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Free book – learn azure in a month of lunches – covering Cloud, AI, devops etc

 

 

 

At the Data Science for IoT course at the University of Oxford – I have been working on a strategy implementing Artificial Intelligence holistically on the Cloud and Edge. This is a complex approach with many new concepts to learn.…

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Added by ajit jaokar on April 23, 2019 at 11:00am — No Comments

Causality – The Next Most Important Thing in AI/ML

Summary:  Finally there are tools that let us transcend ‘correlation is not causation’ and identify true causal factors and their relative strengths in our models.  This is what prescriptive analytics was meant to be.

 

Just when I thought we’d figured it all out, something comes along to make…

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Added by William Vorhies on April 22, 2019 at 8:47am — No Comments

Data Science Central Weekly Digest, April 22

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 April 21, 2019 at 10:00am — No Comments

Unsolved Problems in Machine Learning

Quora contribution written by Chomba Bupe.

I am actually not even aware of any machine learning (ML) problem that is considered to have been solved recently or in the past. This tells you a lot about how hard things really are in ML. Of course, if you read media outlets, it may seem like researchers are sweeping the floor clean with deep learning (DL), solving ML problems one…

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Added by Andrea Manero-Bastin on April 21, 2019 at 6:00am — No Comments

Data Curation: Weaving Raw Data into Business Gold

The Big Data craze caught fire with a provocative declaration that “Data is the New Oil”; that data will fuel the economic growth in the 21stcentury in much the same way that oil fueled the economic growth of the 20thcentury.  The “New Oil” analogy was a great way to contextualize the economic value of data; to give the Big Data conversation an easily recognizable face.  The Economist recently declared data “…

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Added by Bill Schmarzo on April 19, 2019 at 11:15am — No Comments

What my first Silver Medal taught me about Text Classification and Kaggle in general?

Kaggle is an excellent place for learning. And I learned a lot of things from the recently concluded competition on Quora Insincere questions classification in which I got a rank of 182/4037. In this post, I will try to provide a summary of the things I tried. I will also try to summarize the ideas which I missed but were a part of other winning solutions.



As a side note: if you want to know more about NLP, I would…

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Added by Rahul Agarwal on April 19, 2019 at 10:15am — No Comments

Data Science Central Thursday Digest, April 18

Here is our selection of featured articles and resources posted since Monday:

Resources

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Added by Vincent Granville on April 18, 2019 at 12:00pm — No Comments

Reinforcement Learning Explained: Overview, Comparisons and Applications in Business

Imagine you’re completing a mission in a computer game. Maybe you’re going through a military depot to find a secret weapon. You get points for the right actions (killing an enemy) and lose them for the wrong ones (falling into a pit or getting hit). If you’re playing on high difficulty, you might not conclude this task in just one attempt. Try after try, you learn which consecutive actions are needed to get out of a location safe, armed, and equipped with bonuses like extra health points or…

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Added by Kateryna Lytvynova on April 18, 2019 at 2:00am — No Comments

What is the Difference Between AI and Machine Learning

Artificial Intelligence and Machine Learning have empowered our lives to a large extent. The number of advancements made in this space has revolutionized our society and continue making society a better place to live in.

In terms of perception, both Artificial Intelligence and Machine Learning are often used in the same context which leads to confusion. AI is the concept in which machine makes smart decisions whereas Machine Learning is a sub-field of AI…

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Added by Divya Singh on April 17, 2019 at 9:00pm — No Comments

34 Great Articles and Tutorials on Clustering

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…

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Added by Vincent Granville on April 17, 2019 at 8:30am — No Comments

Free Python Data Science coding Book series

In this post, I explain

  1. How you can participate further in the free book series which we are launching based on the early experiences and
  2. Useful resources we recommend based on our experience for learning coding for Data Science (using Python – tensorflow and keras)

 

To provide some context, I posted…

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Added by ajit jaokar on April 17, 2019 at 8:06am — No Comments

“Please, explain.” Interpretability of black-box machine learning models

In February 2019 Polish government added an amendment to a banking law that gives a customer a right to receive an explanation in case of a negative credit decision. It’s one of the direct consequences of implementing GDPR in EU. This means that a bank needs to be able to explain why the loan wasn’t granted if the decision process was automatic.

In October 2018 world headlines reported about …

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Added by Michał Frącek on April 17, 2019 at 7:30am — No Comments

Maximizing Sales with Market Basket Analysis

Sales data analyses can provide a wealth of insights for any business but rarely is it made available to the public. In 2018, however, a retail chain provided Black Friday sales data on Kaggle as part of a Kaggle competition. Although the store and product lines are…

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Added by Ayumi Owada on April 17, 2019 at 6:30am — No Comments

Data Science vs. Decision Science [Infographic]

Data science has become a widely used term and a buzzword as well. It is a broad field representing a combination of multiple disciplines. However, there are adjacent areas that deserve proper attention and should not be confused with data science.…

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Added by Igor Bobriakov on April 17, 2019 at 1:30am — No Comments

Understanding Greedy Classifiers with a Real-World Example

The diverse fields in which machine learning has proven its worth is nothing short of amazing. At the heart of machine learning are the various algorithms it employs to classify data and predict outcomes. This article highlights two greedy classifiers that, albeit simple, can be extremely powerful in their own right.

 

This article is an excerpt from the book…

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Added by Packt Publishing on April 16, 2019 at 11:37pm — No Comments

An Overview of Microsoft’s Network-Based Interconnect

Learn about Microsoft's network architecture and products in this article by Florian Klaffenbach, a technology solution professional at Microsoft who is a well-known expert when it comes to hybrid cloud scenarios, cloud connectivity, and cloud environment optimization.

This article will take a closer look at Microsoft's connectivity options and how you can connect to Microsoft Cloud Services. You will learn about Microsoft's points of presence for internet peering and…

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Added by Packt Publishing on April 16, 2019 at 9:26pm — No Comments

How To Mimic Evolution For Machine Learning Tasks

Experiments

In his book, The Master Algorithm, Pedro Domingos imagines the following experiments:  

Take a building, extremely wellbuilt for two purposes: Nothing can enter and most importantly nothing can…

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Added by Paul Pinard on April 16, 2019 at 6:00am — No Comments

Using Data Visualization Graphs for Better Decision Making in Digital Marketing

Graphics reveal data. It is a reasonably new invention (compared to say complex mathematical equations) as it was only in the late 1750 to 1800 that the first graphs were invented and referred to as ‘linear arithmetic’. The art and science of data visualization has grown in leaps and bounds since then and is a vital part of informed decision making today in both the business and scientific world. To manage your digital marketing campaigns with insight, it is crucial to understand the…

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Added by Dylan Menders on April 15, 2019 at 11:24pm — No Comments

5 Dimensions to Consider for Governments Turning to AI

Artificial Intelligence might not be the newest entrant in smart technology but, its redefined usage is. It has recently gained mass popularity. Now, it is being accepted across many industries. With the general public embracing AI, government agencies are also considering this fantastic technology. AI can imitate human's decision-making skills. Thus, it has the potential to improve the decision-making ability of various applications. The AI engine is useful for multiple applications such…

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Added by Amit Dua on April 15, 2019 at 9:38pm — No Comments

Real Time Analytics and Stream Processing

   

In many business scenarios it is no longer desirable to wait hours, days or weeks for the results of analytic processes. Psychologically, people expect real-time or near real-time responses from the systems they interact with. Real-time analytics is closely tied to infrastructure issues and recent move to technologies like in-memory databases is beginning to make ‘real-time’ look achievable in the business world and not just in the computer science laboratory.…

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Added by Ajit Singh on April 15, 2019 at 10:16am — No Comments

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