Dec
2017 Jan
All (106) | Courses, Education (12) | Meetings (15) | News, Features (23) | Opinions, Interviews (26) | Software (3) | Tutorials, Overviews (25) | Webcasts & Webinars (2)
- Advanced Predictive Modeling Methods at PAW Chicago
- Jan 31, 2017.
At Predictive Analytics World for Business in Chicago, June 19-22, many of the sessions and workshops cover advanced predictive modeling methods. Register for PAW Business Chicago now with super early bird rates.
- ODSC Masterclass Summit, San Francisco, March 1-2: Premium Data Science Training + Save 25% thru Jan 31
- Jan 31, 2017.
Deep Learning is on everyone's list of top skills to learn in 2017. ODSC Masterclass Summit, San Francisco, March 1-2 offers 2 intense days of hands-on training in deep learning. Use discount code: KD25 for an extra 25% Off before it expires Jan 31 at 11 PM!
- New e-learning course: Fraud Analytics using Descriptive, Predictive and Social Network Analytics
- Jan 31, 2017.
This online course teaches how to find fraud patterns from historical data using descriptive analytics, and social network learning.
- Domino Data Science Popup, San Francisco, Feb 22 – KDnuggets Offer
- Jan 31, 2017.
Learn about the latest trends in data science applications in technology from the top experts in the industry. Register by Feb 8 and save with code KDNuggetsVIP.
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Deep Learning Research Review: Natural Language Processing
- Jan 31, 2017.
This edition of Deep Learning Research Review explains recent research papers in Natural Language Processing (NLP). If you don't have the time to read the top papers yourself, or need an overview of NLP with Deep Learning, this post is for you. - Top Stories, Jan 23-29: 6 Areas of AI and Machine Learning to Watch Closely; Pandas Cheat Sheet: Data Science and Data Wrangling in Python
- Jan 30, 2017.
6 Areas of AI and Machine Learning to Watch Closely; Pandas Cheat Sheet; Great Collection of Minimal and Clean Implementations of Machine Learning Algorithms; Chatbots on Steroids: 10 Key Machine Learning Capabilities to Fuel Your Chatbot; The Top Predictive Analytics Pitfalls to Avoid
- Internet of Things Tutorial: IoT Devices and the Semantic Sensor Web
- Jan 30, 2017.
IoT applications have to collect and analyze information from multiple heterogeneous objects. Dealing with multiple sensors and internet connected objects, at multiple levels, requires attention. Read on to find out more.
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Data Scientist – best job in America, again
- Jan 30, 2017.
Glassdoor again ranked Data Scientist as the no. 1 job in USA, and 5 of the top 10 US jobs are related to Analytics, Big Data, and Data Science. - Avoiding Another AI Winter
- Jan 30, 2017.
This post is a look at the factors -- public fears and a loss of investor appetite -- that could thwart AI progress... if we don’t pay them enough attention.
- IEEE Big Data 2016 keynotes, tutorial presentations
- Jan 29, 2017.
Read the keynote and tutorial presentations on important topics including Big Data and Privacy, Mining Unstructured Text Data, Database Decay and How to Avoid It, Trajectory Data Mining, and more.
- Pandas Cheat Sheet: Data Science and Data Wrangling in Python
- Jan 27, 2017.
The Pandas library can seem very elaborate and it might be hard to find a single point of entry to the material: with other learning materials focusing on different aspects of this library, you can definitely use a reference sheet to help you get the hang of it.
- Bad Data + Good Models = Bad Results
- Jan 26, 2017.
No matter how advanced is your Machine Learning algorithm, the results will be bad if the input data
is bad. We examine one popular IMDB dataset and discuss how an analyst can deal with such data. - Artificial Intelligence and Speech Recognition for Chatbots: A Primer
- Jan 26, 2017.
Bot bots bots... Read this overview of how artificial intelligence and natural language processing are contributing to chatbot development, and where it all goes from here.
- Marketing Analytics and Data Science conference, Apr 3-5, San Francisco – KDnuggets Offer
- Jan 26, 2017.
The Marketing Analytics and Data Science conference is happening April 3-5 in San Francisco. Exclusive KDnuggets offer saves you 20% with VIP Code MADS17KDN. Register today!
- Top KDnuggets tweets, Jan 18-24: Most Popular Language For #MachineLearning and #DataScience; Intro to Geospatial Data with #Python
- Jan 25, 2017.
The Most Popular Language For #MachineLearning and #DataScience; Introduction to Geospatial Data with #Python; The #DataScience Puzzle, Revisited; Best #DataScience Books and Articles That Will Surge Your Career
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6 areas of AI and Machine Learning to watch closely
- Jan 25, 2017.
Artificial Intelligence is a generic term and many fields of science overlaps when comes to make an AI application. Here is an explanation of AI and its 6 major areas to be focused, going forward. - Why the Data Scientist and Data Engineer Need to Understand Virtualization in the Cloud
- Jan 25, 2017.
This article covers the value of understanding the virtualization constructs for the data scientist and data engineer as they deploy their analysis onto all kinds of cloud platforms. Virtualization is a key enabling layer of software for these data workers to be aware of and to achieve optimal results from.
- Great Collection of Minimal and Clean Implementations of Machine Learning Algorithms
- Jan 25, 2017.
Interested in learning machine learning algorithms by implementing them from scratch? Need a good set of examples to work from? Check out this post with links to minimal and clean implementations of various algorithms.
- Regis University MS in Data Science Now Offered On Campus
- Jan 25, 2017.
Regis University is proud to announce a new on-campus option for our Master of Science in Data Science program, which started in January 2017 in Denver, CO.
- Deploying Production-grade Data Products – Special Report
- Jan 24, 2017.
Dataiku launched a survey a few months back to find out how companies handled going from designing to deploying a data product. Read the report and learn four ways that companies approach production.
- Bringing Business Clarity To CRISP-DM
- Jan 24, 2017.
Many analytic projects fail to understand the business problem they are trying to solve. Correctly applying decision modeling in the Business Understanding phase of CRISP-DM brings clarity to the business problem.
- Creating Curious Machines: Building Information-seeking Agents
- Jan 24, 2017.
Researchers at Maluuba are developing ways to teach artificial agents how to seek information actively, by asking questions. This includes a deep neural agent that learns to accomplish these tasks through efficient information-seeking behaviour, a vital step towards Artificial General Intelligence.
- Big Data & Analytics Innovation Summit, Singapore, March 1-2, KDnuggets Offer
- Jan 23, 2017.
The summit will offer you many opportunities to network with over 250 thought leaders and to dig into multiple aspects within big data. Save 20% with code KDN20.
- Predictive Analytics. Max Results. Min Time.
- Jan 23, 2017.
Successful analytics in the big data era does not start with data and software, but with immersive, interactive training and goal-driven strategy. TMA’s live online and classroom training spans all skill levels and analytic team roles to build analytic leaders. Live Online in February; Dubai U.A.E in March; or Washington, DC in April.
- The Top Predictive Analytics Pitfalls to Avoid
- Jan 23, 2017.
Predictive modelling and machine learning are significantly contributing to business, but they can be very sensitive to data and changes in it, which makes it very important to use proper techniques and avoid pitfalls in building data science models.
- Chatbots on Steroids: 10 Key Machine Learning Capabilities to Fuel Your Chatbot
- Jan 23, 2017.
As chatbots become a common practice, the need for smarter bots arises. Empowering your bot with machine learning capabilities can really differentiate it from the rest. Check out these 10 capabilities to help fuel your chatbot.
- Discover our Master in Business Analytics and Big Data!
- Jan 23, 2017.
The Master in Business Analytics & Big Data from the IE School of Human Sciences and Technology is an innovative degree offered in a Full-Time (Madrid) and Part-Time (Madrid & Dubai) format to train the new generation of data professionals.
- Top Stories, Jan 16-22: Time Series Analysis: A Primer; Deep Learning Can be Applied to Natural Language Processing
- Jan 23, 2017.
Time Series Analysis: A Primer; Deep Learning Can be Applied to Natural Language Processing; The Current State of Automated Machine Learning; Introduction to Forecasting with ARIMA in R; 90 Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning
- Learn how to Develop and Deploy a Gradient Boosting Machine Model
- Jan 20, 2017.
GBM is one the hottest machine learning methods. Learn how to create GBM using SciKit-Learn and Python and understand the steps required to transform features, train, and deploy a GBM.
- 100,000 LinkedIn Followers
- Jan 20, 2017.
I reached a milestone of 100,000 LinkedIn followers this week. Here are some of my most popular recent posts.
- Eat Melon: A Deep Q Reinforcement Learning Demo in your browser
- Jan 20, 2017.
Check "Eat Melon demo", a fun way to gain familiarity with the Deep Q Learning algorithm, which you can do in your browser.
- The Data Science Puzzle, Revisited
- Jan 20, 2017.
The data science puzzle is re-examined through the relationship between several key concepts in the realm, and incorporates important updates and observations from the past year. The result is a modified explanatory graphic and rationale.
- Webinar: Predictive Analytics: Failure to Launch – Feb 14
- Jan 19, 2017.
Learn how to get started with predictive modeling and overcome strategic and tactical limitations that cause data mining projects to fall short of their potential. Next webinar is Feb 14.
- Data Science of Sales Calls: 3 Actionable Findings
- Jan 19, 2017.
How does AI help sales and marketing teams in the organisation? Let’s understand Dos and don’ts of sales calls with the help of analysis of over 70,000+ B2B SaaS sales calls.
- Going to War with the Giants: Automated Machine Learning with MLJAR
- Jan 19, 2017.
The performance of automated machine learning tool MLJAR on Kaggle competition data is presented in comparison with those from other predictive APIs from Amazon, Google, PredicSis and BigML.
- The big data ecosystem for science: X-ray crystallography
- Jan 19, 2017.
Diffract-and-destroy experiments to accurately determine three-dimensional structures of nano-scale systems can produce 150 TB of data per sample. We review how such Big Data is processed.
- Get Early Price for the priceless: Strata + Hadoop World
- Jan 19, 2017.
Whatever you want to learn about data, you’ll find it at Strata + Hadoop World. Take a look at the program and see for yourself, and register by midnight January 20 with code PCKDNG and save up to $670 on your pass.
- Four Problems in Using CRISP-DM and How To Fix Them
- Jan 18, 2017.
CRISP-DM is the leading approach for managing data mining, predictive analytic and data science projects. CRISP-DM is effective but many analytic projects neglect key elements of the approach.
- The Current State of Automated Machine Learning
- Jan 18, 2017.
What is automated machine learning (AutoML)? Why do we need it? What are some of the AutoML tools that are available? What does its future hold? Read this article for answers to these and other AutoML questions.
- 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.
- More Data or Better Algorithms: The Sweet Spot
- Jan 17, 2017.
We examine the sweet spot for data-driven Machine Learning companies, where is not too easy and not too hard to collect the needed data.
- Time Series Analysis: A Primer
- Jan 17, 2017.
Time series analysis is a complex subject but, in short, when we use our usual cross-sectional techniques such as regression on time series data, variables can appear "more significant" than they really are and we are not taking advantage of the information the serial correlation in the data provides.
- Discover the new Modern Data Science Academy
- Jan 17, 2017.
The Modern Data Science Academy provides state-of-the-art workshops taught by San Diego Supercomputer Center experts. Coming workshops on Machine Learning (Feb 8-9) and NoSQL Databases (Mar 1-2).
- 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.
- Introduction to Forecasting with ARIMA in R
- Jan 16, 2017.
ARIMA models are a popular and flexible class of forecasting model that utilize historical information to make predictions. In this tutorial, we walk through an example of examining time series for demand at a bike-sharing service, fitting an ARIMA model, and creating a basic forecast.
- CAMELYON17 Grand Challenge – Help improve diagnosis of breast cancer metastases with AI
- Jan 16, 2017.
Here is a challenge to contribute to the world health, organised by Camelyon17 and IEEE. Come forward to build a healthy world. Submission deadline is April 1, 2017s.
- Deep Learning Can be Applied to Natural Language Processing
- Jan 16, 2017.
This post is a rebuttal to a recent article suggesting that neural networks cannot be applied to natural language given that language is not a produced as a result of continuous function. The post delves into some additional points on deep learning as well.
- Hurry – 10 Days Until 2017’s Essential Data Event
- Jan 16, 2017.
There are only 10 days to go until the Las Vegas Data & Analytics Summits, and only a handful of passes left. If you haven't had a chance to register yet, do it now!
- Top Stories, Jan 9-15: The Most Popular Language For Machine Learning and Data Science; Analytics and Data Science Make Business Smarter
- Jan 16, 2017.
The Most Popular Language For Machine Learning and Data Science; Analytics and Data Science Make Business Smarter; Exclusive Interview with Jeremy Howard; 5 Machine Learning Projects You Can No Longer Overlook, January
- Exclusive: Interview with Jeremy Howard on Deep Learning, Kaggle, Data Science, and more
- Jan 14, 2017.
My exclusive interview with rock star Data Scientist Jeremy Howard, on his latest Deep Learning course, what is needed for success in Kaggle, how Enlitic is transforming medical diagnostics, and what Data Scientists should do to create value for their organization.
- Clean Data Science: Evaluating The Cleanliness of NYC Craft Beer Bar Kitchens
- Jan 13, 2017.
An analysis of NYC Open Data health inspections showing that craft beer bar kitchens in Manhattan are cleaner than the average establishment by a statistically significant margin. An encouraging finding for Dry January.
- Data Exploration in Preparation for Modeling
- Jan 13, 2017.
The most important traits for a good data analyst or data miner are curiosity, creativity and intuition for how to answer important questions using data. Read this white paper to learn more.
- A Concise Overview of Recent Advances in Chatbot Technologies
- Jan 13, 2017.
2016 saw some big leaps in chatbot technologies (along with a few unforeseen embarrassments). Get a quick review of the big events in the space over the past year, complete with supporting videos.
- Predictive Analytics World San Francisco – Early Bird ends Soon
- Jan 13, 2017.
Predictive Analytics World for Business is heading to San Francisco this Spring. The deadline to save with Super Early Bird rates is around the corner, but act today and save an additional $150 using discount code KDN150.
- Data Hoarding and Alternative Data In Finance – How to Overcome the Challenges
- Jan 13, 2017.
Big data craze inspires firms to save every possible bit of data, with the misconception that the more data you have, the better. Firms must keep data (for compliance purposes) or often aren’t sure what information they need to keep. This post looks at alternative data sources.
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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. - A Concise Overview of Recent Advances in the Internet of Things (IoT)
- Jan 12, 2017.
A lot happened in IoT during 2016. Read this post for a briefing on some of the most important events, how they unfolded, and what they mean moving forward, complete with select videos to reinforce and elaborate.
- 6 Steps to Effective Data Preparation for Quality Conclusions
- Jan 12, 2017.
Data preparation is usually the most time consuming part of a data analysis project. To get good results, follow the six steps here, starting with Understand the Business Needs, Get to Know the Data, and Wrangle, Munge, and Mash Up.
- Doctor of Business Administration/Data Analytics, Online at Grand Canyon University
- Jan 12, 2017.
Offered in a convenient online format, this doctoral program empowers expert data analysts to spark new industry-wide innovation.
- Top KDnuggets tweets, Jan 04-10: Cartoon: When Self-Driving Car takes you too far; A massive collection of free programming books
- Jan 11, 2017.
Also AI #DataScience #MachineLearning: Main Developments 2016, Key Trends 2017; Scikit-Learn Cheat Sheet: #Python #MachineLearning
- 4 ways to learn about Deep Learning, Anomaly Detection and more Data Science topics online at Statistics.com
- Jan 11, 2017.
Online courses at Statistics.com are small, with rich and engaging content that includes readings, videos, quizzes, homework, projects, and practical work with software. Use promo code deepkdn17 to save.
- 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 Concise Overview of Recent Advances in Vehicle Technologies
- Jan 11, 2017.
2016 was a big year for electric and driverless cars. Get a quick review with relevant videos on some of the events of interest in the field during the past year.
- Top /r/MachineLearning Posts, 2016: Google Brain AMA; Google Machine Learning Recipes; StarCraft II AI Research Environment
- Jan 11, 2017.
Google Brain AMA; Google Machine Learning Recipes; StarCraft II AI Research Environment; Huggable Image Classifier; xkcd: Linear Regression; AlphaGO WINS!; TensorFlow Fizzbuzz
- Deep Learning in Healthcare Summit in London, 28 February – 1 March (KDnuggets Offer)
- Jan 11, 2017.
Discover advances in deep learning tools and techniques from the world's leading innovators across industry, academia and the healthcare sector at the Deep Learning in Healthcare Summit in London, 28 February – 1 March. Use discount code KDNUGGETS to save 20%.
- Prepare for Growing Data Field with Merrimack College
- Jan 10, 2017.
Merrimack College online MS in Data Science and MS in Business Analytics degrees provide a personalized and convenient curriculum that teaches the skills employers demand.
- Text Mining Amazon Mobile Phone Reviews: Interesting Insights
- Jan 10, 2017.
We analyzed more than 400 thousand reviews of unlocked mobile phones sold on Amazon.com to find out insights with respect to reviews, ratings, price and their relationships.
- 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.
- KDnuggets Top Blogs and Bloggers in December 2016
- Jan 10, 2017.
We recognize our top blogs and bloggers in December 2016, who wrote about Data Science and Machine Learning Cheat Sheets, Machine Learning & AI Main Developments in 2016 and Key Trends in 2017, and more.
- Data Analytics Summit, March 9-10, Free Event – RSVP
- Jan 10, 2017.
Harrisburg University of Science and Technology invites you to attend the FREE 2017 Data Analytics Summit, March 9 & 10, 2017, where the theme will be Analytics Applied: Case Studies, Measuring Impact, and Communicating Results. RSVP now!
- 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.
- Predictive Analytics World for Manufacturing, Germany, Feb 2-3, Program highlights
- Jan 9, 2017.
Learn to expert presentations from leading companies (including IBM Watson, Microsoft, and Nokia Bell Labs) with a strong focus on real-world examples of deployed predictive analytics techniques.
- Top Stories, Jan 2-8: 5 Machine Learning Projects You Can No Longer Overlook, January; Machine Learning and Cyber Security Resources
- Jan 9, 2017.
5 Machine Learning Projects You Can No Longer Overlook, January; Machine Learning and Cyber Security Resources; Generative Adversarial Networks - Hot Topic in Machine Learning; Ten Myths About Machine Learning
- Social Media for Marketing and Healthcare: Focus on Adverse Side Effects
- Jan 9, 2017.
Social media like twitter, facebook are very important sources of big data on the internet and using text mining, valuable insights about a product or service can be found to help marketing teams. Lets see, how healthcare companies are using big data and text mining to improve their marketing strategies.
- Big Data to Big Profits: Strategies for Monetizing Social, Mobile, and Digital Data with Data Science, Mar 23-24, San Francisco
- Jan 9, 2017.
This course will examine how firms can take big data to big profits through data monetization strategies and the best use of data science for growth and innovation across your organization.
- The Surprising Ethics of Humans and Self-Driving Cars
- Jan 9, 2017.
The surprising finding is that people are much more willing to ride in a self-driving car that might kill them to save several pedestrians than in a car that would save them but kill pedestrians. Asian respondents had significantly different preferences from US and Europe.
- arXiv Paper Spotlight: Sampled Image Tagging and Retrieval Methods on User Generated Content
- Jan 9, 2017.
Image tagging with user generated content in the wild, without the use of curated image datasets? Read more about this paper and its promising research.
- What Insurers in Asia doing about their digital transformation?
- Jan 8, 2017.
Digital transformation that allows insurers to become more agile and customer-facing is fuelling growth globally. But what are Insurers in Asia doing about their digital transformation? Read this exclusive white paper.
- 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.
- Machine Learning Meets Humans – Insights from HUML 2016
- Jan 6, 2017.
Report from an important IEEE workshop on Human Use of Machine Learning, covering trust, responsibility, the value of explanation, safety of machine learning, discrimination in human vs. machine decision making, and more.
- Internet of Things Tutorial: WSN and RFID – The Forerunners
- Jan 6, 2017.
WSN and RFID are key to understanding more complex IoT concepts and technologies, but also the structure of non-trivial IoT systems, which are very likely to comprise RFID or WSN components.
- What Are Your Analytics Goals for 2017?
- Jan 6, 2017.
Let TDWI Las Vegas give you a head start with the latest skills in analytics, data science and data management this February 12-17. Save 10% now with priority code VEGAS24!
- Top December Stories: 50+ Data Science, Machine Learning Cheat Sheets; Machine Learning/AI: Main 2016 Developments, Key 2017 Trends
- Jan 5, 2017.
Also Why Deep Learning is Radically Different From Machine Learning; Bayesian Basics, Explained
- Deep Learning Summit in San Francisco, Jan 26-27 (KDnuggets Offer)
- Jan 5, 2017.
Discover advances in Deep Learning, NLP, speech recognition, image retrieval, virtual assistants, and more from leading researchers and industry at the Deep Learning Summit and Virtual Assistant Summit in San Francisco, 26-27 January. Use code KDNUGGETS to save 20%.
- 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.
- The Major Advancements in Deep Learning in 2016
- Jan 5, 2017.
Get a concise overview of the major advancements observed in deep learning over the past year.
- Creating Data Visualization in Matplotlib
- Jan 5, 2017.
Matplotlib is the most widely used data visualization library for Python; it's very powerful, but with a steep learning curve. This overview covers a selection of plots useful for a wide range of data analysis problems and discusses how to best deploy each one so you can tell your data story.
- Top /r/MachineLearning Posts, December: OpenAI Universe; Deep Learning MOOC For Coders; Musk: Tesla Gets Awesome-er
- Jan 5, 2017.
OpenAI Universe; Deep Learning For Coders—18 hours of lessons for free; Elon Musk on Twitter: Tesla Autopilot vision neural net now working well; Apple to Start Publishing AI Research; Duolingo's "half-life regression" method for modeling human memory
- Top KDnuggets tweets, Dec 21 – Jan 03: R vs Python: A Comparison and Free Books to Learn; Popular Deep Learning Tools – a review
- Jan 4, 2017.
R vs Python: A Comparison and Free Books to Learn; The Five Capability Levels of Deep Learning - Yann Lecun view; The Future Of Machine Learning, McKinsey 2016 Analytics Study; #BigData: Main Developments in 2016 and Key Trends in 2017
- Cartoon: When Self-Driving Car + Machine Learning takes you too far …
- Jan 4, 2017.
What can happen in the not too distant future when advanced technologies like a Self-Driving car and Machine Learning Recommendations Engine are combined ...
- How To Stay Competitive In Machine Learning Business
- Jan 4, 2017.
To stay competitive in machine learning business, you have to be superior than your rivals and not the best possible – says one of the leading machine learning expert. Simple rules are defined here to make that happen. Let’s see how.
- Tidying Data in Python
- Jan 4, 2017.
This post summarizes some tidying examples Hadley Wickham used in his 2014 paper on Tidy Data in R, but will demonstrate how to do so using the Python pandas library.
- Get a data science job, guaranteed
- Jan 4, 2017.
Springboard, a leader in data science education, is launching the first data science bootcamp to guarantee you a data science career -- or your money back. The program is very selective, so apply quickly to see if you qualify.
- Fundamentals of Machine Learning for Predictive Data Analytics, Dublin, 21-23 March, 2017
- Jan 4, 2017.
Based on the trainers book, this course presents a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.
- Revenue per Employee: golden ratio, or red herring?
- Jan 4, 2017.
There is growing support for revenue per employee as one of the most underrated metrics available for assessing business performance in a crowded marketplace.
- 100+ Upcoming Meetings in Analytics, Big Data, Data Mining, Data Science: January and Beyond
- Jan 3, 2017.
Coming soon: Global AI Santa Clara, Big Data Innovation Las Vegas, CAO Miami, Deep Learning Summit San Francisco, PAw Manufacturing Dusseldorf, WSDM 2017 Cambridge UK, AnacondaCON Austin, TDWI Las Vegas, and more.
- 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.
- Generative Adversarial Networks – Hot Topic in Machine Learning
- Jan 3, 2017.
What is Generative Adversarial Networks (GAN) ? A very illustrative explanation of GAN is presented here with simple examples like predicting next frame in video sequence or predicting next word while typing in google search.
- 3 methods to deal with outliers
- Jan 3, 2017.
In both statistics and machine learning, outlier detection is important for building an accurate model to get good results. Here three methods are discussed to detect outliers or anomalous data instances.
- Ten Myths About Machine Learning, by Pedro Domingos
- Jan 3, 2017.
Myths on artificial intelligence and machine learning abound. Noted expert Pedro Domingos identifies and refutes a number of these myths, of both the pessimistic and optimistic variety.
- Uber-fication! Uberize Your Business
- Jan 2, 2017.
We examine what Uber has done that drives success in many markets across the globe and why so many businesses are seeking an Uber-style solution to their business. We present a listing of lessons on what to do if you are seeking to Uber-ize your business model.
- Top Stories, Dec 26-Jan 1: Game Theory Reveals the Future of Deep Learning; A Funny Look at Big Data and Data Science
- Jan 2, 2017.
Game Theory Reveals the Future of Deep Learning; A Funny Look at Big Data and Data Science; Machine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017; How I Detect Fake News, by Tim O’Reilly
- Global Predictive Analytics and Data Management Forum, Milan, February 2-3, 2017
- Jan 2, 2017.
The forum is a cross industry, vendor-neutral event where global senior speakers will present case studies, share their expertise in predictive analytics, data management, and digital transformation of their companies. Register by Jan 20 to get 20% off.
- Machine Learning and Cyber Security Resources
- Jan 2, 2017.
An overview of useful resources about applications of machine learning and data mining in cyber security, including important websites, papers, books, tutorials, courses, and more.
- 5 Machine Learning Projects You Can No Longer Overlook, January
- Jan 2, 2017.
There are a lot of popular machine learning projects out there, but many more that are not. Which of these are actively developed and worth checking out? Here is an offering of 5 such projects, the most recent in an ongoing series.
- Academic/Research positions in Business Analytics, Data Science, Machine Learning in December 2016
- Jan 2, 2017.
Academic Director Data Science Notre Dame, Postdocs in ML at Oxford, PhD in Q/A at Bonn, Faculty at Washington Jefferson College, Faculty in Machine Learning at Edinburgh, and more.
Automating Every Aspect of Your Python Project