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Emmanuelle Rieuf's Blog (170)

The 10 Algorithms Machine Learning Engineers Need to Know

This article was written by James Le.

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples…

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Added by Emmanuelle Rieuf on June 19, 2017 at 2:30pm — No Comments

Artificial Intelligence 2017: Top 100 Influencers, Brands and Publications

This article was written by Thomas Legoff. 

Artificial intelligence – or AI – is a true part of our world, as well as a substantial hub of interest for science and business. Companies are ferociously investing in, engaging in and including artificial intelligence in their operations. It is a fascinating technology that enables new options for companies, from detecting security intrusions…

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Added by Emmanuelle Rieuf on June 5, 2017 at 8:30am — No Comments

Image Segmentation using deconvolution layer in Tensorflow

This article was written by Koustuch on CV-Tricks. 
In this series of post, we shall learn the algorithm for image segmentation and implementation of the same using Tensorflow. This is the first part of the series where we shall focus on understanding and be implementing a deconvolutional/fractional-strided-convolutional layer in…
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Added by Emmanuelle Rieuf on June 5, 2017 at 7:30am — 1 Comment

5 data science books you should read in 2017

This article comes from Coursera Blog.

The Data Buzz series brings you a regular roundup of what’s trending in data science.

As data-driven technologies are more and more integrated into everyday life, knowledge of data science is becoming increasingly valuable. Here are five books to boost your data literacy – whether you’re new to the field or a seasoned expert.…

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Added by Emmanuelle Rieuf on May 15, 2017 at 10:30am — No Comments

Estimating the Age of a Person with AI Techniques

Abstract:

In this paper, we propose hybrid principal component analysis (HPCA) to extract appearance feature of a face and inter-age group variation-based classifier (IAGVC) with regression to estimate age of a person. The proposed age estimation system is robust…

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Added by Emmanuelle Rieuf on May 14, 2017 at 3:30pm — No Comments

An executive’s guide to machine learning

This article was written by Dorian Pyle and Cristina San Jose on McKinsey&Company. Dorian Pyle is a data expert in McKinsey’s Miami office, and Cristina San Jose is a principal in the Madrid office.

It’s no longer the preserve of artificial-intelligence researchers and born-digital companies like Amazon, Google, and Netflix.

Machine learning is based on algorithms…

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Added by Emmanuelle Rieuf on May 11, 2017 at 6:30am — No Comments

How well do facial recognition algorithms cope with a million strangers?

This article was written by Jennifer Langston. Co-authors include UW computer science and engineering professor Steve Seitz, undergraduate student and web developer Evan Brossard and former student Daniel Miller.…

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Added by Emmanuelle Rieuf on May 11, 2017 at 6:30am — No Comments

New Trends in Artificial Intelligence & Machine Learning

This article was written by Hardik Gohil, Sr Content Writer. 

Artificial Intelligence has effectively convinced its necessity to the entire world by performing excellently in various industries. Almost all the industries including manufacturing, healthcare, construction, online retail, etc. are adapting to the reality of IoT to leverage its advantages.

Machine learning technology is…

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Added by Emmanuelle Rieuf on May 10, 2017 at 11:30am — No Comments

A curated list of resources dedicated to bayesian deep learning

This article comes from GitHub.

A curated list of resources dedicated to bayesian deep learning.

2013:

  1. Deep gaussian processes|Andreas C. Damianou,Neil D. Lawrence|2013 -- Source:…
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Added by Emmanuelle Rieuf on May 10, 2017 at 7:30am — No Comments

Time Series Analysis With Generalized Additive Models

This article comes from Algobeans Layman tutorials in analytics. 

Whenever you spot a trend plotted against time, you would be looking at a time series. The de facto choice for studying financial market performance and weather forecasts, time series are one of the most pervasive analysis techniques because of its inextricable relation to time—we are always interested to foretell the future.

Temporal Dependent Models

One intuitive way to make…

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Added by Emmanuelle Rieuf on April 29, 2017 at 3:00pm — No Comments

Machine Learning Skills Among Data Scientists

This article was posted by Bob E. Hayes on Customer think. Bob, PhD is Chief Research Officer at Appuri. He a scientist, blogger and author on CEM and data science.

Data scientists have a variety of different skills that they bring to bear on Big Data projects. These skills cut across Subject Matter Expertise, Technology, Programming, Math & Modeling and Statistics. One valuable…

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Added by Emmanuelle Rieuf on April 18, 2017 at 9:00am — No Comments

Ranking All 50 States by Average Credit Score of its Citizens

This article was contributed by Statistical Future.

Whether you want it to or not, credit and its availability plays a major role in everyone’s life, whether or not you directly experience it. For the average person, credit scores are mainly going to be used for three things: buying a house, buying a car, and using credit cards.

In the world of business, things get exponentially more complicated and it also ended up leading to a horrible housing crash and recession…

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Added by Emmanuelle Rieuf on April 15, 2017 at 9:30am — 1 Comment

The Startup Founder’s Guide to Analytics

This article was written by Tristan Handy. Tristan is the founder and president of Fishtown Analytics: helping startups implement advanced analytics.

I’m very confident of that, because today, everyone needs analytics. Not just product, not just marketing, not just finance… sales, fulfillment, everyone at a startup needs analytics today.…

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Added by Emmanuelle Rieuf on April 10, 2017 at 11:00am — No Comments

Implement an ARIMA model using statsmodels (Python)

In this article was written by Michael Grogan. Michael is a data scientist and statistician, with a profound passion for statistics and programming.

In a previous tutorial, I elaborated on how an ARIMA model can be implemented using R. The model was fitted on a stock price dataset, with a (0,1,0) configuration being used for ARIMA.

Here, I detail how to implement an ARIMA model in Python using the…

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Added by Emmanuelle Rieuf on April 9, 2017 at 11:00am — No Comments

Understanding the limits of deep learning

This article was written by Mariya Yao. Mariya is the Head of Design and Engagement at TOPBOTS.com, a media and marketing firm specializing in chatbots and conversational agents.

Artificial intelligence has reached peak hype. News outlets report that companies have replaced workers with IBM Watson and that algorithms are beating doctors at diagnoses. New AI startups pop up everyday, claiming to solve all your…

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Added by Emmanuelle Rieuf on April 8, 2017 at 8:30am — No Comments

Introduction to Anomaly Detection

In this article, Data Scientist Pramit Choudhary provides an introduction to both statistical and machine learning-based approaches to anomaly detection in Python. Introduction: Anomaly Detection 

This overview is intended for beginners in the fields of data science and machine learning.…

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Added by Emmanuelle Rieuf on April 6, 2017 at 12:30pm — No Comments

Implementing the Gradient Descent Algorithm in R

This article was posted by S. Richter-Walsh

A Brief Introduction: 

Linear regression is a classic supervised statistical technique for predictive modelling which is based on the linear hypothesis:

y = mx + c

where is the response or outcome variable, m is the gradient of the linear…

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Added by Emmanuelle Rieuf on April 4, 2017 at 6:00pm — No Comments

Build a Recurrent Neural Net in 5 min

This video was posted on Youtube by Sirajology. He explains the basics of recurrent neural networks. Then you code your own RNN in 80 lines of python (plus white-space) that predicts the sum of two binary numbers after training.

Code for this video:…

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Added by Emmanuelle Rieuf on April 4, 2017 at 12:00pm — No Comments

Book: Java Deep Learning Essentials

Book Description

AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Deep Learning algorithms are being used across a broad range of industries – as the…

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Added by Emmanuelle Rieuf on April 2, 2017 at 6:31pm — No Comments

Book: Advanced R (Chapman & Hall/CRC The R Series)

An Essential Reference for Intermediate and Advanced R Programmers

Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of…

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Added by Emmanuelle Rieuf on March 30, 2017 at 3:30am — No Comments

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