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AI News Monday, February 12

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AI News TLDR / Table of Contents

  • Emergence Of Coding without Codes
    • Blockchain is a platform that allows the developers to reimagine . two of these developers, Ben Gorlick and Johnny Dilley left a renowned Blockchain industry, Blockstream, in order to join a start-up company named Crown Machine with the designation of CTO and CSA respectively.
    • crowd machine, distributive cloud computing, Gorlick, basic calendar app, ICO based industries
  • Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics
    • In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, de…
    • data science, machine learning, data scientist, ,
  • A Complete Tutorial to Learn Data Science with Python from Scratch
    • This article on a complete tutorial to learn Data Science with Pyhon from scratch, was posted by Kunal Jain. Kunal is a post graduate from IIT Bombay in Aerosp…
    • python, Kunal Jain. Kunal, data science, data analysis, Python libraries
  • YouTube
    • Duration, ngAtlanta, views, Angular vs React.js, Smart Angular Elements

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Score: 2702.5788969359332
URL: https://www.applancer.co/blog/emergence-of-coding-without-codes
Tweeted At: Wed Feb 07 06:00:00 +0000 2018
Publish Date: 2018-02-07T11:21:00+00:00
Author: Applancer

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Emergence Of Coding without Codes

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  • With the emergence of Blockchain technology, developers realized what still needs to be discovered and like many other Blockchain and ICO based industries, Crowd Machine believes that this technology can help in improving the situation.
  • To explain his current companies idea, Gorlick came forward with an example of basic calendar app.
  • Describing the functioning of Cloud machine, Gorlick said that the new technology will break this technology into a bunch of pieces which would be launched from a network of devices that would amalgamate them together.
  • Gorlick and Dilley came up with this idea while working at block stream and also decided that nodes will work as they are doing it with a part of involved incentives in the form of Crowd machine tokens.
  • Gorlick – – With the usage of this technology, developing countries like Africa will be able to accomplish their blockchain ideas without spending huge amount on AWS

[/vc_column_text][vc_column_text el_class=”topfeed-tags”]Tags: crowd machine, distributive cloud computing, Gorlick, basic calendar app, ICO based industries[/vc_column_text][/vc_column][vc_column width=”1/2″][vc_separator][vc_column_text el_class=”topfeed-tweet”]

[/vc_column_text][vc_column_text el_class=”topfeed-embedly”]Emergence Of Coding without Codes – Applancer[/vc_column_text][/vc_column][/vc_row][vc_row el_id=”Difference-between-Machine-Learning-Data-Science-AI-Deep-Learning-and-Statistics”][vc_column width=”1/2″][vc_separator][vc_column_text]

Score: 2227.7665794979084
URL: https://www.datasciencecentral.com/profiles/blogs/difference-between-machine-learning-data-science-ai-deep-learning
Tweeted At: Mon Feb 12 03:25:13 +0000 2018
Publish Date:
Author: Vincent Granville

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Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics

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  • In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics.
  • Before digging deeper into the link between data science and machine learning, let’s briefly discuss machine learning and deep learning.
  • If the data collected comes from sensors and if it is transmitted via the Internet, then it is machine learning or data science or deep learning applied to IoT.
  • Machine learning and statistics are part of data science.
  • For instance, unsupervised clustering – a statistical and data science technique – aims at detecting clusters and cluster structures without any a-priori knowledge or training set to help the classification algorithm.

[/vc_column_text][vc_column_text el_class=”topfeed-tags”]Tags: data science, machine learning, data scientist, , [/vc_column_text][/vc_column][vc_column width=”1/2″][vc_separator][vc_column_text el_class=”topfeed-tweet”]

[/vc_column_text][vc_column_text el_class=”topfeed-embedly”]Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics – Data Science Central[/vc_column_text][/vc_column][/vc_row][vc_row el_id=”A-Complete-Tutorial-to-Learn-Data-Science-with-Python-from-Scratch”][vc_column width=”1/2″][vc_separator][vc_column_text]

Score: 865.0931709503884
URL: https://www.datasciencecentral.com/profiles/blogs/a-complete-tutorial-to-learn-data-science-with-python-from?overrideMobileRedirect=1
Tweeted At: Mon Feb 12 03:42:18 +0000 2018
Publish Date:
Author: Emmanuelle Rieuf

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A Complete Tutorial to Learn Data Science with Python from Scratch

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  • This article on a complete tutorial to learn Data Science with Pyhon from scratch, was posted byKunal Jain.
  • Python was originally a general purpose language.
  • Due to lack of resource on python for data science, he decided to create this tutorial to help many others to learn python faster.
  • In this tutorial, you will take bite sized information about how to use Python for Data Analysis, chew it till you are comfortable and practice it at your own end.
  • For other articles about Python,click here.

[/vc_column_text][vc_column_text el_class=”topfeed-tags”]Tags: python, Kunal Jain. Kunal, data science, data analysis, Python libraries[/vc_column_text][/vc_column][vc_column width=”1/2″][vc_separator][vc_column_text el_class=”topfeed-tweet”]

[/vc_column_text][vc_column_text el_class=”topfeed-embedly”]A Complete Tutorial to Learn Data Science with Python from Scratch – Data Science Central[/vc_column_text][/vc_column][/vc_row][vc_row el_id=”YouTube”][vc_column width=”1/2″][vc_separator][vc_column_text]

Score: 4510.9843624406285
URL: https://www.youtube.com/watch?feature=youtu.be&v=28_Q9wu01i0
Tweeted At: Mon Feb 12 15:00:03 +0000 2018
Publish Date:
Author:

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YouTube

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    [/vc_column_text][vc_column_text el_class=”topfeed-tags”]Tags: Duration, ngAtlanta, views, Angular vs React.js, Smart Angular Elements[/vc_column_text][/vc_column][vc_column width=”1/2″][vc_separator][vc_column_text el_class=”topfeed-tweet”]

    [/vc_column_text][vc_column_text el_class=”topfeed-embedly”]How to Do Sales Win loss Analysis with Watson Analytics[/vc_column_text][/vc_column][/vc_row]