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.
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.
In this post, the author implements a machine learning algorithm from scratch, without the use of a library such as scikit-learn, and instead writes all of the code in order to have a working binary classifier algorithm.
The 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!
"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?
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.
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.
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
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.
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.
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 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.
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.
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.
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.
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.
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.
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 ...
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.
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.
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.
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.
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.
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.
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.
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, 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.
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.
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 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.
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.
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
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.
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.
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.
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.
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.
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.
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
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.
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 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.
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.
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.
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.
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.
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.
Learn about a powerful tree-based machine learning algorithm called gradient boosting, which often outperforms linear regression, Random Forests, and CART.
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.
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
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.
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.
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.
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.
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 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.
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.
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.
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 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.
Also #DeepLearning Research Review: Natural Language Processing; K-Means, Other Clustering Algorithms: A Quick Intro with #Python; Why #DeepLearning Needs Assembler Hackers.
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.
Very useful, updated list of 50+ APIs in machine learning, prediction, text analytics & classification, face recognition, language translation, and more.
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.
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.
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.
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.
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.
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
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.
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.
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
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 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.
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.
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.
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.
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.
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.
Coming soon: AnacondaCON Austin, TDWI Las Vegas, Predictive Analytics Summit San Diego, Big Data Paris, Strata + Hadoop San Jose, Machine Intelligence Summit, and more.
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.
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!
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.
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.
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.
#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.
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.
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?
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.
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.
An Overview of Python Deep Learning Frameworks
The Anatomy of Deep Learning Frameworks
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