- Top 9 Mobile Apps for Learning and Practicing Data Science - Jan 17, 2020.
This article will tell you about the top 9 mobile apps that help the user in learning and practicing data science and hence is improving their productivity.
- Google Open Sources MobileNetV3 with New Ideas to Improve Mobile Computer Vision Models - Dec 2, 2019.
The latest release of MobileNets incorporates AutoML and other novel ideas in mobile deep learning.
- The Semiconductor Imperative for Driving Meaningful Innovation - Nov 20, 2019.
The fundamental fact is that more information than ever will need to be analyzed on millions of devices. And that’s where 5G will make accessing data dramatically faster and more efficient. At Samsung, we’re excited about what 5G can truly enable and to be a central player in the new 5G world.
- The Hackathon Guide for Aspiring Data Scientists - Jul 15, 2019.
This article is an overview of how to prepare for a hackathon as an aspiring data scientist, highlighting the 4 reasons why you should take part in one, along with a series of tips for participation.
- Comparing MobileNet Models in TensorFlow - Mar 1, 2019.
MobileNets are a family of mobile-first computer vision models for TensorFlow, designed to effectively maximize accuracy while being mindful of the restricted resources for an on-device or embedded application.
- KDnuggets™ News 18:n39, Oct 17: 10 Best Mobile Apps for Data Scientist; Vote in new poll: Largest dataset you analyzed? - Oct 17, 2018.
Also: An interesting explanation of why Adversarial examples arise; 5 clean code tips to improve your productivity; Github Python Data Science; and don't forget to vote in new poll: What was the largest dataset you analyzed?
- 10 Best Mobile Apps for Data Scientist / Data Analysts - Oct 10, 2018.
A collection of useful mobile applications that will help enhance your vital data science and analytic skills. These free apps can improve your listening abilities, logical skills, basic leadership qualities and more.
- DeepSense: A unified deep learning framework for time-series mobile sensing data processing - Aug 2, 2017.
Compared to the state-of-art, DeepSense provides an estimator with far smaller tracking error on the car tracking problem, and outperforms state-of-the-art algorithms on the HHAR and biometric user identification tasks by a large margin.
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- 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.
- Uber-fication! Uberize Your Business - Jan 2, 2017.
We examine what Uber has done that drives success in many markets across the globe and why so many businesses are seeking an Uber-style solution to their business. We present a listing of lessons on what to do if you are seeking to Uber-ize your business model.
- Where Analytics, Data Mining, Data Science were applied in 2016 - Dec 12, 2016.
CRM/Consumer Analytics, Finance, and Banking are still the leading applications, but Anti-spam, Mobile apps, Travel/hospitality grew the most in 2016. Share of Health care, Consumer analytics, and Direct Marketing/ Fundraising data science applications declined for 2 years in a row.
- TalkingData Data Science Competition: understand mobile users - Jul 12, 2016.
Unique opportunity to solve complex real world big data challenges for the China mobile market - predict users demographic characteristics based on their app usage, geolocation, and mobile device properties.
- Top KDnuggets tweets, Jun 22-28: #Bayesian #Statistics explained in Simple English; Brexit - Jun 29, 2016.
#Bayesian #Statistics explained to Beginners in Simple English; Amazing analysis of #Brexit with #MachineLearning - it is sad; 18 Useful Mobile Apps for #DataScientist; Sharp divisions between England, #Scotland in #Brexit vote suggest future UK split.
- CrowdSignals.io, Building Big Mobile Social Sensor dataset - Mar 25, 2016.
CrowdSignals.io a crowdfunding campaign to generate the largest mobile and sensor dataset available to the Data Science community for use in research and product development.
- Top KDnuggets tweets, Feb 08-14: MIT-designed chip brings #MachineLearning to mobile devices; Best TED Talks for #DataScientist - Feb 15, 2016.
Best TED Talks for #DataScientist; Easy #DeepLearning w. TensorFlow; #DataScientist Valentine's Day Options - neural net predicts 98.9% compatibility; DeepLearning is not Enough - majority in KDnuggets Poll says; Great #DataScience application: Most timeless #song of all time #Spotify.
- KDnuggets™ News 16:n04, Feb 3: Is Deep Learning Overhyped? Businesses Will Need 1M Data Scientists - Feb 3, 2016.
New Poll: Deep Learning - does reality match the hype?; Is Deep Learning Overhyped?; Businesses Will Need One Million Data Scientists by 2018; KDnuggets New Responsive, Mobile-Friendly Design.
- KDnuggets New Responsive, Mobile-Friendly Design - Feb 2, 2016.
Check KDnuggets new responsive, mobile-friendly design and different new features, including more ways to access our rich content.
- Uber-fication: Lessons from Uber in Economics, Digital, Risk, and Analytics - Dec 5, 2015.
Uber-fication or Uberisation is the conversion of existing jobs and services into discrete tasks that can be requested on-demand; the emulation or adoption of the Uber’s business model. Here we have discussed opportunities, risk and challenges while doing uberisation.
- Upcoming Webcasts on Analytics, Big Data, Data Science – Aug 25 and beyond - Aug 24, 2015.
Advance Speech Analytics, Mobile Analytics, Scraping data with import.io, Graph Analytics, Big Data Certification - which one, and more.
- Interview: Ali Vanderveld, Groupon on How Data Science is Changing the Global E-commerce Marketplace - Jul 17, 2015.
We discuss the tools used for data science, competitive landscape, journey from astrophysics to data science, advice, skills sought in data scientists, and more.
- Data Science and Mobile Devices: Joined at the Hip - Jun 25, 2015.
As number of wearable and IoT devices have soared, there is a new big data market emerging at horizon. Here, we have scratched the surface of this giant and got few connections between mobile devices and data science.
- Localytics: Data Scientist - Feb 12, 2015.
Build the future of mobile with Localytics. Named among the top places to work by The Boston Globe, we're changing mobile marketing and analytics through predictive modeling and machine learning.
- Interview: Daqing Zhao, Macys.com on Building Effective Data Models for Marketing - Dec 11, 2014.
We discuss the challenges in identifying the fair price of ad media, recommendations for building effective models for online marketing, unique challenges of Mobile channel, selection of Big Data tools, and more.
- Tableau Top 10 Trends in Business Intelligence for 2015 - Dec 6, 2014.
Tableau Software presents its top 10 trends in business intelligence in 2015, including transformed data governance, improved social intelligence, and organizational analytics.
- Interview: Igor Elbert, Gilt on Boosting Sales through Analytics-curated Shopping - Dec 4, 2014.
We discuss Analytics at Gilt, unique Analytics challenges of a flash sales portal, consumer behavior across channels, interesting insights, advice and more.
- Sisense 2015 predictions for BI, Big Data - Dec 3, 2014.
Mobile devices, text analytics, Google Glass, and data intelligence will be key to the evolution of business intelligence in 2015 according to Adi Azaria and Eldad Farkash of SiSense.
- Stanford: Postdoctoral Position in Data Mining of Human Activity - Nov 20, 2014.
Stanford University's newly-established Mobility Center has several openings for postdoctoral candidates interested in researching the intersection of human health and machine learning.
- Amazon: Business Intelligence Engineer, Mobile Business Development - Apr 17, 2014.
Talented BI Engineer who is passionate about using data to drive crucial business decisions regarding our activity in the mobile ecosystem.
- RootMetrics: Statistical Analyst - Mar 14, 2014.
Join us at RootMetrics where we are providing an accurate view of wireless carrier and connected device performance, and help build a movement for an open mobile market that democratizes mobile performance data.