How to Make Manual Predictions for ARIMA Models with Python

Feb 7 1:00pm Blog – Machine Learning Mastery
The autoregression integrated moving average model or ARIMA model can seem intimidating to beginners. A good way to pull back the curtain in the method is to to use a trained model to make predictions manually. This demonstrates that ARIMA is a linear regression model at its core. Making manual predictions with a fit ARIMA […] The post How to Make Manual Predictions for ARIMA Models with Python appeared first on Machine Learning Mastery.
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16

TIBCOs Accelerator for Financial Crime Was Just Published and Its Not a Black Box

Feb 7 8:19am The TIBCO Blog
The final piece of the puzzle has just been published. First, it was my white paper called “Busting Financial Crime with TIBCO“, which explains the hows and the whys of our end-to-end approach to this horizontal issues. In particular, currently common enterprise crime fighting strategies suffer from two main problems:... Read More →...
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13

A Gentle Introduction to Autocorrelation and Partial Autocorrelation

Feb 5 1:00pm Blog – Machine Learning Mastery
Autocorrelation and partial autocorrelation plots are heavily used in time series analysis and forecasting. These are plots that graphically summarize the strength of a relationship with an observation in a time series with observations at prior time steps. The difference between autocorrelation and partial autocorrelation can be difficult and confusing for beginners to time series […] The post A Gentle Introduction to Autocorrelation and Partial Autocorrelation appeared first on Machine Learning Mastery.
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19

Tears In The Rain: A Spectacular SciFi Blade Runner Fanfilm

Feb 4 4:26pm Singularity Weblog
Tears In The Rain is a short film set in the world of Philip K. Dick’s novel Do Androids Dream of Electric Sheep? (1968) as well as the motion picture Blade Runner (1982). Synopsis: In a dystopian Los Angeles future, replicants or genetically engineered humanoids are created to work forced […]...
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Tears In The Rain: A Spectacular Short SciFi Blade Runner Fanfilm

Feb 4 4:26pm Singularity Weblog
Tears In The Rain is a short film set in the world of Philip K. Dick’s novel Do Androids Dream of Electric Sheep? (1968) as well as the motion picture Blade Runner (1982). Synopsis: In a dystopian Los Angeles future, replicants or genetically engineered humanoids are created to work forced […]...
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How to Make a Digital Newsroom Dashboard with TIBCO Simplr

Feb 3 8:50am The TIBCO Blog
Our Public Relations team has many channels of data to analyze and use for reporting, but they were unconnected, and there was no one place where they could go to access all the information they needed. As as result, the team spent a lot of time gathering and distributing the... Read More →...
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How to Work Through a Time Series Forecast Project

Feb 2 1:00pm Blog – Machine Learning Mastery
A time series forecast process is a set of steps or a recipe that leads you from defining your problem through to the outcome of having a time series forecast model or set of predictions. In this post, you will discover time series forecast processes that you can use to guide you through your forecast […] The post How to Work Through a Time Series Forecast Project appeared first on Machine Learning Mastery.
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28

STATS4TRADE Unlocks the Power of Machine Learning for Investors

Feb 2 10:54am The Official Blog of BigML.com
The investment industry is an extremely competitive one, where fund managers work hard to demonstrate a strong track record that beats their respective benchmarks in order to be able to justify their fees and to partake in the profits from their assets under management. For retail investors, the recent years have been characterized by a significant shift towards passive investing […]...
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TIBCO 2017 Trailblazer Customer Award Nominations Open

Feb 2 8:28am The TIBCO Blog
Nominations are open for the 2017 TIBCO Trailblazer Awards! Nominate your company to showcase how your use of technology transformed IT into a strategic differentiator that fuels growth and outstanding customer experience. This year, TIBCO will honor three winners at each of three global TIBCO NOW events. Submit your nomination for... Read More →...
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Recipes to Boost Employee Engagement #3: Measuring Success

Feb 1 8:40am The TIBCO Blog
In this next blog in our series of simple recipes for boosting employee engagement for your enterprise social networking (ESN), let’s look at how to prepare for and measure success. While the best practices here are often thought of as applying to early rollouts, they can just as easily be... Read More →...
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Why the Future adds 0 and what Conversations with the Future is about

Jan 31 4:43pm Singularity Weblog
This is the introduction of my book Conversations with the Future. If you like it, you can buy the book on Amazon here: http://amzn.to/2kcseK9 “If someone needs directions, don’t give them a globe. It’ll merely waste their time. But if someone needs to understand the way things are, don’t give them […]...
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Time Series Forecasting Performance Measures With Python

Jan 31 1:00pm Blog – Machine Learning Mastery
Time series prediction performance measures provide a summary of the skill and capability of the forecast model that made the predictions. There are many different performance measures to choose from. It can be confusing to know which measure to use and how to interpret the results. In this tutorial, you will discover performance measures for […] The post Time Series Forecasting Performance Measures With Python appeared first on Machine Learning Mastery.
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27

Doubling Efficiency with Digital Twins

Jan 30 8:18am The TIBCO Blog
As first published by Internet of Business: https://internetofbusiness.com/tibco-double-efficiency-digital-twins/ In five years’ time, it’s quite likely that devices will run much of the world through their own private Internet of Things. There could be billions of them and they’ll all have their own virtual “mini-me.” But there’s no need to worry and... Read More →...
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How to Decompose Time Series Data into Trend and Seasonality

Jan 29 1:00pm Blog – Machine Learning Mastery
Time series decomposition involves thinking of a series as a combination of level, trend, seasonality, and noise components. Decomposition provides a useful abstract model for thinking about time series generally and for better understanding problems during time series analysis and forecasting. In this tutorial, you will discover time series decomposition and how to automatically split a […] The post How to Decompose Time Series Data into Trend and Seasonality appeared first on Machine Learning Mastery.
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18

How to Make Predictions for Time Series Forecasting with Python

Jan 26 1:00pm Blog – Machine Learning Mastery
Selecting a time series forecasting model is just the beginning. Using the chosen model in practice can pose challenges, including data transformations and storing the model parameters on disk. In this tutorial, you will discover how to finalize a time series forecasting model and use it to make predictions in Python. After completing this tutorial, […] The post How to Make Predictions for Time Series Forecasting with Python appeared first on Machine Learning Mastery.
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13

How and Why Customers Use TIBCO Technology

Jan 26 8:25am The TIBCO Blog
Our new Customers website shows off how more than 75 companies across every major industry are using TIBCO technology to improve business results and customer satisfaction. The site includes quotes, videos, and stories that describe the most pressing challenges faced by organizations around the globe, how and why they decided on... Read More →...
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17

Harvards soft exoskeleton

Jan 25 7:31pm Robotics Zeitgeist
It was 2009-2010 when exoskeletons exited science fiction and entered the mainstream as several companies and research labs revealed their state-of-the-art designs (see Rex Bionics, Lockheed Martin, and Honda’s exoskeletons). These wearable robots that assist a person to walk promise improved mobility for many people in need such as the handicapped and the elderly. Exoskeletons… Read More »...
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19

Explore the New TIBCO.com Web Experience!

Jan 25 3:00pm The TIBCO Blog
Have you visited TIBCO.com lately? If you have, you’ll notice that we made some major changes. If not, you’re in for a surprise. The TIBCO website has been completely revamped with our users, customers, and partners in mind. Hurry over to explore the new web experience today, and you’ll see... Read More →...
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How to Use Power Transforms for Time Series Forecast Data with Python

Jan 24 1:00pm Blog – Machine Learning Mastery
Data transforms are intended to remove noise and improve the signal in time series forecasting. It can be very difficult to select a good, or even best, transform for a given prediction problem. There are many transforms to choose from and each has a different mathematical intuition. In this tutorial, you will discover how to […] The post How to Use Power Transforms for Time Series Forecast Data with Python appeared first on Machine Learning Mastery.
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23

TIBCO NOW 2017 Goes Global, Driving Digital Smarter

Jan 24 8:52am The TIBCO Blog
TIBCO is thrilled to announce the upcoming TIBCO NOW conference series taking place in Singapore’s Marina Bay Sands Hotel March 27-28, 2017, Berlin’s Estrel Hotel and Conference Center June 6-7, 2017, and San Diego’s Hilton San Diego Bay Front Hotel October 25-26, 2017. Elevating discussion topics from TIBO NOW 2016, this year’s... Read More →...
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15

Machine Learning Automation: Beware of the Hype!

Jan 23 3:23pm The Official Blog of BigML.com
There’s a lot of buzz lately around “Automating Machine Learning”.  The general idea here is that the work done by a Machine Learning engineer can be automated, thus freeing potential users from the tyranny of needing to have specific expertise. Presumably, the ultimate goal of such automations is to make Machine Learning accessible to more people.  […]...
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How to Reframe Your Time Series Forecasting Problem

Jan 22 1:00pm Blog – Machine Learning Mastery
You do not have to model your time series forecast problem as-is. There are many ways to reframe your forecast problem that can both simplify the prediction problem and potentially expose more or different information to be modeled. A reframing can ultimately result in better and/or more robust forecasts. In this tutorial, you will discover […] The post How to Reframe Your Time Series Forecasting Problem appeared first on Machine Learning Mastery.
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10

Cloud-Native Integration Microservices with Netflix Hystrix Circuit Breaker and TIBCO BWCE

Jan 20 8:00am The TIBCO Blog
Cloud-native microservices offer many benefits. You can develop, test, and deploy and maintain independent lightweight services. You can easily combine various technologies, including programming languages such as Java or Go, and tools like integration middleware. However, as you do not build monoliths anymore, ”that complexity has moved and […] increased... Read More →...
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A Gentle Introduction to the Random Walk for Times Series Forecasting with Python

Jan 19 1:00pm Blog – Machine Learning Mastery
How do you know your time series problem is predictable? This is a difficult question with time series forecasting. There is a tool called a random walk that can help you understand the predictability of your time series forecast problem. In this tutorial, you will discover the random walk and its properties in Python. After […] The post A Gentle Introduction to the Random Walk for Times Series Forecasting with Python appeared first on Machine Learning Mastery.
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inQuba and Whispir on their Success with TIBCO

Jan 19 8:30am The TIBCO Blog
inQuba delivers context for enhanced customer experience  To build a platform for (1) listening to the voice of the customer, (2) learning what customers were saying, (3) sharing that information across a company, and then (4) engaging with the customer to close the loop, inQuba needed a single, fully integrated,... Read More →...
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Reflecting on 2016 to Guide BigMLs Journey in 2017

Jan 19 6:38am The Official Blog of BigML.com
2016 has proven a whirlwind year for BigML with substantial growth in users, customers and the team riding on the realization by businesses and experts that Machine Learning has transformational power in the new economy where data is in abundance but actionable insights have not been able to keep pace with improvements in storage, computational […]...
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13

Customer Analytics in an Insight-Driven Business

Jan 18 8:54am The TIBCO Blog
In its report titled “The Insights-Driven Business”, Forrester explained that “an insights-driven business harnesses and applies data and analytics at every opportunity to differentiate its products and customer experiences”. Insights-driven businesses operate in a closed-loop learning process, where they identify metrics to measure business outcomes, gather data to develop insights,... Read More →...
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5

Artificial Intelligence vs Machine Learning vs Deep Learning: What does it all mean?

Jan 17 11:41pm Robotics Zeitgeist
For more than a decade, hundreds of millions of people on planet Earth have, unbeknownst to them, interacted on a daily basis with the most advanced artificial intelligence (AI) ever created. The AI I am referring to is none other than the Google search engine. Surprised? Google’s online search engine actually meets the definition of… Read More »...
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6

How to Grid Search ARIMA Model Hyperparameters with Python

Jan 17 1:00pm Blog – Machine Learning Mastery
The ARIMA model for time series analysis and forecasting can be tricky to configure. There are 3 parameters that require estimation by iterative trial and error from reviewing diagnostic plots and using 40-year-old heuristic rules. We can automate the process of evaluating a large number of hyperparameters for the ARIMA model by using a grid […] The post How to Grid Search ARIMA Model Hyperparameters with Python appeared first on Machine Learning Mastery.
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6

Do They Practice What They Preach?

Jan 17 8:23am The TIBCO Blog
Are you wondering if what TIBCO says is easy is actually easy? Everybody ‘knows’ that we are in a data-driven culture where making decisions using data is the way to go. That’s why you see words like “data-discovery” mapped to “ROI” on just about every business website. However, the truth—more... Read More →...
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4

Adopting Cloud: Why, When, and How?

Jan 16 8:04am The TIBCO Blog
Many of the customer conversations I have these days cover the efforts organizations are undergoing to migrate their applications to the cloud. The conversations are deeper discussions than simply around the adoption of SaaS applications; we talk about how to leverage cloud in conjunction with existing infrastructure to: Modernize IT... Read More →...
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6

Machine Learning Books

Jan 15 1:00pm Blog – Machine Learning Mastery
The Complete Machine Learning Bookshelf. Books are a fantastic investment. You get years of experience for tens of dollars. I love books and I read every machine learning book I can get my hands on. I think having good references is the fastest way to getting good answers to your machine learning questions, and having […] The post Machine Learning Books appeared first on Machine Learning Mastery.
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9

AI weekly news roundup (Jan 8-14, 2017)

Jan 13 11:39pm Robotics Zeitgeist
The second week of January is now behind us, so here is a brief look at some AI related stories as we are heading into the second half of the new year’s first month. Microsoft acquired Canadian deep learning startup Maluuba partly in order to get deep learning pioneer Yoshua Bengio onboard. Professor Bengio has… Read More »...
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9

TIBCO Earns Dresner Advisory Services 2016 Technology Innovation Award

Jan 13 8:43am The TIBCO Blog
TIBCO starts off the new year right earning the Dresner Advisory Services 2016 Technology Innovation Award for technology leadership in Advanced & Predictive Analytics and Location Intelligence. The award recognizes the top vendors in its 2016 Wisdom of Crowds® series of thematic market studies. The annual research reports are based... Read More →...
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A Gentle Introduction to the Box-Jenkins Method for Time Series Forecasting

Jan 12 1:00pm Blog – Machine Learning Mastery
The Autoregressive Integrated Moving Average Model, or ARIMA for short is a standard statistical model for time series forecast and analysis. Along with its development, the authors Box and Jenkins also suggest a process for identifying, estimating, and checking models for a specific time series dataset. This process is now referred to as the Box-Jenkins […] The post A Gentle Introduction to the Box-Jenkins Method for Time Series Forecasting appeared first on Machine Learning Mastery.
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12

Digital Nebula Sparks Clients IT Innovation and Experimentation

Jan 12 8:03am The TIBCO Blog
Digital Nebula is a financial services consultancy that helps firms establish a digital presence, drive innovation, and prevent being disrupted. It works with tech startups to engage and compete with large organizations in a compliant and secure manner. Its goal is to give clients more agile capabilities that lead them... Read More →...
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4

Omni-Channel Experience Means So Much More Than Online Shopping

Jan 11 8:23am The TIBCO Blog
Congratulations! You made it through another holiday season. The final numbers for the season are still coming in, but, according to the National Retail Federation, American retailers saw about a 2\% year over year growth in shoppers during Thanksgiving weekend this year. That 2\% represents about 3 million more customers... Read More →...
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How to Model Residual Errors to Correct Time Series Forecasts with Python

Jan 10 1:00pm Blog – Machine Learning Mastery
The residual errors from forecasts on a time series provide another source of information that we can model. Residual errors themselves form a time series that can have temporal structure. A simple autoregression model of this structure can be used to predict the forecast error, which in turn can be used to correct forecasts. This […] The post How to Model Residual Errors to Correct Time Series Forecasts with Python appeared first on Machine Learning Mastery.
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5

Creating a Culture of Data Visualization

Jan 10 8:15am The TIBCO Blog
Many companies use data and analytics to make decisions and know how visualizations help people quickly grasp and better understand important information. Yet many companies struggle with data democratization. Instead of developing broad capability, people are intimidated, and visualization technology is available to only a select few. This doesn’t have... Read More →...
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9

Spotfire Tips and Tricks: Histograms Made Easy with Spotfire Data Panel

Jan 9 8:54am The TIBCO Blog
A histogram is a graphical method of representing a large amount of data by way of bars, to reflect the distribution frequency and proportion or density of each class interval as a data visualization.  TIBCO Spotfire analytic tool provides a quick and easy method to create histograms, which are common first... Read More →...
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How to Create an ARIMA Model for Time Series Forecasting with Python

Jan 8 1:00pm Blog – Machine Learning Mastery
A popular and widely used statistical method for time series forecasting is the ARIMA model. ARIMA is an acronym that stands for AutoRegressive Integrated Moving Average. It is a class of model that captures a suite of different standard temporal structures in time series data. In this tutorial, you will discover how to develop an […] The post How to Create an ARIMA Model for Time Series Forecasting with Python appeared first on Machine Learning Mastery.
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2

How to Build a Custom Flogo Adapter

Jan 6 8:40am The TIBCO Blog
Last year, TIBCO announced the Open Source Project Flogo at TIBCO NOW in Las Vegas. In October 2016, the project was published as first developer preview. You can reach the project via Flogo website TIBCO Community Source code on Github Introductory slides and videos This blog post demonstrates how build... Read More →...
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7

Book review: Deep Learning by Goodfellow, Bengio and Courville

Jan 6 12:57am Robotics Zeitgeist
The big success story this past year (several decades in the making, though) was deep learning, a machine learning method that has allowed researchers and practitioners to tackle with success some of the hardest problems in AI. Only problem is that for newcomers to the field no canonical reference for deep learning exists. Until now,… Read More »...
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10 Offbeat Predictions for Machine Learning in 2017

Jan 5 2:23pm The Official Blog of BigML.com
As each year wraps up experts pull their crystal balls from their drawers and start peering into it for a glimpse of what’s to come in the next one. At BigML, We have been following such clairvoyance carefully this past holiday season to compare and contrast with our own take on what 2017 will have in store, […]...
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How to Visualize Time Series Residual Forecast Errors with Python

Jan 5 1:00pm Blog – Machine Learning Mastery
Forecast errors on time series regression problems are called residuals or residual errors. Careful exploration of residual errors on your time series prediction problem can tell you a lot about your forecast model and even suggest improvements. In this tutorial, you will discover how to visualize residual errors from time series forecasts. After completing this […] The post How to Visualize Time Series Residual Forecast Errors with Python appeared first on Machine Learning Mastery.
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Harnessing the Integration Spectrum

Jan 5 8:41am The TIBCO Blog
The integration market has changed! When I look back to my role as an integration specialist a number of years ago (the start of a new year is as good as time as any for reflection), I remember talking about EAI (enterprise application integration), connectors, and mappings, and also discussing... Read More →...
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Building Analytics Apps for SaaS: Analytics as a Service

Jan 4 8:14am The TIBCO Blog
How can big data and embedded analytics be used to help students learn better? Waggle believes in learning and everything the company does has a simple goal: to improve the quality of education for students, teachers, and schools. They understand that real-time data analytics and visualizations can help a classroom teacher identify... Read More →...
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2

Time Series Data Visualization with Python

Jan 3 1:00pm Blog – Machine Learning Mastery
6 Ways to Plot Your Time Series Data with Python Time series lends itself naturally to visualization. Line plots of observations over time are popular, but there is a suite of other plots that you can use to learn more about your problem. The more you learn about your data, the more likely you are […] The post Time Series Data Visualization with Python appeared first on Machine Learning Mastery.
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TIBCOs 2017 Tech Predictions

Jan 3 8:00am The TIBCO Blog
With the close of 2016 behind us, we are facing a fresh, brand-new year and all of its possibilities. This season often has us wondering, discussing, and working toward what’s ahead. We put our heads together for a TIBCO think tank and compiled this lis of predictions for 2017. Here... Read More →...
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Autoregression Models for Time Series Forecasting With Python

Jan 1 1:00pm Blog – Machine Learning Mastery
Autoregression is a time series model that uses observations from previous time steps as input to a regression equation to predict the value at the next time step. It is a very simple idea that can result in accurate forecasts on a range of time series problems. In this tutorial, you will discover how to […] The post Autoregression Models for Time Series Forecasting With Python appeared first on Machine Learning Mastery.
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4

Ankis Cozmo robot is the best robot of 2016

Dec 31 1:10am Robotics Zeitgeist
If you haven’t heard of the tiny, adorable, smart, programmable, robot Cozmo then you have missed out on the best robot of 2016 and, possibly, the best entertainment robot ever build! Yes, we are not exaggerating when we say it is the best. We have one here, and it’s the best thing we’ve spent a… Read More »...
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How to Check if Time Series Data is Stationary with Python

Dec 29 1:00pm Blog – Machine Learning Mastery
Time series is different from more traditional classification and regression predictive modeling problems. The temporal structure adds an order to the observations. This imposed order means that important assumptions about the consistency of those observations needs to be handled specifically. For example, when modeling, there are assumptions that the summary statistics of observations are consistent. […] The post How to Check if Time Series Data is Stationary with Python appeared first on Machine Learning Mastery.
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Moving Average Smoothing for Data Preparation, Feature Engineering, and Time Series Forecasting with Python

Dec 27 1:00pm Blog – Machine Learning Mastery
Moving average smoothing is a naive and effective technique in time series forecasting. It can be used for data preparation, feature engineering, and even directly for making predictions. In this tutorial, you will discover how to use moving average smoothing for time series forecasting with Python. After completing this tutorial, you will know: How moving […] The post Moving Average Smoothing for Data Preparation, Feature Engineering, and Time Series Forecasting with Python appeared first on Machine Learning Mastery.
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Merry Christmas and Happy New Years 2017

Dec 25 5:46am Marcus P. Zillman
I would like to take this opportunity to wish all of my friends, associates and business acquaintances a Very Very... The post Merry Christmas and Happy New Years 2017 appeared first on Marcus P. Zillman.
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Fourth Edition of the Startup Battle at 4YFN

Dec 23 7:45am The Official Blog of BigML.com
Four Years From Now, the startup business platform of Mobile World Congress that enables startups, investors and corporations to connect and launch new ventures together, goes to Barcelona, Spain, from February 27 to March 1, 2017. We could not think of a better context to run the fourth edition of our series of Startup Battles. […]...
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Santas Got a Brand New Backend

Dec 22 8:00am The TIBCO Blog
Hiring Alyc—a strange, bearded, tattooed elf who seemed to speak only in Star Wars references—was a risk, but it paid off. He completely modernized the entire North Pole enterprise, despite about 1700 years of legacy code and hardware. The old Naughty and Nice system—originally handwritten in massive ledgers, then migrated... Read More →...
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Should you say Myanmar or Burma?

Dec 21 12:45am Babbage
“FOLLOW local practice when a country expressly changes its name,” advises “The Economist Style Book”, the Bible of this newspaper. Among the list of examples that follow (“Lviv, not Lvov” etc) only two rate authorial interjections: “Myanmar, not (alas) Burma” and “Yangon, not (alas, alack) Rangoon”. We follow that dictate in our pages, of course, but not everyone else does. Upon landing at the country’s busiest airport, your pilot may welcome you to Yangon, but your luggage will still be tagged RGN. Though Barack Obama referred to Myanmar when he met the country’s former president, Thein Sein, for the first time, the American embassy still gives its address as “Rangoon, Burma”. And ordinary Burmese tend to refer, at least in conversation, to their country as “Burma” and its capital as “Rangoon”. Which should you use, and why?In 1989 the then-ruling military junta changed the name, one year after it brutally suppressed an uprising, and one year before Aung San Suu Kyi won a landslide electoral victory that the junta simply ignored. The...Continue reading...
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The most profitable time of the year

Dec 20 2:54pm Babbage
We look at the decline in holiday spending in America and ask what surprises 2017 could bring. And Adrian Wooldridge takes on the ghosts of capitalism past, present and future...
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Even Easier Machine Learning for Every Day Tasks

Dec 20 11:39am The Official Blog of BigML.com
Recently, the “Machine Learning for Everyday Tasks” post suddenly rising to the top of Hacker News drew our attention. In that post, Sergey Obukhov, software developer at San Francisco-based startup Mailgun, tries to debunk the myth that Machine Learning is a hard task: I have always felt like we can benefit from using machine learning for simple tasks that […]...
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The challenges of adapting The Red Shoes

Dec 19 10:11am Babbage
THE big screen hungers for them, the small screen is addicted and the stage would not survive without a constant supply of adaptations of novels and films. If it is true that there are only seven basic plots in fiction, it is hardly surprising that the performing arts are one big recycling plant. But what happens when a story makes the journey from one medium to another and back again? What happens to its DNA along the way?“The Red Shoes”, originally a short story by Hans Christian Andersen, is now better known to the world as a British film classic made by Michael Powell and Emeric Pressburger. In their hands, a sinister tale about a pair of shoes that compelled the wearer to dance indefinitely became a complex romantic tragedy about the power struggles in an international ballet company, and an allegory of ambition and sexual desire. The fictional company is run by a saturnine figure whose new ballerina is played by the entrancing, flame-haired Moira Shearer (who was, in real life, a member of the fledgling Royal Ballet). Released in 1948, the film has been hailed as the greatest picture from one of the greatest film-making teams. It’s one that plumbs the...Continue reading...
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