 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

    Seeking a Data Architect Manager to work with consulting teams to understand and translate business problems, help to increase consulting staff’s knowledge of Advanced Analytics and Data Science, and develop/implement various data tools.

  • Boosting Productivity of the Next-Generation Data Scientist: IBM June 6 event

    On June 6, IBM will share important announcements for making R, Spark, and open data science a sustainable business reality at the Apache Spark Maker Community Event in San Francisco, Attend in person or watch live.

  • Top KDnuggets tweets, May 11-17: Vote: What software you used for Analytics, Data Mining, Data Science projects?

    Vote: What software you used for Analytics, Data Mining, Data Science projects? Useful #Cheatsheet: #Python, R #rstats code for #MachineLearning Algorithms; TPOT: A #Python Tool for Automating Data Science; Randomize Acceptance of Borderline Research Papers, save 25 reviewer person-years.

  • Spark 2.0 Preview Now on Databricks Community Edition: Easier, Faster, Smarter

    The preview of Spark 2.0 is here, and it promises to be easier, faster, and smarter.

  • HR/Workforce Analytics leadership conference/London/Innovation Enterprise: Summary

    Two intense days, buzzing with energy, knowledge exchange, panel discussions, in short London Data Festival was a great place to be if you are a data scientist. Here is summary of speakers and major attractions of the event.

  • Data Science and Cognitive Computing with HPE Haven OnDemand: The Simple Path to Reason and Insight

    HPE Haven OnDemand is a diverse collection of APIs for interacting with data designed with flexibility in mind, allowing developers to quickly perform data tasks in the cloud. See why it is a simple path to reason and insight for data science and cognitive computing.

  • 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.

  • Free Advice For Building Your Data Science Career

    Got hired as data scientist, where to go now from here? Understand how you can make the most of your career by following the different paths like managerial, consulting, or as a domain expert.

  • Building effective “Citizens Data Scientist” teams

    The idea of citizen data scientists is being for more than a year, which suggests businesses to put the people from the business side in the work of exploring and analyzing data. Understand how you and your organisation can be benefitted by this.

  • Three Pitfalls to Avoid When Building Data Science Into Your Business

    An overview of pitfalls to avoid when building data science into your business, how to avoid them, and what to do instead.

  • The MBA Data Science Toolkit: 8 resources to go from the spreadsheet to the command line

    A great guide for the MBA, or any relatively non-technical convert, for getting comfortable with the command line and other technical skills required to excel in data science.

  • TD: Sr. Manager, Analytics Innovation

    Seeking a Senior Manager, Analytics Innovation, to be part of a dynamic, innovative team, exhibiting hands-on experience working in Big Data Analytical environments, a deep understanding of analytical techniques, and previous success building strong working relationships.

  • TD: Sr. Manager, Data Science

    Seeking a Senior Manager, Data Science, with a deep understanding of data mining and analytical technique, with a passion for doing leading-edge analytical work with big data alongside a dynamic, innovative team.

  • TD: Data Scientist

    Seeking a Data Scientist with a deep understanding of data mining and analytical technique, with a passion for doing leading-edge analytical work with big data alongside a dynamic, innovative team.

  • RetailMeNot: Principal Data Scientist, Attribution

    Lead the development of our retailer/brand attribution modeling and pricing analytics, and collaborate with product/ business teams to translate insights into a holistic pricing strategy to optimize for retailer/brand ROI goals and help RMN grow our share of marketing budgets.

  • Automatic Data Science: DataRobot, Quill and Loom Systems

    Automatic data science is on the rise. This post examines three recent visionary solutions: DataRobot, Quill and Loom Systems.

  • Ravel: Senior Data Scientist

    Seeking a Lead or Senior Data Scientist to join our rapidly growing team; A senior member of the Data Science team, you will design systems to tackle tough problems in the legal domain and expand our award-winning products.

  • Open Data in Elections: Using Visualization and Graphical Discovery Analysis for Voter Education and Civic Engagement

    This article makes a case for the importance of innovating using open data, its also proves that adapting open data principles with visual design can enhance transparency, foster accountability, and aid citizen and voter education in elections.

  • 3 Ways to Build an Analytics Dream Team

    So your March Madness bracket is busted. Maybe that new algorithm can through the first round next year. It's never too early to start building your analytics Dream Team.

  • Civis Analytics: Data Scientist, Statistics

    Be part of the Research and Development team, responsible for developing the fundamental data science methods, techniques, and best practices that power the mission of our company, performing predictive analytics, algorithm development, experimental design, visualization, and survey research.

  • Engineers Shouldn’t Write ETL: A Guide to Building a High Functioning Data Science Department

    An exploration of data science team building, with insight into why engineers should not write ETL, and other not-so-subtle pieces of advice.

  • HR Analytics Starter Kit – Intro to R

    We review tools to help you start performing HR analytics with a focus on R platform, and providing useful examples for the HR and Workforce analytics using R.

  • Lift Analysis – A Data Scientist’s Secret Weapon

    Gain insight into using lift analysis as a metric for doing data science. Understand how to use it for evaluating the performance and quality of a machine learning model.

  • AlphaGo is not the solution to AI

    The field will be better off without an bust cycle it is important for people to keep and inform a balanced view of successes and their extent. AlphoGo might be a step forward for the AI community, but it is still no way close to the true AI.

  • Top KDnuggets tweets, Feb 29 – Mar 06: Data Science Process; Wisdom of Crowds fails to solve this simple puzzle

    Wisdom of Crowds fails to solve this simple #math #puzzle ; #DataScience Process - the work flow of a data scientist; R is the fastest-growing language on #StackOverflow; @DeepDrumpf #DeepLearning #Twitterbot imitates #DTrump, more plausible than real one.

  • Automated Data Science and Data Mining

    Automated Data Science is becoming more popular. Here is our initial list of automated Data Science and Data Mining platforms.

  • Wells Fargo: Data Scientist

    Apply statistical/ machine learning techniques, to develop segmentations, predictive models, experimental designs, and decision analyses; Develop algorithms to optimize product offering, pricing, and distribution channel, and more.

  • Webinar: Building Data Products for Predictive Maintenance, Mar 9

    Dr. Kirk Borne, Data Science thought leader, will address the interesting trends in the world of data science. DataRPM Co-founder Ruban Phukan will show how a cognitive data science platform like DataRPM helps companies to build data products.

  • Top KDnuggets tweets, Feb 22-28: Quantifying Similarity in Structured Data; #Oscar #DataScience: 4-5 nominations no guarantee of winning

    A Statistical View of #DeepLearning; Impressive tutorial - Tree Kernels: Quantifying Similarity in Structures; Conversation with Data Scientist Sebastian Raschka - new podcast; How to become a #Bayesian in eight easy steps.

  • Top KDnuggets tweets, Feb 15-21: Is Big Data Still a Thing? 10 types of #regression. Which one to use?

    10 types of #regression. Which one to use? Is Big Data Still a Thing? 2016 #BigData Landscape; Demystifying #DeepReinforcement Learning; #TextMining #SouthPark.

  • Simplilearn and Tableau to educate 200,000 Data Scientists by 2020

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