2017 Febhttp likes 100
All (103) | Courses, Education (9) | Meetings (13) | News, Features (19) | Opinions, Interviews (27) | Software (5) | Tutorials, Overviews (24) | Webcasts & Webinars (6)
- Cooperative Trust Among Neural Networks Drives Deeper Learning - Feb 28, 2017.
Machine learning developers need to model a growing range of multi-partner scenarios where many learning agents and data sources interact under varying degrees of trustworthiness. This IBM site helps to take next step towards continuous intelligence.
- The Top 5 KPIs to Consider When Measuring Your Campaign - Feb 28, 2017.
When it comes to measuring marketing campaign performance or analysing customers in any business, below top 5 Key Performance Indicators (KPIs) needs to be used to strategically drive the business.
- What I Learned Implementing a Classifier from Scratch in Python - Feb 28, 2017.
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.
- KDnuggets Exclusive: Analytics and Data Science leaders in San Francisco, Apr 3-5 - Feb 28, 2017.
The Marketing Analytics & Data Science Conference is coming to San Francisco April 3-5. Exclusive offer for KDnuggets readers saves you 20% with VIP code MADS17KDN. Reserve your spot today!
- The Human Data Scientist: Safeguarding Your Career in the World of Automation - Feb 28, 2017.
"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?
- Data Science vs Fake News Contest - Feb 27, 2017.
Submit a story that clearly exposes a false claim in the news, using data and visualization. This contest is sponsored by KDnuggets, Data For Democracy, and data.world. Submissions due March 10, 2017.
- An Overview of Python Deep Learning Frameworks - Feb 27, 2017.
Read this concise overview of leading Python deep learning frameworks, including Theano, Lasagne, Blocks, TensorFlow, Keras, MXNet, and PyTorch.
- Learn about modeling methods at PAW Chicago, Jun 19-22 - Feb 27, 2017.
Predictive Analytics World Business is coming to Chicago Jun 19-22, featuring advanced predictive modeling methods. Register by March 10 for super early bird rates.
- Top Stories, Feb 20-26: The Anatomy of Deep Learning Frameworks; Gartner 2017 Magic Quadrant for Data Science Platforms - Feb 27, 2017.
The Anatomy of Deep Learning Frameworks; Gartner 2017 Magic Quadrant for Data Science Platforms; 17 More Must-Know Data Science Interview Questions and Answers; The Gentlest Introduction to Tensorflow - Part 3; The Origins of Big Data
- The 6 Best Data Science Courses from Udemy (only $10 till Feb 28) - Feb 25, 2017.
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.
- Moving from R to Python: The Libraries You Need to Know - Feb 24, 2017.
Are you considering making a move from R to Python? Here are the libraries you need to know, how they stack up to their R contemporaries, and why you should learn them.
- The Anatomy of Deep Learning Frameworks - Feb 24, 2017.
This post sketches out some common principles which would help you better understand deep learning frameworks, and provides a guide on how to implement your own deep learning framework as well.
- Continuum Analytics Webinar, Mar 8: Deliver New Business Value with Open Data Science - Feb 24, 2017.
Continuum Analytics EVP Anaconda Business Michele Chambers and Computational Scientist Ian Stokes-Rees will help you embark on your enterprise's journey to Open Data Science in this webinar.
- Machine 4.0: Making your Factory, Production and Maintenance Data Work - Feb 24, 2017.
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.
- Gartner 2017 Magic Quadrant for Data Science Platforms: gainers and losers - Feb 23, 2017.
We compare Gartner 2017 Magic Quadrant for Data Science Platforms vs its 2016 version and identify notable changes for leaders and challengers, including IBM, SAS, RapidMiner, KNIME, MathWorks, Microsoft, and Quest.
- Machine Learning-driven Firewall - Feb 23, 2017.
Cyber Security is always a hot topic in IT industry and machine learning is making security systems more stronger. Here, a particular use case of machine learning in cyber security is explained in detail.
- What is a Support Vector Machine, and Why Would I Use it? - Feb 23, 2017.
Support Vector Machine has become an extremely popular algorithm. In this post I try to give a simple explanation for how it works and give a few examples using the the Python Scikits libraries.
- Stanford Webinar, Mar 9: When big data seems too small - Feb 23, 2017.
On March 9, Stanford’s Dr. Gregory Valiant discusses the difficulties of and solutions for making accurate inferences in this challenging regime, in which the empirical distribution of the available data is misleading.
- Top KDnuggets tweets, Feb 15-21: curated list of top #DeepLearning papers; Hill for the #DataScientist: An xkcd Story - Feb 22, 2017.
Sir Austin Bradford Hill for the #DataScientist: An xkcd Story; Attacking #machinelearning with adversarial examples; Hans Rosling: An Appreciation - Great Data Scientist, Great Human #RIP; The Most Popular Language For #MachineLearning and #DataScience Is ...
- Introduction to Correlation - Feb 22, 2017.
Correlation is one of the most widely used (and widely misunderstood) statistical concepts. We provide the definitions and intuition behind several types of correlation and illustrate how to calculate correlation using the Python pandas library.
- The Gentlest Introduction to Tensorflow – Part 4 - Feb 22, 2017.
This post is the fourth entry in a series dedicated to introducing newcomers to TensorFlow in the gentlest possible manner, and focuses on logistic regression for classifying the digits of 0-9.
- 17 More Must-Know Data Science Interview Questions and Answers, Part 2 - Feb 22, 2017.
The second part of 17 new must-know Data Science Interview questions and answers covers overfitting, ensemble methods, feature selection, ground truth in unsupervised learning, the curse of dimensionality, and parallel algorithms.
- Short course: Statistical Learning and Data Mining IV, Palo Alto, Apr 6-7 - Feb 21, 2017.
This new two-day course gives a detailed and modern overview of statistical models used by data scientists for prediction and inference, with emphasis on tools useful for tackling modern-day data analysis problems.
- Chief Analytics Officer, Spring: May 2-4 2017, Scottsdale, AZ – KDnuggets Offer - Feb 21, 2017.
Over 85 attendees confirmed for another excellent conference with Big Data and Analytics strategists from across the USA. Use code KDSPR20 to save.
- The Gentlest Introduction to Tensorflow – Part 3 - Feb 21, 2017.
This post is the third entry in a series dedicated to introducing newcomers to TensorFlow in the gentlest possible manner. This entry progresses to multi-feature linear regression.
- Data Scientists Strongly Oppose Trump Immigration Ban - Feb 21, 2017.
Latest poll of nearly 1000 analytics professionals and data scientists who read KDnuggets shows that 75% worldwide and 77% in the US oppose Trump Immigration Ban. The poll results reveal sharp polarization, with strong views prevailing on both sides.
- The Origins of Big Data - Feb 21, 2017.
Big Data has truly come of age in 2013 when OED introduced the term “Big Data” for the first time. But when was the term Big Data first used and Why? Here are the results of our investigation.
- Stacking Models for Improved Predictions - Feb 21, 2017.
This post presents an example of regression model stacking, and proceeds by using XGBoost, Neural Networks, and Support Vector Regression to predict house prices.
- AI & Machine Learning World, London, 13-15 June 2017 – KDnuggets Offer - Feb 21, 2017.
AI & Machine Learning World, part of London Tech Week, brings together global thought leaders who have driven the adoption of machine learning within global enterprises. Use code TEC6245KD to save.
- Predictive Analytics World for Business, June 19-22, Chicago - Feb 20, 2017.
Join your peers at Predictive Analytics World for Business and tap the potential of predictive analytics to optimize business. You will grasp it, own it, and put it to use by learning from the best of the best.
- Causation or Correlation: Explaining Hill Criteria using xkcd - Feb 20, 2017.
This is an attempt to explain Hill’s criteria using xkcd comics, both because it seemed fun, and also to motivate causal inference instructures to have some variety in which xkcd comic they include in lectures.
- Creativity is Crucial in Data Science - Feb 20, 2017.
Creativity and Innovation are integral to Data Science and going forward in the world of AI, those are the things that will give edge to the humans over the machines.
- Data for Democracy: The First Two Months of D4D - Feb 20, 2017.
Let’s hear about how Data Science is used for democracy and well being of human societies by Data for Democracy organisation.
- Deep Learning, Artificial Intuition and the Quest for AGI - Feb 20, 2017.
Deep Learning systems exhibit behavior that appears biological despite not being based on biological material. It so happens that humanity has luckily stumbled upon Artificial Intuition in the form of Deep Learning.
- Top Stories, Feb 13-19: 17 More Must-Know Data Science Interview Questions and Answers • Removing Outliers Using Standard Deviation in Python - Feb 20, 2017.
17 More Must-Know Data Science Interview Questions and Answers • Removing Outliers Using Standard Deviation in Python • Natural Language Processing Key Terms, Explained • KDnuggets Top Blogger: An Interview with Brandon Rohrer
- Webinar: Athena Health “Unbreaks” Health Care by Modernizing their Data Stack, Feb 28 - Feb 17, 2017.
With a new Snowflake data warehouse and Looker data platform on top, data analysts at athenahealth are delivering data to more people, and improving patient experience in the US healthcare system. Register and learn how.
- Reducing Science-related Stress - Feb 17, 2017.
The author presents a list of things learned through hard experience to help him with his own imposter syndrome, and help him to feel less stressed out about science.
- Machine Intelligence Summit & Machine Intelligence in Autonomous Vehicles Summit in San Francisco, 23-24 March (KDnuggets Offer) - Feb 17, 2017.
Explore the new smart machines and self-controlled vehicles from the world's leading innovators across all industries at the Machine Intelligence and Autonomous Vehicles summits. Use code KDNUGGETS to save.
- Why Go Long on Artificial Intelligence? - Feb 17, 2017.
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.
- Gain the Skills for the Hottest Careers in Analytics - Feb 17, 2017.
Get 25% off All Online Courses* from TDWI, the Industry's Best BI & Analytics Online Education! Use special KDnuggets discount code DATALOVE by Fri 3/3 @ Midnight PT.
- Introduction to Natural Language Processing, Part 1: Lexical Units - Feb 16, 2017.
This series explores core concepts of natural language processing, starting with an introduction to the field and explaining how to identify lexical units as a part of data preprocessing.
- Removing Outliers Using Standard Deviation in Python - Feb 16, 2017.
Standard Deviation is one of the most underrated statistical tools out there. It’s an extremely useful metric that most people know how to calculate but very few know how to use effectively.
- Apache Arrow and Apache Parquet: Why We Needed Different Projects for Columnar Data, On Disk and In-Memory - Feb 16, 2017.
Apache Parquet and Apache Arrow both focus on improving performance and efficiency of data analytics. These two projects optimize performance for on disk and in-memory processing
- Webinar: The Data Science Sandbox as a Service, March 8 - Feb 16, 2017.
The platform includes storage, data movers, processing and embedded analytics tools including RStudio Server Pro - see it in action at this expert webinar and live demo.
- Natural Language Processing Key Terms, Explained - Feb 16, 2017.
This post provides a concise overview of 18 natural language processing terms, intended as an entry point for the beginner looking for some orientation on the topic.
- Spark Streaming Innovation Contest - Feb 15, 2017.
Build a Spark application on StreamAnalytix, a real-time streaming analytics platform and win $10K. Register by March 31, 2017.
- Top KDnuggets tweets, Feb 08-14: 5 Free Courses for Getting Started in AI; Deep Learning for NLP at Oxford, course materials - Feb 15, 2017.
5 Free Courses for Getting Started in #AI; Python #DataScience tutorial: Making #Python Speak #SQL with pandasql; Course materials: #DeepLearning for Natural Language Processing at Oxford; Resources for Learning AI, courtesy of McGill #AI Society.
- 17 More Must-Know Data Science Interview Questions and Answers - Feb 15, 2017.
17 new must-know Data Science Interview questions and answers include lessons from failure to predict 2016 US Presidential election and Super Bowl LI comeback, understanding bias and variance, why fewer predictors might be better, and how to make a model more robust to outliers.
- Surprising Popularity: A Solution to the Crowd Wisdom Problem - Feb 15, 2017.
This is an overview of a recent proposed method for solving the crowd wisdom problem: select the answer that is more popular than people predict. Research shows that this principle yields the best answer under reasonable assumptions about voter behavior.
- The Internet of Things vs. Related Concepts and Terms - Feb 14, 2017.
This post attempts to provide some insights on the differences between IoT and the related technologies of M2M, CPS, and WoT, based on literature texts, but also the author's experience from projects and application deployments.
- Web Scraping for Dataset Curation, Part 2: Tidying Craft Beer Data - Feb 14, 2017.
This is the second part in a 2 part series on curating data from the web. The first part focused on web scraping, while this post details the process of tidying scraped data after the fact.
- Boost your career with Stanford data mining courses - Feb 14, 2017.
Be a member of an on-campus graduate class, watch lectures and complete assignments online, and digitally interact with your classmates. Stanford data mining courses: Flexibility. World-Class Teaching and Research. Stanford Credential.
- Cartoon: Perfect Valentine’s Dates Found With Data Analysis - Feb 14, 2017.
New KDnuggets Cartoon shows one example where perfect Valentine's Dates can be found with scientific data analysis.
- KDnuggets Top Blogs and Bloggers in January 2017 - Feb 13, 2017.
We recognize our top blogs and bloggers in January, who wrote about Machine Learning, CyberSecurity, IoT, Pandas Cheat Sheet, Data Scientist - best job in America, Time Series, Deep Learning, and more.
- Webinar: Improve Your Regression with CART and Gradient Boosting, Feb 16 - Feb 13, 2017.
Learn about a powerful tree-based machine learning algorithm called gradient boosting, which often outperforms linear regression, Random Forests, and CART.
- Career Advice for Analytics & Data Science Professionals - Feb 13, 2017.
In our experience working with many quantitative professionals over the years, the two main areas that contribute to long-term career growth are networking and continuous learning. Here is specific advice on how to do this and tips for Continuous Learning.
- Top Stories, Feb 6-12: 5 Career Paths in Big Data and Data Science, Explained • So What is Big Data? - Feb 13, 2017.
5 Career Paths in Big Data and Data Science, Explained • So What is Big Data? • Making Python Speak SQL with pandasql • 52 Useful Machine Learning & Prediction APIs, updated • Deep Learning Research Review: NLP
- Web Scraping for Dataset Curation, Part 1: Collecting Craft Beer Data - Feb 13, 2017.
This post is the first in a 2 part series on scraping and cleaning data from the web using Python. This first part is concerned with the scraping aspect, while the second part while focus on the cleaning. A concrete example is presented.
- KDnuggets Exclusive: London Data Festival 2017, Mar 30 & 31 - Feb 13, 2017.
The London Data Festival takes place March 30 & 31, with KDnuggets readers getting £200 off all two-day passes with code KD200.
- KDnuggets Top Blogger: An Interview with Brandon Rohrer, Top Data Scientist - Feb 13, 2017.
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.
- Chief Analytics Officer Spring, Scottsdale, AZ, May 2-4 2017 – KDnuggets Offer - Feb 10, 2017.
CAO Spring explores strategies and approaches for deriving real actionable insights through tangible real-world case studies and topic highlights. Save 20% with promo code KDSPR20.
- The Data Science of NYC Taxi Trips: An Analysis & Visualization - Feb 10, 2017.
This post outlines using Google BigQuery for an analysis of NYC Taxi Trips in the cloud, presenting the analysis and visualization in Tableau Public for readers to interact with.
- Getting Real World Results From Agile Data Science Teams - Feb 10, 2017.
In this post, I’ll look at the practical ingredients of managing agile data science. By using agile data science methods, we help data teams do fast and directed work, and manage the inherent uncertainty of data science and application development.
- AI is not at all like Mobile/Cloud/SaaS - Feb 10, 2017.
AI is a hard problem and will take much longer to solve in any scope. The sudden uptick in interest may revert back to normal, but the cycle of work will be longer, much more diverse, and interesting than Mobile/Cloud/SaaS.
- Making sense of text analytics - Feb 9, 2017.
Gain a deep understanding of tools and techniques of text analytics and sentiment mining from statistical and NLP perspectives. Next course is in NYC, April 27-28.
- Automatically Segmenting Data With Clustering - Feb 9, 2017.
In this post, we’ll walk through one such algorithm called K-Means Clustering, how to measure its efficacy, and how to choose the sets of segments you generate.
- So What is Big Data? - Feb 9, 2017.
We examine what experts say about Big Data – is it like teenage sex? Is it more than just a large and complex collection of data? And how many Vs are there?
- What Americans Really Think About Trump’s Immigration Ban and Why - Feb 9, 2017.
What do Americans really think of the President's immigration ban? Text analysis of what people say in their own words reveals more than multiple-choice surveys.
- New Poll: Do you support Trump Immigration Ban? - Feb 9, 2017.
Express your opinion about Trump Immigration ban and find out what does Google Autocomplete offers when you search for "Trump Immigration".
- Top KDnuggets tweets, Feb 01-07: Learning to Learn by Gradient Descent by Gradient Descent - Feb 8, 2017.
Also #DeepLearning Research Review: Natural Language Processing; K-Means, Other Clustering Algorithms: A Quick Intro with #Python; Why #DeepLearning Needs Assembler Hackers.
- Quickly tackle unstructured text data - Feb 8, 2017.
Learn about the new advanced text exploration capabilities available that let you quickly extract insights from text-based data.
- Overcoming the Last Hurdle in the Quest for the “Holy Grail” of Marketing - Feb 8, 2017.
A consumer’s complete digital footprint is a messy, fuzzy, dynamic picture. But data science is helping make digital identity as stable as physical identity – the last hurdle in the quest for the "holy grail" of marketing.
- 50+ Useful Machine Learning & Prediction APIs, updated - Feb 8, 2017.
Very useful, updated list of 50+ APIs in machine learning, prediction, text analytics & classification, face recognition, language translation, and more.
- Making Python Speak SQL with pandasql - Feb 8, 2017.
Want to wrangle Pandas data like you would SQL using Python? This post serves as an introduction to pandasql, and details how to get it up and running inside of Rodeo.
- Forrester Study: Companies Using Data Science Platforms Are Surpassing The Competition - Feb 8, 2017.
Companies that regularly exceed shareholder expectations have something in common: 88% of them use a fully functional platform to do data science work. Get the white paper from Forrester to learn more.
- Want a Data Science Job? - Feb 7, 2017.
Apply to Springboard Data Science Career Track - the first online bootcamp to guarantee you a job in data science or your money back. Hundreds of graduates have mastered data science skills, and have been hired at top companies.
- Top January Stories: The Most Popular Language For Machine Learning and Data Science Is … - Feb 7, 2017.
Also 5 Machine Learning Projects You Can No Longer Overlook; Big Data and the Internet of Things don't make business smarter, Analytics and Data Science do.
- Turbo Charge Agile Processes with Deep Learning - Feb 7, 2017.
The key to leveraging Deep Learning, or more broadly AI, in the workplace is to understand where it fits within an agile development environment.
- 5 Decisive Technology Trends which will Make or Break the Manufacturing Momentum in 2017 - Feb 7, 2017.
Manufacturing contributes to 16% of the global GDP and the Internet of Things (IoT ) is on track to connect >28 billion things. What happens when these massive forces collide? We review 5 game-changing technology catalysts.
- Top /r/MachineLearning Posts, January: TensorFlow Updates; AlphaGo in the Wild; Self-Driving Mario Kart - Feb 7, 2017.
TensorFlow 1.0.0-alpha; Unknown bot repeatedly beats top Go players online - so far it's undefeated; TensorKart: self-driving MarioKart with TensorFlow; GTA V integration into Universe is now open-source; Keras will be added to core TensorFlow at Google
- How do you model that? - Feb 6, 2017.
Learn how to identify complex and dynamic patterns within your multilevel data and how to build multilevel linear models (MLM) and multilevel generalized linear models (MGLM). NYC in March, Online in May, SF in July.
- How to get your first job in Data Science? - Feb 6, 2017.
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.
- Top Stories, Jan 30-Feb 5: Deep Learning Research Review: Natural Language Processing; Data Scientist – best job in America, again - Feb 6, 2017.
Deep Learning Research Review: Natural Language Processing; Data Scientist – best job in America, again; 5 Free Courses for Getting Started in Artificial Intelligence; Top R Packages for Machine Learning
- Regression Analysis: A Primer - Feb 6, 2017.
Despite the popularity of Regression, it is also misunderstood. Why? The answer might surprise you: There is no such thing as Regression. Rather, there are a large number of statistical methods that are called Regression, all of which are based on a shared statistical foundation.
- Strata + Hadoop World, May 22-25, London, UK – KDnuggets Offer - Feb 6, 2017.
Strata + Hadoop World is a rich learning experience at the intersection of data science and business. Get best price by Feb 24 and save extra with code PCKDNG.
- 5 Career Paths in Big Data and Data Science, Explained - Feb 6, 2017.
Sexiest job... massive shortage... blah blah blah. Are you looking to get a real handle on the career paths available in "Data Science" and "Big Data?" Read this article for insight on where to look to sharpen the required entry-level skills.
- Data for Humanity – Open Letter - Feb 4, 2017.
The letter, signed by many leading computer experts, calls for 5 ethical principles when using data: Do no harm, help create peaceful coexistence, help vulnerable people, preserve and improve natural environment, and help create a fair world without discrimination.
- Provalis Research Releases an Enhanced Qualitative Data Analysis Freeware - Feb 3, 2017.
Upgraded version of the qualitative analysis freeware QDA Miner Lite now includes a document overview, tree-grid display, image rotation and resizing, importing from PowerPoint and more.
- 3 practical thoughts on why deep learning performs so well - Feb 3, 2017.
Why does Deep Learning perform better than other machine learning methods? We offer 3 reasons: integration of integration of feature extraction within the training process, collection of very large data sets, and technology development.
- Top R Packages for Machine Learning - Feb 3, 2017.
What are the most popular ML packages? Let's look at a ranking based on package downloads and social website activity.
- Learn Tools, Tricks & Techniques of Data Science in Boston, Apr 3-5 - Feb 3, 2017.
TDWI will present a 3-day Accelerate Conference on April 3–5, 2017 in Boston, with sessions on core data science skills including R, Python, and Spark. KDnuggets members save 20% through Feb 10, 2017 with priority code KD20.
- 116 Upcoming Meetings in Analytics, Big Data, Data Mining, Data Science: February and Beyond - Feb 3, 2017.
Coming soon: AnacondaCON Austin, TDWI Las Vegas, Predictive Analytics Summit San Diego, Big Data Paris, Strata + Hadoop San Jose, Machine Intelligence Summit, and more.
- Top arXiv Papers, January: ConvNets Advances, Wide Instead of Deep, Adversarial Networks Win, Learning to Reinforcement Learn - Feb 3, 2017.
Check out the top arXiv Papers from January, covering convolutional neural network advances, why wide may trump deep, generative adversarial networks, learning to reinforcement learn, and more.
- Learning to Learn by Gradient Descent by Gradient Descent - Feb 2, 2017.
What if instead of hand designing an optimising algorithm (function) we learn it instead? That way, by training on the class of problems we’re interested in solving, we can learn an optimum optimiser for the class!
- An ode to the analytics grease monkeys - Feb 2, 2017.
Analytics is not one time job. It needs to be automated, deployed and improved for future business analytics requirements. Here an IBM expert discusses about development & deployment of analytics assets and capabilities of it.
- Identifying Variables That Might Be Better Predictors - Feb 2, 2017.
This blog serves to expand on the approach that the data science team uses to identify (and quantify) which variables and metrics are better predictors of performance.
- Online MS in Data Science and in Business Analytics programs from Merrimack College - Feb 2, 2017.
Higher salaries, an exploding job market, and two Master's programs from Merrimack College mean this is the year for data science... and for you!
- Marketing Metrics and Analytics Summit, New York, Apr 26-27 – KDnuggets Offer - Feb 2, 2017.
Designed to be at the intersection of marketing, data science, and analytics, this summit will discuss common challenges and pain points, discover new cutting-edge technology tools and solutions, and to connect and network. Use discount code KDN15 to save.
- Top KDnuggets tweets, Jan 25-31: Python implementations of Andrew Ng #MachineLearning MOOC exercises - Feb 1, 2017.
#Python implementations of Andrew Ng #MachineLearning MOOC exercises; This repository contains the entire #Python #DataScience Handbook; What are the best #visualizations of #MachineLearning algorithms? Learn #TensorFlow and #DeepLearning, without a PhD.
- Fixing Deployment and Iteration Problems in CRISP-DM - Feb 1, 2017.
Many analytic models are not deployed effectively into production while others are not maintained or updated. Applying decision modeling and decision management technology within CRISP-DM addresses this.
- Is Deep Learning the Silver Bullet? - Feb 1, 2017.
With nearly every every smart young computer scientist planning to work on deep learning, are there really still artificial intelligence researchers working on other techniques? Is deep learning the AI silver bullet?
- 5 Free Courses for Getting Started in Artificial Intelligence - Feb 1, 2017.
A carefully-curated list of 5 free collections of university course material to help you better understand the various aspects of what artificial intelligence and skills necessary for moving forward in the field.
- Insurance Nexus USA (Chicago, Mar 14-15) – Build a Resilient Core: Analytics, Technology, Culture: KDnuggets Offer - Feb 1, 2017.
The Insurance Nexus USA Summit (March 14-15, Chicago) is the world’s only venue helping insurers to build a resilient inner core. Check out the attendee list, agenda topics and speakers and get special KDnuggets discount.