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Free book: The #dataengineering cookbook by Andreas Kretz

 

 

I found an interesting, free book which is still a work in progress book – The Data Engineering Cookbook

 

I will be contributing through the author (Andreas Kretz.com) patreon site : (…

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Added by ajit jaokar on July 17, 2019 at 11:00am — No Comments

Thinking about Moving Up to Automated Machine Learning (AML)

Summary: Are you wondering about moving up to Automated Machine Learning (AML)?  Here are some considerations to help guide you.

 

Are you wondering about moving up to Automated Machine…

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Added by William Vorhies on July 15, 2019 at 7:30am — No Comments

Live Chat Vs Chatbot: Which Is The Best For Your Business

Establishing and tracking engagement on website pages, giving solution to audience queries, resolving FAQs, and assisting with maintenance is a powerful way for businesses to build relations with existing and potential customers.

To support the customer-brand relationship, there are two big ways…

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Added by Jassjeet Kaur on July 14, 2019 at 9:17pm — No Comments

How to learn the maths of Data Science using your high school maths knowledge - Gradient Descent

This post is a part of my forthcoming book on Mathematical foundations of Data Science.

In the previous blog, we saw how you could use basic high school maths to learn about the workings of data science and artificial intelligence

In this post we extend that idea to learn about Gradient descent

We…

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Added by ajit jaokar on July 14, 2019 at 12:30pm — No Comments

Return of the Thriller “3 Horizons of Digital Transformation”

In “Importance of Thinking Differently…Hint: Don’t Pave the Cow Path”, I introduced the concept of the “3 Horizons of Digital Transformation.”  I wanted to provide a framework that helped organizations differentiate between “Digitalization” versus “Digital Transformation”.  Unfortunately, in succeeding client engagements, I realized I did a crappy job of explaining these 3…

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Added by Bill Schmarzo on July 13, 2019 at 12:25pm — No Comments

Bayesian Machine Learning

Bayesian Machine Learning (part - 3)

 

Bayesian Modelling

In this post we will see the methodology of building  Bayesian models. In my previous post I used a Bayesian model for linear regression. The model looks like:…

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Added by Ashutosh vyas on July 13, 2019 at 3:28am — No Comments

Data Science Central Monday Digest, July 15

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this…

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Added by Vincent Granville on July 12, 2019 at 6:30am — No Comments

How do I prepare for Data Scientist interviews?

If you are a recent graduate or someone preparing for your first data scientist position, then here are some tips to help you ace your interview!…

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Added by Ann Rajaram on July 11, 2019 at 2:52pm — No Comments

Summarizing Economic Bulletin Documents with TF-IDF

A key strength of NLP (natural language processing) is being able to process large amounts of texts and then summarise them to extract meaningful insights.

In this example, a selection of economic bulletins in PDF format from 2018 to 2019 are analysed in order to gauge economic sentiment. The bulletins in question are sourced from the European Central Bank website. tf-idf is used to rank…

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Added by Michael Grogan on July 11, 2019 at 12:28pm — No Comments

Data Science Central Thursday Digest, July 11

Featured selected articles and technical resources posted since Monday.

Technical Resources

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Added by Vincent Granville on July 10, 2019 at 9:30am — No Comments

Machine Learning in Agriculture: Applications and Techniques

Recently we have discussed the emerging concept of smart farming that makes agriculture more efficient and…

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Added by Max Ved on July 10, 2019 at 8:30am — No Comments

Comparing Model Evaluation Techniques Part 1: Statistical Tools & Tests

Evaluating a model is just as important as creating the model in the first place. Even if you use the most statistically sound tools to create your model, the end result may not be what you expected. Which metric you use to test your model depends on the type of data you’re working with and your comfort level with statistics.

Model evaluation techniques answer three main questions:

  1. How well does your model match your data (in other words, what is the…
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Added by Stephanie Glen on July 10, 2019 at 5:36am — 1 Comment

Ten Machine Learning Algorithms You Should Know to Become a Data Scientist

machine learning algorithms



Machine Learning Practitioners have different personalities. While some of them are “I am an expert in X and X…

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Added by Shaily Baheti on July 9, 2019 at 11:00pm — No Comments

Smart Farming, or the Future of Agriculture

We are a Ukraine-based company which means that our parents and grandparents lived in the era of infamous Soviet collective farms, where tractors were considered to be an ultimate technology. For them, a smart farm will sound like a fairy tale.…

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Added by Max Ved on July 9, 2019 at 2:41pm — No Comments

New MOOC on Coursera on Data Science for Business Innovation for non-IT Professionals

The course "Data Science for Business Innovation" is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation.

It consists of introductory lectures spanning big data, machine learning, data valorization and communication for a non-technical audience.

You can register for free on Coursera at this…

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Added by Marco Brambilla on July 9, 2019 at 4:30am — No Comments

Enter the Era of Terabyte Memory

Enabling cost-effective terabyte main memory along with third-party observations of a “profound” change in storage, Intel® Optane™ DC persistent memory modules change the way we think about memory capacity, tiered memory, out-of-core algorithms, storage speed, and essentially what we can do on a computational “fat node” and with persistent storage.

With a growing ecosystem of more than 50 OEMs, ISVs and cloud service providers are exploring what is possible given the touted three-fold…

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Added by Rob Farber on July 8, 2019 at 1:51pm — No Comments

State of #AI 2019 Report

I highly recommend  the #StateofAI 2019 report. I have followed this report from By Nathan Benaich and Ian Hogarth

The report is free and you can download it at stateofai 2019

The report is kind of Mary Meeker theme for AI for me i.e. a great reference…

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Added by ajit jaokar on July 8, 2019 at 9:04am — 1 Comment

Privacy and AI - How Much Should We Really Care

Summary:  More data means better models but we may be crossing over a line into what the public can tolerate, both in the types of data collected and our use of it.  The public seems divided.  Targeted advertising is good but the increased invasion of privacy is bad.

 

Headlines are full of alarm.  The public is up in arms.  The internet is stealing their privacy.  Indeed, the Future of Humanity Institute at Oxford rates this as the most…

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Added by William Vorhies on July 8, 2019 at 7:30am — No Comments

The Importance of Community in Data Science

Nobody is an island. Even less so a data scientist. Assembling predictive analytics workflows benefits from help and reviews: on processes and algorithms by data science colleagues; on IT infrastructure to deploy, manage and monitor the AI-based solutions by IT professionals; on dashboards and reporting features to communicate the final results by data visualization experts; as well as on automatization features for workflow execution by system administrators. It really seems that a…

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Added by Rosaria Silipo on July 8, 2019 at 6:00am — No Comments

Top IoT Predictions & Trends For The Year 2019

What Do You Mean By IoT?

According to TechTarget, IoT also known as the Internet of Things is a system of inter-related computer devices, machine,…

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Added by Harikrishna on July 8, 2019 at 1:30am — No Comments

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