Data is big
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Data is big
"The future is here. It's just not evenly distributed yet." - William Gibson     :::: Follow this topic for fresh resources and ideas related to Data Science, Machine Learning, Algorithms and #bigdata :::: <a href="http://www.dataisbig.co" rel="nofollow">http://www.dataisbig.co</a>/
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Robotics Institute Seminar Series - YouTube

Robotics Institute Seminar Series - YouTube | Data is big | Scoop.it
A seminar series hosted by Carnegie Mellon University's Robotics Institute.
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A seminar series hosted by Carnegie Mellon University's Robotics Institute.
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ReinforcementLearning: A package for replicating human behavior in R

ReinforcementLearning: A package for replicating human behavior in R | Data is big | Scoop.it
Nicolas Proellochs and Stefan Feuerriegel 2017-04-06 Introduction Reinforcement learning has recently gained a great deal of traction in studies that call for
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Explained Visually

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Explained Visually (EV) is an experiment in making hard ideas intuitive inspired the work of Bret Victor's Explorable Explanations.
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Unpacking Assignment %<-% 

The zeallot package defines an operator for unpacking assignment, sometimes called parallel assignment or destructuring assignment in other programming languages. The operator is written as %<-% and used like this.

{ lat : lng } %<-% list(38.061944, -122.643889)
The result is that the list is unpacked into its elements, and the elements are assigned to lat and lng.
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The most comprehensive Data Science learning plan for 2017

This article features a year long learning path for aspiring data scientist, intermediate & transitioner to progress in data science industry for R & Python
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How to find daily good deals online, automatically with R?

How to find daily good deals online, automatically with R? | Data is big | Scoop.it
As defined here, “a data scientist is someone who is better at statistics than any software engineer and better at software engineering than any statistician.” Therefore, this blog post focuses on…
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Deep Learning Gallery - a curated list of awesome deep learning projects

Deep Learning Gallery - a curated list of awesome deep learning projects | Data is big | Scoop.it
Deep Learning Gallery - a curated list of awesome deep learning projects
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A Guide to Deep Learning by YerevaNN

Deep learning is a fast-changing field at the intersection of computer science and mathematics. It is a relatively new branch of a wider field called machine learning.
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Daniel Oratokhai's curator insight, January 2, 5:35 AM

A Guide to Deep Learning by YerevaNN

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Practical Deep Learning For Coders—18 hours of lessons for free

Practical Deep Learning For Coders—18 hours of lessons for free | Data is big | Scoop.it
Welcome to fast.ai's 7 week course, "Practical Deep Learning For Coders, Part 1", taught by Jeremy Howard (Kaggle's #1 competitor 2 years running, and founder of Enlitic). Learn how to build state of the art models without needing graduate-level math—but also without dumbing anything down. Oh and one other thing... it's totally free!
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Daniel Oratokhai's curator insight, January 3, 1:01 AM

Practical Deep Learning For Coders—18 hours of lessons for free

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State of the art deep learning model for question answering

State of the art deep learning model for question answering | Data is big | Scoop.it
We introduce the Dynamic Coattention Network, a state of the art question answering deep learning model that significantly outperforms all existing systems on the Stanford Question Answering dataset.
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[1206.4634] Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting

Oriental ink painting, called Sumi-e, is one of the most appealing painting styles that has attracted artists around the world. Major challenges in computer-based Sumi-e simulation are to abstract complex scene information and draw smooth and natural brush strokes. To automatically find such strokes, we propose to model the brush as a reinforcement learning agent, and learn desired brush-trajectories by maximizing the sum of rewards in the policy search framework. We also provide elaborate design of actions, states, and rewards tailored for a Sumi-e agent. The effectiveness of our proposed approach is demonstrated through simulated Sumi-e experiments.
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AudioSet

A large-scale dataset of manually annotated audio eventsAudioSet consists of an expanding ontology of 632 audio event classes and a collection of 2,084,320 human-labeled 10-second sound clips drawn from YouTube videos. The ontology is specified as a hierarchical graph of event categories, covering a wide range of human and animal sounds, musical instruments and genres, and common everyday environmental sounds. By releasing AudioSet, we hope to provide a common, realistic-scale evaluation task for audio event detection, as well as a starting point for a comprehensive vocabulary of sound events.
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A large-scale dataset of manually annotated audio events AudioSet consists of an expanding ontology of 632 audio event classes and a collection of 2,084,320 human-labeled 10-second sound clips drawn from YouTube videos.
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Explaining the decisions of machine learning algorithms | StatsBlogs.com | All About Statistics

Explaining the decisions of machine learning algorithms | StatsBlogs.com | All About Statistics | Data is big | Scoop.it
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Machine Learning Boot Camp - live and archived videos Jan. 23 – Jan. 27, 2017

Machine Learning Boot Camp - live and archived videos Jan. 23 – Jan. 27, 2017 | Data is big | Scoop.it
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Machine Learning Boot Camp Jan. 23 – Jan. 27, 2017
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Introduction to Forecasting with ARIMA in R

Data Scientist Ruslana Dalinina explains how to forecast demand with ARIMA in R. Learn how to fit, evaluate, and iterate an ARIMA model with this tutorial.
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46 Questions on SQL to test a data science professional (Skilltest Solution)

This article features 46 questions on SQL every data science professional should know. Questions related to DDL, DML, Joins, Update, Drop, where, Groupby
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Making an R based ML model accessible through a simple API

Building an accurate machine learning (ML) model is a feat on its own. But once you’re there, you still need to find a way to make the model accessible t
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Analyzing Genomics Data at Scale using R, AWS Lambda, and Amazon API Gateway | AWS Compute Blog

Analyzing Genomics Data at Scale using R, AWS Lambda, and Amazon API Gateway | AWS Compute Blog | Data is big | Scoop.it
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Learning Reinforcement Learning (With Code, Exercises and Solutions) | Open Data Science

Skip all the talk and go directly to the Github Repo with code and exercises. WHY STUDY REINFORCEMENT LEARNING Reinforcement Learning is one of the fields I’m
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What I Learned Recreating One Chart Using 24 Tools - Features - Source: An OpenNews project

What I Learned Recreating One Chart Using 24 Tools - Features - Source: An OpenNews project | Data is big | Scoop.it
Source - Journalism Code, Context & Community
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