Bigdata, futureofdata, podcast, bigdata & much more…
BigData News Monday, July 23
- RPubs – Machine Learning con H2O y R
- Listen on Google Play Music
BigData, FutureOfData, Podcast
- Gaussian Processes for Machine Learning: Book webpage
- Eckerson Group
bigdata, digitaltransformation, DataOps, DevOps, dataquality, bigdata
- Most of AI’s Business Uses Will Be in Two Areas
- liveVideo • premium video training by Manning
apachespark, bigdata, datastreaming
- Top languages and tools according to Data Professionals
- NodeXL Graph Gallery: Graph Details
iiot, iiot, iot, ai, bigdata, ml, machinelearning, cybersecurity, artificialintelligence
@taimourzaman: What healthcare CFOs should know about artificial intelligence, machine learning and chatbots https://t.co/upPr9AwaK0
@RPubsRecent: Machine Learning con H2O y R https://t.co/Dz1Jx6S4xQ
@AppCzar: #BigData @AnalyticsWeek #FutureOfData #Podcast with Michael OConnell, @Tibco https://t.co/FuTyEGJcum
- Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines.
- GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning.
- The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics.
- Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others.
- The book contains illustrative examples and exercises, and code and datasets are available on the Web.
@newsycombinator: Gaussian Processes for Machine Learning (2010) https://t.co/K0f4YkOpab
@weckerson: In the #bigdata world, siloed roles prove too rigid and slow for #digitaltransformation! That’s where the need for #DataOps arises: https://t.co/6zeKVHgtAs #DevOps #dataquality #bigdata
- As they shouldone estimate suggests that 40% of all the potential value that can created by analytics today comes from the AI techniques that fall under the umbrella deep learning, (which utilize multiple layers of artificial neural networks, so-called because their structure and function are loosely inspired by that of…
- As they shouldwe estimate that 40% of all the potential value that can created by analytics today comes from the AI techniques that fall under the umbrella , (which utilize multiple layers of artificial neural networks, so-called because their structure and function are loosely inspired by that of the human…
- After all, embedding AI across the business requires significant investment in talent and upgrades to the tech stack as well as sweeping change initiatives to ensure AI drives meaningful value, whether it be through powering better decision-making or enhancing consumer-facing applications.
- We found that the greatest potential for AI to create value is in use cases where neural network techniques could either provide higher performance than established analytical techniques or generate additional insights and applications.
- Even as we see economic potential in the use of AI techniques, we recognize the tangible obstacles and limitations to implementing AI.
@HarvardBiz: Where deep learning will have the biggest impacthttps://t.co/gZI2R8C05K
@ManningBooks: Spark simplifies your data infrastructure! Find out how with our video course https://t.co/L9wVB3gjjh Spark in Motion. #apachespark #bigdata #datastreaming
- Packt Publishing, publisher of software learning resources, has revealed the results of its 2018 Skill Up Developer Skills survey in a new report.From what programming languages, frameworks, and libraries are most used, to job satisfaction, the report offers a snapshot of what matters to software developers in 2018.
- In the Skill Up Survey, both app and web developers have spoken of the importance of Machine Learning and other cutting edge data techniques to their future success.
- Here are some of the key findings from Packts report on Data Science: – – Standing proud, Python has ascended to be the number one language of data.
- Pythons ease of use, powerful tools and libraries, and use outside of the data field make it almost mandatory to know and use in 2018.
- Pushing Machine Learning algorithms further and further is going to be one of the key challenges for every data professional over the next year and beyond.
@marc_smith: #iiot via NodeXL https://t.co/6BzT9zAyoZ@fisher85m@iiot_world@mikequindazzi@wil_bielert@evankirstel@antgrasso@jblefevre60@gp_pulipaka@tamaramccleary@ravikikanTop hashtags:#iiot#iot#ai#bigdata#ml#machinelearning#cybersecurity#artificialintelligence