All (93) | Courses, Education (2) | Meetings (8) | News, Features (10) | Opinions, Interviews (35) | Top Stories, Tweets (9) | Tutorials, Overviews (23) | Webcasts & Webinars (6)
- How To Debug Your Approach To Data Analysis - Dec 29, 2017.
Seven common biases that influence how we understand, use, and interpret the world around us.
- Lessons from Game of Thrones: Stopping the White Walkers of Data Monetization - Dec 29, 2017.
As I watched the impending battle between the White Walkers and humanity, I couldn’t help but identify a number of lessons that we can learn from Jon Snow’s battle with the leader of the White Walkers… and the power of Valyrian steel!
- Data Science for Laymen: 5 Writers Who Speak Your Language - Dec 28, 2017.
Here are 5 excellent Data Scientists who are also very good at explaining concepts and interacting with you.
- How AI Learns What You’re Willing to Pay - Dec 28, 2017.
Why are we all paying different prices? Is it price "personalization" or price "discrimination"? The answer isn't so simple.
- 15 Minute Guide to Choose Effective Courses for Machine Learning and Data Science - Dec 28, 2017.
Advice for young professionals in non-CS field who wants to learn and contribute to data science/machine learning. Curated from personal experience.
- Top KDnuggets tweets, Dec 20-26: Harvard CS109 #DataScience Course Resources; Computer Vision by Andrew Ng: Lessons Learned - Dec 27, 2017.
Also: Ten years in, nobody has come up with a use for #blockchain - here is what happened; Can I Become a #DataScientist: Research into 1,001 #DataScience Profiles.
- Machine Learning Engineer, Data Scientist – top US emerging jobs - Dec 27, 2017.
Machine Learning Engineer jobs grew almost 10 fold since 2012, and Data Scientist jobs grew 6.5 times. However, finding qualified people to fill such jobs remains difficult.
- Simple Ways Of Working With Medium To Big Data Locally - Dec 27, 2017.
An overview of the installation and implementation of simple techniques for working with large datasets in your machine.
- SQL Window Functions Tutorial for Business Analysis - Dec 27, 2017.
In this SQL window functions tutorial, we will describe how these functions work in general, what is behind their syntax, and show how to answer these questions with pure SQL.
- Can I Become a Data Scientist: Research into 1,001 Data Scientist Profiles - Dec 26, 2017.
Results from a survey include: the average data scientist is a male, with median experience on the job is 2 years. He uses R, Python, and SQL. Read for more details.
- View from Google Assistant: Are we becoming reliant on AI? - Dec 26, 2017.
AI is powering a paradigm shift in human machine interaction and conversational UIs like Alexa, Cortana, Google Assistant, and Siri, have the potential to break free from some key limitations of mobile app.
- Demystifying Data Science - Dec 26, 2017.
Marketing scientist Kevin Gray asks Dr. Randy Bartlett of Blue Sigma Analytics what Data Science really is and how it can help decision-makers.
- Yet Another Day in the Life of a Data Scientist - Dec 25, 2017.
Are you interested in what a data scientist does on a typical day of work? Each data science role may be different, but these four individuals provide insight to help those interested in figuring out what a day in the life of a data scientist actually looks like.
- Is Religion The Next Frontier For AI? - Dec 23, 2017.
Different civilizations have worshiped many different gods and deities. Science, discovery and new technologies have influenced religion in the past, so will our digital age should birth an AI god?
- An Introduction to Monte Carlo Tree Search - Dec 22, 2017.
A great explanation of the concept behind Monte Carlo Tree Search algorithm and a brief example of how it was used at the European Space Agency for planning interplanetary flights.
- Computer Vision by Andrew Ng - 11 Lessons Learned - Dec 22, 2017.
I recently completed Andrew Ng’s computer vision course on Coursera. In this article, I will discuss 11 key lessons that I learned in the course.
- DeepSchool.io: Deep Learning Learning - Dec 22, 2017.
What I truly envision for deep school is that this will build a whole lot of Meetup nodes across the world where people will learn, mentor and network around sharing AI knowledge.
- Top Stories of 2017: 10 Free Must-Read Books for Machine Learning and Data Science; Python overtakes R, becomes the leader in Data Science, Machine Learning platforms - Dec 21, 2017.
Also Top 10 Machine Learning Algorithms for Beginners; 30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets.
- How to Improve Machine Learning Algorithms? Lessons from Andrew Ng, part 2 - Dec 21, 2017.
The second chapter of ML lessons from Ng’s experience. This one will only be talking about Human Level Performance & Avoidable Bias.
- Deep Learning Made Easy with Deep Cognition - Dec 21, 2017.
So normally we do Deep Learning programming, and learning new APIs, some harder than others, some are really easy an expressive like Keras, but how about a visual API to create and deploy Deep Learning solutions with the click of a button? This is the promise of Deep Cognition.
- Why Use Data Analytics to Prevent, Not Just Report - Dec 21, 2017.
The best way to reduce operating and business costs and risks is to prevent them!
- Top KDnuggets tweets, Dec 13-19: The Art of Learning Data Science; Data Science, ML Main Developments, Key Trends - Dec 20, 2017.
The Art of Learning #DataScience; How to Generate FiveThirtyEight Graphs in #Python; #TensorFlow for Short-Term Stocks Prediction; 15 Mathematics MOOCs for #DataScience.
- Win KDnuggets Free Pass to Strata Data Conference San Jose, Mar 5-8, 2018 - Dec 20, 2017.
Cutting-edge science and new business fundamentals intersect and merge at Strata Data Conference. Win KDnuggets Pass - submit your entry by Jan 3, 2018.
- 70 Amazing Free Data Sources You Should Know - Dec 20, 2017.
70 free data sources for 2017 on government, crime, health, financial and economic data, marketing and social media, journalism and media, real estate, company directory and review, and more to start working on your data projects.
- How Much Mathematics Does an IT Engineer Need to Learn to Get Into Data Science? - Dec 20, 2017.
When I started diving deep into these exciting subjects (by self-study), I discovered quickly that I don’t know/only have a rudimentary idea about/ forgot mostly what I studied in my undergraduate study some essential mathematics.
- $5 Data science eBooks and videos from Packt - Dec 19, 2017.
Check Packt $5 sale on every ebook and video, including many great titles on Data Analysis, Machine Learning, Python, Deep Learning, and more - sale runs until Jan 15, 2018.
- Deep Learning by Uber – at PAW Vegas 2018 – Best Price Ends Friday - Dec 19, 2017.
Announcing Deep Learning World: The call-for-speakers for the inaugural Deep Learning World, June 3-7, 2018 in Las Vegas is open. Agenda now posted for Predictive Analytics World, Las Vegas – June 3-7, 2018.
- Industry Predictions: Main AI, Big Data, Data Science Developments in 2017 and Trends for 2018 - Dec 19, 2017.
Here is a treasure trove of analysis and predictions from 17 leading companies in AI, Big Data, Data Science, and Machine Learning: What happened in 2017 and what will 2018 bring?
- Getting Started with TensorFlow: A Machine Learning Tutorial - Dec 19, 2017.
A complete and rigorous introduction to Tensorflow. Code along with this tutorial to get started with hands-on examples.
- A Guide for Customer Retention Analysis with SQL - Dec 19, 2017.
Customer retention curves are essential to any business looking to understand its clients, and will go a long way towards explaining other things like sales figures or the impact of marketing initiatives. They are an easy way to visualize a key interaction between customers and the business.
- New Poll: When will Artificial General Intelligence (AGI) be achieved? - Dec 18, 2017.
When will Artificial General Intelligence (AGI) be achieved, if ever? Please vote in new KDnuggets Poll.
- Accelerating Algorithms: Considerations in Design, Algorithm Choice and Implementation - Dec 18, 2017.
If you are trying to make your algorithms run faster, you may want to consider reviewing some important points on design and implementation.
- Top Stories, Dec 11-17: Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018; Top Data Science and Machine Learning Methods Used in 2017 - Dec 18, 2017.
Also: Another Day in the Life of a Data Scientist; The 10 Deep Learning Methods AI Practitioners Need to Apply; Machine Learning & Artificial Intelligence: Main Developments in 2017 and Key Trends in 2018; Top 10 Machine Learning Algorithms for Beginners
- NIPS 2017 Key Points & Summary Notes - Dec 18, 2017.
Third year Ph.D student David Abel, of Brown University, was in attendance at NIP 2017, and he labouriously compiled and formatted a fantastic 43-page set of notes for the rest of us. Get them here.
- Cartoon: AI and Technology Transforming Christmas? - Dec 16, 2017.
New KDnuggets cartoon looks at how AI and the new technology can transform Christmas.
- Building an Audio Classifier using Deep Neural Networks - Dec 15, 2017.
Using a deep convolutional neural network architecture to classify audio and how to effectively use transfer learning and data-augmentation to improve model accuracy using small datasets.
- Transitioning to Data Science: How to become a data scientist, and how to create a data science team - Dec 15, 2017.
"A good data scientist in my mind is the person that takes the science part in data science very seriously; a person who is able to find problems and solve them using statistics, machine learning, and distributed computing."
- Machine Learning & Artificial Intelligence: Main Developments in 2017 and Key Trends in 2018 - Dec 15, 2017.
As we bid farewell to one year and look to ring in another, KDnuggets has solicited opinions from numerous Machine Learning and AI experts as to the most important developments of 2017 and their 2018 key trend predictions.
- CogX London 2018, The Festival of all things AI, exclusive KDnuggets Discount - Dec 15, 2017.
CogX 2018 (11-12 June, London) will be the most important AI event in Europe. Get early bird tickets for only £599 (reduced from £1,799) with code KDN15 (valid December 2017).
- Best Masters in Data Science and Analytics – Asia and Australia Edition - Dec 14, 2017.
The fourth edition of our comprehensive, unbiased survey on graduate degrees in Data Science and Analytics from around the world.
- Get Network insights in Excel with NodeXL - Dec 14, 2017.
NodeXL, the network overview discovery and exploration add-in for the familiar Microsoft Office Excel (TM) spreadsheet brings network functions within the reach of people who are more comfortable making pie charts than writing code. See what NodeXL finds in KDnuggets network and download NodeXL Pro for your analyses.
- Best Data Science, Machine Learning Courses from Udemy, only $10 until Dec 21 - Dec 14, 2017.
Holiday Dev & IT sale on best courses from Udemy, including Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until Dec 21, 2017.
- Data Science in 30 Minutes: A Conversation with Gregory Piatetsky-Shapiro, President of KDnuggets, Jan 11 - Dec 14, 2017.
KDnuggets founder, Gregory Piatetsky-Shapiro, joins Michael Li, CEO and founder of The Data Incubator, Jan 11 at 2:30 pm PT/ 5:30 pm ET for their monthly webinar series, Data Science in 30 Minutes. Gregory will discuss his career - from Data Mining to Data Science and examine current trends in the field.
- Learn from Google Brain, DeepMind, Facebook & other AI experts, KDnuggets offer - Dec 14, 2017.
RE•WORK interview leading minds in the field to discuss the impact and progressions of AI on business and in society. The complimentary white paper 'Should You Be Using AI In Your Business?' is now available to download. Save 20% on globally renowned AI and Deep Learning summits with code KDNUGGETS.
- How Big Data and New Technologies Are Changing Aging - Dec 14, 2017.
Big data and new technologies are changing the healthcare industry and the aging process as we know it; and for now, that seems to be a move in the right direction.
- Xavier Amatriain’s Machine Learning and Artificial Intelligence Year-end Roundup - Dec 14, 2017.
So much has happened in the world of AI that it is hard to fit in a couple of paragraphs. Here is my attempt.
- How to Generate FiveThirtyEight Graphs in Python - Dec 14, 2017.
In this post, we'll help you. Using Python's matplotlib and pandas, we'll see that it's rather easy to replicate the core parts of any FiveThirtyEight (FTE) visualization.
- 4th AI NEXTCon Conf. Seattle, Jan 17-19, Early bird (50% off) ends soon - Dec 13, 2017.
AI NEXTCon Seattle brings together top technical engineers, practitioners, influential technologists and data scientists to share solutions and practical experiences in machine/deep learning, computer vision, speech recognition and NLP.
- Top KDnuggets tweets, Dec 06-12: Top #DataScience and #MachineLearning Methods Used in 2017; Geoff Hinton Capsule Networks – a new way for machines to see - Dec 13, 2017.
Also The first international #beauty contest decided by #AI #algorithm sparked controversy; 4 Common #Data Fallacies That You Need To Know; Using #DeepLearning to Solve Real World Problems; Best Online Masters in #DataScience and #Analytics.
- Watch the Best of Open Data Science Talks of 2017 for Free - Dec 13, 2017.
Here is a selection of some of the highest rated ODSC talks of 2017 as voted by our attendees. Also check out our series of bi-weekly data science and AI webinars. Attend ODSC East 2018 in person and save 70% with code KDNUGGETS!
- How to Improve Machine Learning Performance? Lessons from Andrew Ng - Dec 13, 2017.
5 useful tips and lessons from Andrew Ng on how to improve your Machine Learning performance, including Orthogonalisation, Single Number Evaluation Metric, and Satisfying and Optimizing Metric.
- The 10 Deep Learning Methods AI Practitioners Need to Apply - Dec 13, 2017.
Deep learning emerged from that decade’s explosive computational growth as a serious contender in the field, winning many important machine learning competitions. The interest has not cooled as of 2017; today, we see deep learning mentioned in every corner of machine learning.
- The Fastest Way to Benefit from Text Analytics, Dec 20 Webinar - Dec 13, 2017.
MeaningCloud Vertical Packs: Voice of the Customer (VoC) and Voice of the Employee (VoE), offer the fastest way to benefit from text analytics.
- Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018 - Dec 12, 2017.
The leading experts in the field on the main Data Science, Machine Learning, Predictive Analytics developments in 2017 and key trends in 2018.
- TensorFlow for Short-Term Stocks Prediction - Dec 12, 2017.
In this post you will see an application of Convolutional Neural Networks to stock market prediction, using a combination of stock prices with sentiment analysis.
- Creating Simple Data Visualizations as an Act of Kindness - Dec 12, 2017.
The field of data visualization is still quite young and evolving rapidly—and tools like the web and VR are continuing to expand the possibilities. So there is a lot of room for exploring new possibilities and creating new formats, as well as many examples of novel and amazing visualizations.
- No More Excuses – 470 Outstanding Women in Analytics - Dec 12, 2017.
In case your network doesn’t include many of the remarkable women you might consider, I have some lists to get you started. Here’s where to find more information and links to profiles of 470 of the industry’s best.
- Top Data Science and Machine Learning Methods Used in 2017 - Dec 11, 2017.
The most used methods are Regression, Clustering, Visualization, Decision Trees/Rules, and Random Forests; Deep Learning is used by only 20% of respondents; we also analyze which methods are most "industrial" and most "academic".
- AnacondaCON – Harness the Power of Data Science, Austin, April 8-11 - Dec 11, 2017.
AnacondaCON is coming to Austin, TX April 8-11. Register now to take advantage of our Early Bird offer of two tickets for the price of one. We’re also offering a bonus 10% off your ticket price if you book a hotel room at the conference site.
- Robust Algorithms for Machine Learning - Dec 11, 2017.
This post mentions some of the advantages of implementing robust, non-parametric methods into our Machine Learning frameworks and models.
- Another Day in the Life of a Data Scientist - Dec 11, 2017.
Are you interested in what a data scientist does on a typical day of work? Each data science role may be different, but these five individuals provide insight to help those interested in figuring out what a day in the life of a data scientist actually looks like.
- Top Stories, Dec 4-10: Using Deep Learning to Solve Real World Problems; Big Data: Main Developments in 2017 and Key Trends in 2018 - Dec 11, 2017.
Also: What is a Bayesian Neural Network?; Today I Built a Neural Network During My Lunch Break with Keras; 4 Common Data Fallacies That You Need To Know; Top 10 Machine Learning Algorithms for Beginners; The 10 Statistical Techniques Data Scientists Need to Master
- Unlock Machine Learning for the New Speed and Scale of Business - Dec 8, 2017.
Learn how Vertica in-database machine learning supports the entire predictive analytics process with, with MPP, SQL execution, R, Python, Java and more - get the whitepaper.
- 5 Tricks When A/B Testing Is Off The Table - Dec 8, 2017.
Sometimes you cannot do A/B testing, but it does not mean we have to fly blind - there is a range of econometric methods that can illuminate the causal relationships at play.
- Today I Built a Neural Network During My Lunch Break with Keras - Dec 8, 2017.
So yesterday someone told me you can build a (deep) neural network in 15 minutes in Keras. Of course, I didn’t believe that at all. So the next day I set out to play with Keras on my own data.
- Top November Stories: The 10 Statistical Techniques Data Scientists Need to Master - Dec 7, 2017.
Also: Best Online Masters in Data Science and Analytics - a comprehensive, unbiased survey; Deep Learning Specialization by Andrew Ng - 21 Lessons Learned; Machine Learning Algorithms: Which One to Choose for Your Problem; Want to know how Deep Learning works? Here's a quick guide
- Unleash a faster Python on your data - Dec 7, 2017.
Get real performance results and download the free Intel® Distribution for Python that includes everything you need for blazing-fast computing, analytics, machine learning, and more. Use Intel Python with existing code, and you’re all set for a significant performance boost.
- Best Masters in Data Science and Analytics – Europe Edition - Dec 7, 2017.
The third part of our comprehensive, unbiased survey of graduate programs in Data Science and Analytics, examining the programs from Europe.
- Bill Inmon on Hearing The Voice Of Your Customer - Dec 7, 2017.
This post explores the importance of hearing your customer, and how to use sentiment analytics and other technologies to achieve this goal and avoid going out of business.
- Managing Machine Learning Workflows with Scikit-learn Pipelines Part 1: A Gentle Introduction - Dec 7, 2017.
Scikit-learn's Pipeline class is designed as a manageable way to apply a series of data transformations followed by the application of an estimator.
- Top KDnuggets tweets, Nov 29 – Dec 5: Teaching the Data Science Process - Dec 6, 2017.
Also An Introduction to Key Data Science Concepts; Using Deep Learning To Extract Knowledge From Job Descriptions; A General Approach to Preprocessing Text Data; keras-text - A Text Classification Library in #Keras.
- Web Scraping for Data Science with Python - Dec 6, 2017.
We take a quick look at how web scraping can be useful in the context of data science projects, eg to construct a social graph based of S&P 500 companies, using Python and Gephi.
- The first data science course with a job guarantee just got even better - Dec 6, 2017.
Apply for Springboard Data Science Career Track, the first online program to guarantee you a job in data science or your money back.
- When reinforcement learning should not be used? - Dec 6, 2017.
While reinforcement learning has achieved many successes, there are situations when it use is problematic. We describe the issues and how to work around them.
- Some Musings on Capsule Networks and DLPaper2Code - Dec 6, 2017.
Only the Godfather of Deep Learning did it again and came up with something brilliant — adding layers inside existing layers instead of adding more layers i.e nested layers.... giving rise to the Capsule Networks!
- AI World coming to Boston, December 11-13 - Dec 5, 2017.
Attend the AI World Expo and meet with 50+ exhibitors and AI Startups. Save $200 off your 2 or 3-day VIP conference pass using priority code AIW200KD. Save $100 off your AI World Expo Pass using priority code AIW100EXPD. Priority codes expire Dec 7.
- Advances in Fraud Detection with Automated Machine Learning - Dec 5, 2017.
Join DataRobot, Dec 13, for a webinar discussion of the current state of machine learning in fraud detection and learn how you can stay one step ahead of those looking to harm your business.
- Multi-objective Optimization for Feature Selection - Dec 5, 2017.
By having the model analyze the important signals, we can focus on the right set of attributes for optimization. As a side effect, less attributes also mean that you can train your models faster, making them less complex and easier to understand.
- Exclusive: Interview with Rich Sutton, the Father of Reinforcement Learning - Dec 5, 2017.
My exclusive interview with Rich Sutton, the Father of Reinforcement Learning, on RL, Machine Learning, Neuroscience, 2nd edition of his book, Deep Learning, Prediction Learning, AlphaGo, Artificial General Intelligence, and more.
- Big Data: Main Developments in 2017 and Key Trends in 2018 - Dec 5, 2017.
As we bid farewell to one year and look to ring in another, KDnuggets has solicited opinions from numerous Big Data experts as to the most important developments of 2017 and their 2018 key trend predictions.
- 4 Common Data Fallacies That You Need To Know - Dec 5, 2017.
In this post you will find a list of common the data fallacies that lead to incorrect conclusions and poor decision-making using data. Here you will find great resources and information so that you can always be reminded of these fallacies when you’re working with data.
- What is a Bayesian Neural Network? - Dec 5, 2017.
BNNs are important in specific settings, especially when we care about uncertainty very much.
- Chatbots Gone Wild - Dec 4, 2017.
How do you build a chatbot your customers will actually want to talk to? At CrowdFlower, we’ve seen the data and the projects that do just that. And we’d like to share what we’ve learned in this free eBook.
- DataRobot: Moving from BI to Machine Learning with Automation - Dec 4, 2017.
Analytics industry expert Jen Underwood shares the fast path to developing world-class predictive modeling capabilities.
- How Do You Build A Great Analytic Culture? - Dec 4, 2017.
We need to create a sense of urgency around exploring and analyzing data. We also need to train and empower individuals to know how. This video covers the need for students to enter the workforce with analytics skills and why we need to give employees permission to fail.
- Graph Analytics Using Big Data - Dec 4, 2017.
An overview and a small tutorial showing how to analyze a dataset using Apache Spark, graphframes, and Java.
- Using Deep Learning to Solve Real World Problems - Dec 4, 2017.
Do you assume that deep learning is only being used for toy problems and in self-learning scenarios? This post includes several firsthand accounts of organizations using deep neural networks to solve real world problems.
- Top Stories, Nov 27-Dec 3: Embracing Vectorization in Data Science; Understanding Deep Convolutional Neural Networks - Dec 4, 2017.
Also: How To Unit Test Machine Learning Code; Evolutionary Algorithms for Feature Selection; A General Approach to Preprocessing Text Data; The 10 Statistical Techniques Data Scientists Need to Master; Deep Learning Specialization by Andrew Ng - 21 Lessons Learned
- Database Bootcamp Webinar Series, Dec 5, 7, 12, 14 - Dec 1, 2017.
The need to be broadly knowledgeable and rapidly understand the existing database ecosystem is growing. Looker broken down and simplified the differentiators of the main database technologies into this series of four, 45-minute webinar sessions.
- Analytic Creation to Production: Bridging The Chasm, Webinar, Dec 7 - Dec 1, 2017.
Understand best practices for optimizing the handoff from analytic team to IT across your business as a core competency, how to create scalable peak model performance, and more.
- Upcoming Meetings in Analytics, Big Data, Data Science, Machine Learning: December 2017 and Beyond - Dec 1, 2017.
Coming soon: H2O World, Mountain View; NIPS 2017, Long Beach; IEEE Big Data Boston; IE8NY17, NYC; Strata, Singapore; Deep Learning Summit, San Francisco; TDWI Las Vegas and many more.
- Exploring Recurrent Neural Networks - Dec 1, 2017.
We explore recurrent neural networks, starting with the basics, using a motivating weather modeling problem, and implement and train an RNN in TensorFlow.
- A General Approach to Preprocessing Text Data - Dec 1, 2017.
Recently we had a look at a framework for textual data science tasks in their totality. Now we focus on putting together a generalized approach to attacking text data preprocessing, regardless of the specific textual data science task you have in mind.