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Entrepreneurial Resources 2017

Entrepreneurial Resources (EntrepreneurialResources.info) is a Subject Tracer™ Information Blog developed and created by the Virtual Private Library™. It is designed to monitor entrepreneurial resources on the World Wide Web.

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Web Guide for the New Economy 2017:

Web Guide for the New Economy 2017 Download the Web Guide for the New Economy The Web Guide for the…

Recent Blog Posts

Deep Learning for Java – Open Source, Distributed, Deep Learning Library for the JVM

July 28, 2017

Deep Learning for Java – Open Source, Distributed, Deep Learning Library for the JVM
https://deeplearning4j.org/

Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Spark, DL4J is designed to be used in business environments on distributed GPUs and CPUs. Deeplearning4j aims to be cutting-edge plug and play, more convention than configuration, which allows for fast prototyping for non-researchers. DL4J is customizable at scale. Released under the Apache 2.0 license, all derivatives of DL4J belong to their authors. DL4J can import neural net models from most major frameworks via Keras, including TensorFlow, Caffe, Torch and Theano, bridging the gap between the Python ecosystem and the JVM with a cross-team toolkit for data scientists, data engineers and DevOps. This will be added to Data Mining Resources Subject Tracer™. This will be added to Artificial Intelligence Resources Subject Tracer™.

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MOA (Massive Online Analysis)

July 28, 2017

MOA (Massive Online Analysis)
https://moa.cms.waikato.ac.nz/

MOA is the most popular open source framework for data stream mining, with a very active growing community (blog). It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation. Related to the WEKA project, MOA is also written in Java, while scaling to more demanding problems. This will be added to Data Mining Resources Subject Tracer™. This will be added to Artificial Intelligence Resources Subject Tracer™.

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Weka 3: Data Mining Software in Java

July 28, 2017

Weka 3: Data Mining Software in Java
http://www.cs.waikato.ac.nz/ml/weka/index.html

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this. Weka is open source software issued under the GNU General Public License. They have put together several free online courses that teach machine learning and data mining using Weka. Check out the website for the courses for details on when and how to enroll. The videos for the courses are available on Youtube. Yes, it is possible to apply Weka to big data! This will be added to Data Mining Resources Subject Tracer™. This will be added to Artificial Intelligence Resources Subject Tracer™.

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Updated> Searching the Internet 2017 – A Primer by Marcus P. Zillman, M.S., A.M.H.A.

July 27, 2017

Updated> Searching the Internet 2017 – A Primer by Marcus P. Zillman, M.S., A.M.H.A.
http://www.SearchingTheInternet.info/

The annotated white paper titled “Searching the Internet 2017 – A Primer” by Marcus P. Zillman, M.S., A.M.H.A. has been updated and is a primer for those new to searching the Internet or for experienced searchers always looking for new and innovative search sources .. both are all included in this primer!! It is freely available as a 19 page .pdf document (394KB) from the above link from the Virtual Private Library™. Other white papers are available by clicking here. [Updated with all links validated and new links added on: July 15, 2017]

This research is powered by Subject Tracer Bots™ available from the Virtual Private Library™.

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Microsoft Cognitive Toolkit

July 27, 2017

Microsoft Cognitive Toolkit
https://www.microsoft.com/en-us/cognitive-toolkit/

A free, easy-to-use, open-source, commercial-grade toolkit that trains deep learning algorithms to learn like the human brain. Unlock deeper learning with the new Microsoft Cognitive Toolkit. The Microsoft Cognitive Toolkit—previously known as CNTK—empowers you to harness the intelligence within massive datasets through deep learning by providing uncompromised scaling, speed, and accuracy with commercial-grade quality and compatibility with the programming languages and algorithms you already use. Features include: a) Speed & Scalability – The Microsoft Cognitive Toolkit trains and evaluates deep learning algorithms faster than other available toolkits, scaling efficiently in a range of environments—from a CPU, to GPUs, to multiple machines—while maintaining accuracy; b) Commercial-Grade Quality – The Microsoft Cognitive Toolkit is built with sophisticated algorithms and production readers to work reliably with massive datasets. Skype, Cortana, Bing, Xbox, and industry-leading data scientists already use the Microsoft Cognitive Toolkit to develop commercial-grade AI; and c) Compatibility – The Microsoft Cognitive Toolkit offers the most expressive, easy-to-use architecture available. Working with the languages and networks you know, like C++ and Python, it empowers you to customize any of the built-in training algorithms, or use your own. This will be added to Artificial Intelligence Resources Subject Tracer™.

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Char-RNN

July 27, 2017

Char-RNN
https://github.com/karpathy/char-rnn

This code implements multi-layer Recurrent Neural Network (RNN, LSTM, and GRU) for training/sampling from character-level language models. In other words the model takes one text file as input and trains a Recurrent Neural Network that learns to predict the next character in a sequence. The RNN can then be used to generate text character by character that will look like the original training data. The context of this code base is described in detail in my blog post. If you are new to Torch/Lua/Neural Nets, it might be helpful to know that this code is really just a slightly more fancy version of this 100-line gist that I wrote in Python/numpy. The code in this repo additionally: allows for multiple layers, uses an LSTM instead of a vanilla RNN, has more supporting code for model checkpointing, and is of course much more efficient since it uses mini-batches and can run on a GPU. This will be added to Artificial Intelligence Resources Subject Tracer™.

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Awareness Watch Talk Show for Wednesday July 26, 2017 at 2:00pm EDST – Artificial Intelligence Resources 2017

July 26, 2017

Awareness Watch Talk Show for Wednesday July 26, 2017 at 2:00pm EDST – Artificial Intelligence Resources 2017
http://www.BlogTalkRadio.com/AwarenessWatch/

This program will be featuring my just updated Artificial Intelligence Resources 2017. We will be highlighting the latest and greatest resources and sources for artificial intelligence covering search engines, subject directories, articles, guides and tracers….literally everything on the Internet covering ARTIFICIAL INTELLIGENCE!! We will also discussing my latest freely available Awareness Watch Newsletter V15N7 July 2017 featuring 2017 New Economy as well as my freely available July 2017 Zillman Column highlighting Employment Resources 2017. You may call in to ask your questions at (718)508-9839. The show is live and thirty minutes in length starting at 2:00pm EDST on Wednesday, July 26, 2017 and then archived for easy review and access. Listen, Call and Enjoy!!

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Updated> Data Mining Resources 2017 Whitepaper Dataset Link Compilation

July 26, 2017

Updated> Data Mining Resources 2017 Whitepaper Dataset Link Compilation
http://www.DataMiningResources.info/

I have just updated my Data Mining Resources 2017 Subject Tracer™ Whitepaper Dataset Link Compilation and it is now a 33 page (286KB) .pdf white paper document is available from the above URL link. It lists alphabetically the latest resources and sources for data mining available from the Internet.[Completely updated with all links validated and new URLs added on July 8, 2017] Additional white papers and resources by Marcus P. Zillman are available by clicking here.

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Voice Project

July 26, 2017

Voice Project
https://voice.mozilla.org/

oice recognition technology could revolutionize the way we interact with machines, but it’s expensive and proprietary. Common Voice is a project to make voice recognition technology easily accessible to everyone. People donate their voices to a massive database that will let anyone quickly and easily train voice-enabled apps. All voice data will be available to developers. Voice is natural, voice is human. It’s the easiest and most natural way to communicate. With Common Voice, developers can build amazing things––from real-time translators to voice-enabled administrative assistants. But the data they need to build these apps isn’t publicly available. Common Voice will give them what they need to innovate. Mozilla aims to begin to capture voices in June and release the open source database later in 2017. This will be added to Research Resources Subject Tracer™

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Updated> Crowdfunding Resources 2017

July 25, 2017

Updated> Crowdfunding Resources 2017
http://www.CrowdFundingResources.info/

This newly created white paper link dataset compilation covering Crowdfunding Resources 2017 displays all areas of crowdfunding including equity crowdfunding. The Internet has become the financial go to for entrepreneurs to kickstart their financial needs for their startups! This will be added to Financial Sources Subject Tracer™, Entrepreneurial Resources Subject Tracer™ and Startup Resources for the Entrepreneur white paper. [Updated July 7, 2017 24 Pages, 212KB PDF]

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