2017 Mar
All (117) | Courses, Education (9) | Meetings (17) | News, Features (21) | Opinions, Interviews (27) | Software (4) | Tutorials, Overviews (35) | Webcasts & Webinars (4)
- Medical Image Analysis with Deep Learning - Apr 6, 2017.
In this article, I start with basics of image processing, basics of medical image format data and visualize some medical data.
- A Short Guide to Navigating the Jupyter Ecosystem - Mar 31, 2017.
This post presents a no-nonsense overview of the Jupyter ecosystem, and a few tips, tricks and concepts you may find useful for navigating it.
- PLOTCON, Largest Data Visualization Event of its kind, Oakland, May 2-5 - Mar 31, 2017.
For data scientists, journalists, and business analysts, PLOTCON is THE opportunity to meet the creators of the tools you use everyday, ask questions, hear where the future is heading, and be part of the conversation. Use code KDNUGGETS to save.
- Join CommBank to push the boundaries of what is, and what could be - Mar 30, 2017.
CommBank, Australia leading bank, is searching for smarter, faster and better solutions. Which is why we're investing in people like you. Talented analytics professionals ready for the next step in their career.
- Put Your Best Face Forward: The New Frontier of Communication - Mar 30, 2017.
Our events are people-focused, bringing brands, influencers, and talent into one space with one goal: to solve all the problems worth solving. We plan conferences that are fun and relaxed on the front end and organized and optimized on the back end.
- What makes a great data scientist? - Mar 30, 2017.
Here are 3 key traits that differentiate between a data scientist and a great data scientist, starting with – great data scientist is obsessed with solving problems, not new tools.
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The Best R Packages for Machine Learning - Mar 30, 2017.
There is no doubt R is language of choice for the majority of data scientists who want to understand data, especially those looking to leverage its great machine learning packages. - Join Deep Learning Leaders in London, June 1-2 (KDnuggets Offer) - Mar 30, 2017.
400+ leading experts and business executives convene at the Deep Learning in Finance & Retail and Advertising Summits, London, June 1-2. KDnuggets subscribers get 20% off with code KDNUGGETS.
- Top KDnuggets tweets, Mar 22-28: Big #DataScience: Expectation vs. Reality - Mar 29, 2017.
Also A Gentle Introduction To Graph Theory; An Overview of #Python #DeepLearning Frameworks; The Great Algorithm Tutorial Roundup.
- Webinar: Predictive Analytics, Failure to Launch – Apr 13 - Mar 29, 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 Apr 13.
- Key Takeaways from Strata + Hadoop World 2017 San Jose, Day 2 - Mar 29, 2017.
The focus is increasingly shifting from storing and processing Big Data in an efficient way, to applying traditional and new machine learning techniques to drive higher value from the data at hand.
- A Beginner’s Guide to Tweet Analytics with Pandas - Mar 29, 2017.
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.
- It’s Getting Hot In Here: Data Science vs Fake News - Mar 29, 2017.
While some opponents still hold the misconception that the 'science is not yet in' on the culprit, the scientific community has long reached a consensus to the drivers behind the increase in global temperatures.
- Chatbots & Virtual Assistants for the Enterprise, San Francisco, May 15-16, KDnuggets Offer - Mar 28, 2017.
Gain insight into their build, partner or buy decisions, their real-life implementation stories, using bots/VAs to generate customer insights, and the unexpected hurdles they had to overcome. Use code KNUG15 for a 15% discount.
- Deep Learning, Generative Adversarial Networks & Boxing – Toward a Fundamental Understanding - Mar 28, 2017.
In this post we will see why GANs have so much potential, and frame GANs as a boxing match between two opponents.
- Standardization and Specialization in Analytics, Data Science, and BI - Mar 28, 2017.
We see beginnings of both standardization and specialization, with graduate analytics curriculum that covers math, statistics, CS, IT systems, and communications. We also see specializations in data science and BI, and verticals like marketing and healthcare analytics.
- The Next Challenges for Reinforcement Learning - Mar 28, 2017.
Despite the recent success of RL, there is still a lot of work to be done before it will become a mainstream technique. In this blog-post, we look at some of the remaining challenges that are currently being studied.
- Webinar: Improve Your CLASSIFICATION with CART(r) and RandomForests(r), Mar 29 - Mar 27, 2017.
We discuss the advantages of tree based techniques, including automatic variable selection, variable interactions, nonlinear relationships, outliers, and missing values.
- Top Stories, Mar 20-26: What Is Data Science, What Does a Data Scientist Do?; The Most Underutilized Function in SQL - Mar 27, 2017.
What Is Data Science, and What Does a Data Scientist Do?; The Most Underutilized Function in SQL; Getting Started with Deep Learning; Getting Up Close and Personal with Algorithms; How to think like a data scientist to become one
- From Big Data Platforms to Platform-less Machine Learning - Mar 27, 2017.
The rise in serverless architectures along with marketplaces from cloud providers creates a significant momentum to democratize big data analytics. Machine learning or AI services are much more valuable, tangible and easier to understand for businesses than clumsy big data platforms.
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What is Structural Equation Modeling? - Mar 27, 2017.
Structural Equation Modeling (SEM) is an extremely broad and flexible framework for data analysis, perhaps better thought of as a family of related methods rather than as a single technique. What is its relevance to Marketing Research? - Last Chance: Big Data San Francisco, April 19 & 20 - Mar 27, 2017.
The Big Data Innovation Summit is coming to San Francisco, April 19 & 20. We are now down to the final batch of passes - secure yours with $200 off using code KD200.
- Analytics and Machine Learning training in Q2 - Mar 24, 2017.
Learn Anomaly Detection, Deep Learning, or Customer Analytics in R online at Statistics.com with top instructors who are leaders of the field. Use code 3CAP17 before March 30 to save $170.
- Getting Started with Deep Learning - Mar 24, 2017.
This post approaches getting started with deep learning from a framework perspective. Gain a quick overview and comparison of available tools for implementing neural networks to help choose what's right for you.
- IBM Chief Data Officer Strategy Summit, March 29-30, San Francisco – free VIP passes - Mar 24, 2017.
Join over 150 Chief Data Officers, Chief Analytics Officers and other senior data leaders in San Francisco. A few VIP complimentary places are still available.
- Key Takeaways from Strata + Hadoop World 2017 San Jose, Day 1 - Mar 24, 2017.
The focus is increasingly shifting from storing and processing Big Data in an efficient way, to applying traditional and new machine learning techniques to drive higher value from the data at hand.
- Unsupervised Investments: A Comprehensive Guide to AI Investors - Mar 24, 2017.
This article presents a list of 80 funds investing in Artificial Intelligence and Machine Learning.
- Make Analytics Pay with Live Immersive Training - Mar 23, 2017.
Successful analytics starts 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. Washington, DC in April, Live Online in May and Seattle in July.
- How to think like a data scientist to become one - Mar 23, 2017.
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.
- What Is Data Science, and What Does a Data Scientist Do? - Mar 23, 2017.
This article is intended to help define the data scientist role, including typical skills, qualifications, education, experience, and responsibilities. This definition is somewhat loose, and given that the ideal experience and skill set is relatively rare to find in one individual.
- Apache Big Data: top projects, people and technologies – KDnuggets Offer - Mar 23, 2017.
Apache: Big Data gathers the Apache projects, people and technologies in Big Data in Miami, May 16-18, 2017. KDnuggets readers save 20% with discount code ABDKD20.
- Top KDnuggets tweets, Mar 15-21: Reverse-engineering a $500M AI company in one week; Climate Change Denial and CO2 Emissions - Mar 22, 2017.
Also Hastie, Tibshirani and Friedman - The Elements of Statistical Learning Book PDF; Getting Close and Personal w. #MachineLearning #Algorithms; Open Source Toolkits for Speech Recognition.
- Webinar: Predictive Analytics: Failure to Launch – Apr 13 - Mar 22, 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 Apr 13.
- Deep Learning Summit & Deep Learning in Healthcare Summit in Boston, 25-26 May (KDnuggets Offer) - Mar 22, 2017.
Explore the latest advancements in deep learning and their applications in industry and healthcare at the Deep Learning Summit and Deep Learning in Healthcare Summit in Boston, 25-26 May. Use discount code KDNUGGETS to save 20% off all tickets.
- What Top Firms Ask: 100+ Data Science Interview Questions - Mar 22, 2017.
Check this out: A topic wise collection of 100+ data science interview questions from top companies.
- Why A/B Testers Have The Best Jobs In Tech - Mar 22, 2017.
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.
- What Happened Last Night in Sweden: Data Science vs Fake News - Mar 22, 2017.
During a rally in February, President Trump had these disparaging words about Sweden’s humane immigration policy... but nothing of note actually happened the previous night in Sweden.
- Podcast: The Golden Age of Data Science, featuring Gregory Piatetsky - Mar 21, 2017.
How did a stuffed yellow elephant permanently intertwine itself in history? What is a data scientist? Why is right now the golden age for data science? Data Crunch podcast examines these questions with the help of Gregory Piatetsky-Shapiro and Ryan Henning.
- Kanri Distance Calculator(tm) – patented solution applying power of Big Data to an Individual - Mar 21, 2017.
Kanri combination of patented statistical and process methods provide a powerful ability to evaluate large data, tells users the exact distance from target, and variable contributions for participant. Free trial and 88% KDnuggets discount for the first 100 buyers.
- Octoparse: Free & Automated Web Crawling Tool - Mar 21, 2017.
Octoparse has both a user-friendly, point and click UI for beginner and advanced mode for experts. It also provides Cloud Service with at least 6 cloud servers running your tasks simultaneously. Try it now.
- Data Scientists Might Have It Made For 2017 - Mar 21, 2017.
Companies all over the world have placed a lot of value on getting more insights from big data analytics. That’s not without good reason.
- Statistical Modeling: A Primer - Mar 21, 2017.
It's critical to understand that statistical models are simplified representations of reality and they're all wrong but some of them are useful. So why do we use statistical models?
- Getting Up Close and Personal with Algorithms - Mar 21, 2017.
We've put together a brief summary of the top algorithms used in predictive analysis, which you can see just below. Read to learn more about Linear Regression, Logistic Regression, Decision Trees, Random Forests, Gradient Boosting, and more.
- Chief Data Officer, Financial Services/Insurance, NYC, March 28-29 – KDnuggets Offer - Mar 20, 2017.
These are the MUST attend data events in the FS & Insurance worlds - the combination of our senior attendees, and dedicated, directly relevant industry focus. Use code KD30 for 30% off.
- Analytics 101: Comparing KPIs - Mar 20, 2017.
Different business units in the organisation have different behaviours (e.g. turnover rate) and they can’t be compared with each other. So, how can we tell whether the changes in their behaviour are reasons for concern?
- Top Stories, Mar 13-19: 6 Business Concepts Data Science Unicorns Need; 50 Companies Leading The AI Revolution, Detailed - Mar 20, 2017.
Also 17 More Must-Know Data Science Interview Questions and Answers, Part 3; 7 Types of Data Scientist Job Profiles; Applying Machine Learning To March Madness
- The Most Underutilized Function in SQL - Mar 20, 2017.
Find out why md5() is an SQL function that's used surprisingly often, and find out how -- and why -- you can use it yourself.
- We Didn’t Start The Big Data Fire - Mar 18, 2017.
A parody of Billy Joel's song 'We Didn't Start the Fire,' rewritten to include the accomplishments of various Big Data influencers.
- Climate Change Denial and CO2 Emissions – What is the Connection? - Mar 17, 2017.
We examine the connection between Climate Change Denial and CO2 emissions and find a strong correlation - countries with higher CO2 emissions/capita also have higher percentage of climate skeptics.
- Email Spam Filtering: An Implementation with Python and Scikit-learn - Mar 17, 2017.
This post is an overview of a spam filtering implementation using Python and Scikit-learn. The results of 2 classifiers are contrasted and compared: multinomial Naive Bayes and support vector machines.
- Breaking Data Science Open: How Open Data Science is Eating the World - Mar 17, 2017.
Grab this free book on Open Data Science, a movement that makes the open source tools of data science—data, analytics and computation—work together as a connected ecosystem.
- Proxy Indicators: beware of spurious claims - Mar 16, 2017.
Beware of online and market research studies which can lead to false or spurious claims. We examine several notable examples including Google Street View and Argentina inflation.
- Applying Machine Learning To March Madness - Mar 16, 2017.
March Madness is upon us. But before you get your brackets set, check out this overview of using machine learning to do the heavy lifting for you. A great discussion, and a timely topic.
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50 Companies Leading The AI Revolution, Detailed - Mar 16, 2017.
We detail 50 companies leading the Artificial Intelligence revolution in AD Sales, CRM, Autotech, Business Intelligence and analytics, Commerce, Conversational AI/Bots, Core AI, Cyber-Security, Fintech, Healthcare, IoT, Vision, and other areas. - Analytics, Data Science, Data Management Training May 7-12 in Chicago – save 30% with KDnuggets offer - Mar 16, 2017.
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%?
- Top KDnuggets tweets, Mar 08-14: In-depth introduction to Machine Learning in 15 hours of expert videos - Mar 15, 2017.
Also: #ICYMI The #DataScience Project Playbook; Every Intro to #DataScience Course on the Internet, Ranked; Quick reference to #Python in a single script.
- Make Analytics Pay | Live Immersive Training. - Mar 15, 2017.
Successful analytics starts 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. Washington, DC in April, Live Online in May and Seattle in July.
- 7 Types of Data Scientist Job Profiles - Mar 15, 2017.
There is no one profile for the Data Scientist, but I tried to make a few generic job profiles that can somewhat fit job descriptions of different companies. I think there is way too much variety, but I had to narrow down on a set of profiles. Check out the list.
- 17 More Must-Know Data Science Interview Questions and Answers, Part 3 - Mar 15, 2017.
The third and final part of 17 new must-know Data Science interview questions and answers covers A/B testing, data visualization, Twitter influence evaluation, and Big Data quality.
- Data Science Game, Machine learning competition for students - Mar 14, 2017.
Improve your skills and have fun with other talented students from all around the world. Reg by April 9, online qualification ends May 31, and final phase in Paris, Fall 2017.
- Specialize in Analytics with Villanova Top-Ranked Online MBA - Mar 14, 2017.
Get online MBA from highly ranked Villanova School of Business with specializations in Analytics, Finance, Marketing, or Strategic Management.
- Homebrewed Deep Learning and Do-It-Yourself Robotics - Mar 14, 2017.
Learn how to experiment with embodied robotic cognition with IBM Project Intu, a platform that extends Deep Learning and other cognitive services to new devices with minimum coding.
- Open Source Toolkits for Speech Recognition - Mar 14, 2017.
This article reviews the main options for free speech recognition toolkits that use traditional Hidden Markov Models and n-gram language models.
- Cartoon: What Happens When AI Masters the March Madness - Mar 14, 2017.
March Madness college basketball phenomenon is underway. New KDnuggets Cartoon looks at what happens when AI masters the March Madness.
- Text Analytics: A Primer - Mar 14, 2017.
Marketing scientist Kevin Gray asks Professor Bing Liu to give us a quick snapshot of text analytics in this informative interview.
- Grunion, Query Optimization Tool for Data Science and Big Data - Mar 14, 2017.
Grunion is a patent-pending query optimization, translation, and federation framework built to help bridge the gap between data science and data engineering teams. Read more to request access.
- Interview: UN/WDC “Data For Climate Action” Challenge – What Data Scientists Need to Know - Mar 13, 2017.
We ask UN Global Pulse Director about the 'Data For Climate Action' Challenge, the best sources of climate data, examples of using data for climate mitigation and climate adaptation, and resources for convincing climate change skeptics.
- Top Stories, Mar 6-12: What Makes a Good Data Science Visualization; A Ridiculously Specific Guide to Getting a Data Science Job - Mar 13, 2017.
What makes a good data visualization - a Data Scientist perspective; How to Get a Data Science Job: A Ridiculously Specific Guide; Visualizing Time-Series Change; Working With Numpy Matrices: A Handy First Reference; Beginner’s Guide to Customer Segmentation
- “Data For Climate Action” Challenge – call for research proposals - Mar 13, 2017.
The challenge is to harness data science and big data from the private sector to fight climate change. Data scientists, researchers, and innovators - submit proposals at DataForClimateAction.org by 10 April 2017.
- 6 Business Concepts you need to become a Data Science Unicorn - Mar 13, 2017.
Are you a data science professional and want to advance your career as Data Science Unicorn? Here we provide important business concepts and guidelines required for a data science techie to become a Unicorn.
- Predictive Analytics World Chicago Speaker Highlights - Mar 13, 2017.
Predictive Analytics World comes to Chicago, June 19-22. Yes, it has a stellar agenda, but there are some things you did not know about the wonderful line-up of speakers coming. Read this for more!
- Toward Increased k-means Clustering Efficiency with the Naive Sharding Centroid Initialization Method - Mar 13, 2017.
What if a simple, deterministic approach which did not rely on randomization could be used for centroid initialization? Naive sharding is such a method, and its time-saving and efficient results, though preliminary, are promising.
- Best Data Science Courses from Udemy (only $19 till Mar 31) - Mar 10, 2017.
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.
- The HPI Future SOC Lab offers researchers free access to a powerful Big Data infrastructure - Mar 10, 2017.
The HPI Future SOC (Service-Oriented Computing) Lab is a cooperation of the Hasso Plattner Institute (HPI) and industrial partners, providing free access to a powerful Big Data & Computing infrastructure. It is now accepting project proposals for 2017.
- Working With Numpy Matrices: A Handy First Reference - Mar 10, 2017.
This introductory tutorial does a great job of outlining the most common Numpy array creation and manipulation functionality. A good post to keep handy while taking your first steps in Numpy, or to use as a handy reminder.
- Intelligence Analytics Summit: What You Need to Know Now - Mar 10, 2017.
The Intelligence Analytics Summit takes place May 22-24 in Washington, D.C., where decision makers in the Intelligence community will learn to efficiently analyze and assess data and generate actionable intelligence in real time.
- Earn Your Data Modeling Certificate - Mar 10, 2017.
The Data Modeling Certificate will build your skills and get you started with emerging techniques to model the complex structures in big data and NoSQL databases. Save 30% thru Mar 17 with code KDNEWS.
- Free Online Books Explaining Big Data, Machine Learning, Blockchain and More - Mar 10, 2017.
It has been a challenge to keep up-to-date with new concepts from NoSQL, to machine learning, to Internet of things and blockchain, but Little Bee Books is here with free solutions to helping you do so.
- PAW New York – Speaker Proposal Deadline March 21 - Mar 10, 2017.
Since 2009, Predictive Analytics World has been the leading commercial event for advanced analytics and machine learning, and 2017 is YOUR year to become a speaker. Apply to speak Oct 29-Nov 2 at Predictive Analytics World Events in New York.
- Want to know what to expect from Chief Data Officer, Insurance 2017? - Mar 9, 2017.
This is the premier event for the industry high-level data practitioners to meet and discuss the biggest strategic issues of the day. Use code CDOIN500 for $500 until March 17.
- Google Got a Lot of Data About You - Mar 9, 2017.
This article will dive into six types of data that most big tech companies, and especially Google, gather about consumers.
- Visualizing Time-Series Change - Mar 9, 2017.
When creating time-series line charts, it’s important to consider which of the following messages you would like to communicate: Actual value of units? Change in absolute units? Percent change? Change from a specific point in time?
- Beginner’s Guide to Customer Segmentation - Mar 9, 2017.
At the core of customer segmentation is being able to identify different types of customers and then figure out ways to find more of those individuals so you can... you guessed it, get more customers!
- Top KDnuggets tweets, Mar 01-07: Google Unveils Neural Network with “Superhuman” Ability to Determine the Location of Almost Any Image - Mar 8, 2017.
Also Deep Forest: Towards An Alternative to Deep #NeuralNetworks; An Overview of #Python #DeepLearning Frameworks; The Gentlest Introduction to Tensorflow - Part 2.
- What makes a good data visualization – a Data Scientist perspective - Mar 8, 2017.
We examine principles of good data visualization, including some great and terrible examples, guidelines for human perception, focus on key variables, changes and trends, avoiding chart junk, and more.
- The Challenges of Building a Predictive Churn Model - Mar 8, 2017.
Unlike other data science problems, there is no one method for predicting which customers are likely to churn in the next month. Here we review the most popular approaches.
- Building Regression Models in R using Support Vector Regression - Mar 8, 2017.
The article studies the advantage of Support Vector Regression (SVR) over Simple Linear Regression (SLR) models for predicting real values, using the same basic idea as Support Vector Machines (SVM) use for classification.
- Neuroscience for Data Scientists: Understanding Human Behaviour - Mar 8, 2017.
Neuroscience is very complex and advanced study of brain and people often misuse this term. Here we try to explain neuroscience terminologies and use of data science for such studies.
- K-Means & Other Clustering Algorithms: A Quick Intro with Python - Mar 8, 2017.
In this intro cluster analysis tutorial, we'll check out a few algorithms in Python so you can get a basic understanding of the fundamentals of clustering on a real dataset.
- KDnuggets Free Pass to Strata + Hadoop World London, May 22-25, 2017 - Mar 7, 2017.
Strata + Hadoop World is the leading event on how big data and ubiquitous, real-time computing is shaping the course of business and society. Win KDnuggets free pass to Strata + Hadoop World London.
- XLIVE Data & Analytics Summit, April 4-5, Los Angeles - Mar 7, 2017.
Find out how the Golden State Warriors, Country Music Association, Toronto Film Festival, San Francisco 49ers, Netflix and senior executives in sports, music and live events use analytics to engage, retain and monetize their data. Use code XLIVEKD to save.
- How to Get a Data Science Job: A Ridiculously Specific Guide - Mar 7, 2017.
Job hunting is challenging and sometimes frustrating task and we all experience it in our career. Here we provide a very specific and practical guide to get your dream job in Data Science world.
- A Simple XGBoost Tutorial Using the Iris Dataset - Mar 7, 2017.
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.
- Learn to collect, classify, analyze, and model data - Mar 7, 2017.
The courses offered in the Penn State World Campus 30-credit online Master's in Data Analytics degree could enhance your credentials in the growing field of data analytics.
- Top February Stories: 17 More Must-Know Data Science Interview Questions and Answers; 5 Career Paths in Big Data and Data Science, Explained - Mar 7, 2017.
Also Gartner 2017 Magic Quadrant for Data Science Platforms: gainers and losers; An Overview of Python Deep Learning Frameworks.
- Minitab buys Salford Systems, a leading data mining innovator - Mar 6, 2017.
Latest acquisition adds best-in-class predictive analytics tools to Minitab’s array of data-driven products and services.
- Berkeley Data Strategy and Data Driven Marketing Courses for Business Leaders, May - Mar 6, 2017.
Make your strategy better and more profitable with Data Strategy for Business Leaders program, and leverage consumer data for valuable insights and effective marketing decisions with Data Driven Marketing program.
- Big Data Desperately Needs Transparency - Mar 6, 2017.
If Big Data is to realize its potential, people need to understand what it is capable of, what information is out there and where every piece of data comes from. Without such transparency and understanding, it will be difficult to persuade people to rely on the findings.
- Software Engineering vs Machine Learning Concepts - Mar 6, 2017.
Not all core concepts from software engineering translate into the machine learning universe. Here are some differences I've noticed.
- Top Stories, Feb 27-Mar 5: 7 More Steps to Mastering Machine Learning With Python; An Overview of Python Deep Learning Frameworks - Mar 6, 2017.
7 More Steps to Mastering Machine Learning With Python; An Overview of Python Deep Learning Frameworks; Every Intro to Data Science Course on the Internet, Ranked; The Data Science Project Playbook; Hadoop Is Falling – Why?; Every Intro to Data Science Course on the Internet, Ranked
- Keynotes announced for PAW San Francisco, May 14-18 - Mar 6, 2017.
Join the growing crowd at Predictive Analytics World (May 14-18 in San Francisco) to take advantage of the potential of predictive analytics. Keynote speaker line-up has been announced.
- Top /r/MachineLearning Posts, February: Oxford Deep NLP Course; Data Visualization for Scikit-learn Results - Mar 6, 2017.
Oxford Deep NLP Course; scikit-plot: Data Visualization for Scikit-learn Results; Machine Learning at Berkeley's ML Crash Course: Neural Networks; Predicting parking difficulty with machine learning; TensorFlow 1.0 Release
- 3 minute demo: Data Science Sandbox as a Service - Mar 3, 2017.
Cazena Data Science Sandbox as a Service makes it simple to load data, and run R, Python, SQL and advanced analytics on a high-performance Apache Spark platform. Get a 3-minute demo!
- Upcoming Meetings in Analytics, Big Data, Data Mining, Data Science: March and Beyond - Mar 3, 2017.
Coming soon: Strata + Hadoop World San Jose, Machine Intelligence Summit SF, Predictive Analytics Summit London, SAS Global Forum Orlando, TDWI Accelerate Boston, The Marketing Analytics and Data Science Conference San Francisco, and more.
- Bokeh Cheat Sheet: Data Visualization in Python - Mar 3, 2017.
Bokeh is the Python data visualization library that enables high-performance visual presentation of large datasets in modern web browsers. The package is flexible and offers lots of possibilities to visualize your data in a compelling way, but can be overwhelming.
- Gartner Data Science Platforms – A Deeper Look - Mar 3, 2017.
Thomas Dinsmore critical examination of Gartner 2017 MQ of Data Science Platforms, including vendors who out, in, have big changes, Hadoop and Spark integration, open source software, and what Data Scientists actually use.
- Greed, Fear, Game Theory and Deep Learning - Mar 3, 2017.
The most advanced kind of Deep Learning system will involve multiple neural networks that either cooperate or compete to solve problems. The core problem of a multi-agent approach is how to control its behavior.
- Get more insights from fewer experiments - Mar 3, 2017.
Efficient experimentation can save both time and money in the long term when it helps optimize product or process performance. This webcast shows how a dynamic model can dramatically improve outcomes.
- Every Intro to Data Science Course on the Internet, Ranked - Mar 2, 2017.
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.
- Data Science at Northwestern - Mar 2, 2017.
Online MS in Predictive Analytics prepares students for rewarding careers by training in data science, modeling, business management, communications, and information technology. Summer application deadline is April 15.
- Predictions for Data Science in 2017 - Mar 2, 2017.
Our predictions include: 2017 will be the year of Deep Learning (DL) technology, Artificial General Intelligence is still far away, Software and Hardware Progress will accelerate, and AI will have unexpected socio-political implications.
- Building a Bot to Answer FAQs: Predicting Text Similarity - Mar 2, 2017.
In this post, learn to build a bot to answer frequently asked questions, reducing lag time for more customers and taking the load off of engineers, ensuring they can concentrate on building products!
- Top KDnuggets tweets, Feb 22-28: 50 Companies Leading the #AI Revolution; #AI Nanodegree Program Syllabus - Mar 1, 2017.
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? - Mar 1, 2017.
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.
- Hadoop Is Falling – Why? - Mar 1, 2017.
Three years ago, looking beyond Hadoop was insanity, and there was little else that could come close. Recently, adoption of Hadoop has slowed down considerably. We examine why.
- The Data Science Project Playbook - Mar 1, 2017.
Keep your development team from getting mired in high-complexity, low-return projects by following this practical playbook.
- 7 More Steps to Mastering Machine Learning With Python - Mar 1, 2017.
This post is a follow-up to last year's introductory Python machine learning post, which includes a series of tutorials for extending your knowledge beyond the original.
The Best R Packages for Machine Learning
What is Structural Equation Modeling?
50 Companies Leading The AI Revolution, Detailed
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