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20 white papers and power point presentations

20 white papers and power point presentations | Data is big | Scoop.it
Posted on AnalyticBridge over the last few years, related to analytics, data science, big data, statistics, visualization. Feel free to add yours.

Introductio…
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Data is big
&amp;amp;quot;The future is here. It's just not evenly distributed yet.&amp;amp;quot; - 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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Uber Engineering's Tech Stack: The Foundation

Uber Engineering's Tech Stack: The Foundation | Data is big | Scoop.it
Uber’s mission is transportation as reliable as running water, everywhere, for everyone. Here's the first of a two-part series on the tech stack that Uber Engineering uses to make this happen.
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How to Implement a Machine Learning Algorithm

How to Implement a Machine Learning Algorithm | Data is big | Scoop.it
Implementing a machine learning algorithm in code can teach you a lot about the algorithm and how it works. In this post you will learn how to be effective at implementing machine learning algorithms and how to maximize your learning from these projects. Benefits of Implementing Machine Learning Algorithms You can use the implementation of …
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twiml - Podcast - This Week in Machine Learning & AI

Technologies covered include: machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, deep learning and more.

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This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the worlds of machine learning and artificial intelligence. We discuss the latest developments in research, technology, and business and explore interesting projects from across the web.
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A Complete Tutorial on Tree Based Modeling from Scratch (in R & Python)

A Complete Tutorial on Tree Based Modeling from Scratch (in R & Python) | Data is big | Scoop.it
This tutorial explains tree based modeling which includes decision trees, random forest, bagging, boosting, ensemble methods in R and python
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Building a data science portfolio: Storytelling with data

Building a data science portfolio:  Storytelling with data | Data is big | Scoop.it
Learn how to build the first component in a well-rounded data science portfolio by learning how to tell stories with data.
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A 'Brief' History of Neural Nets and Deep Learning, Part 1

A 'Brief' History of Neural Nets and Deep Learning, Part 1 | Data is big | Scoop.it
The beginning of a story spanning half a century, about how we learned to make computers learn
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Text Mining with R on Vikings episode scripts - Networkx

Text Mining with R on Vikings episode scripts - Networkx | Data is big | Scoop.it
Synopsis I'm a hugh fan of the TV show Vikings. I thought it would be cool to mine the tv shows scripts to figure out which terms are the most …
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Google researchers teach AIs to see the important parts of images — and tell you about them

Google researchers teach AIs to see the important parts of images — and tell you about them | Data is big | Scoop.it

This week is the Computer Vision and Pattern Recognition conference in Las Vegas, and Google researchers have several accomplishments to present.  

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An overview of gradient descent optimization algorithms

This blog post looks at variants of gradient descent and the algorithms that are commonly used to optimize them.
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Venn Diagram Comparison of Boruta, FSelectorRcpp and GLMnet Algorithms

Venn Diagram Comparison of Boruta, FSelectorRcpp and GLMnet Algorithms | Data is big | Scoop.it
Venn Diagram Comparison of Boruta, FSelectorRcpp and GLMnet Algorithms
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DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations

Recent advances in clothes recognition have been driven by the construction of clothes datasets. Existing datasets
are limited in the amount of annotations and are difficult to cope with the various challenges in real-world applications. In this work, we introduce DeepFashion, a large-scale clothes dataset with comprehensive annotations. It contains over 800,000 images, which are richly annotated with massive attributes, clothing landmarks, and correspondence of images taken under different scenarios including store, street snapshot, and consumer. Such rich annotations enable the development of powerful algorithms in clothes recognition and facilitating future researches. To demonstrate the advantages of DeepFashion, we propose a new deep model, namely FashionNet, which learns clothing features by jointly predicting clothing attributes and landmarks. The estimated landmarks are then employed to pool or gate the learned features. It is optimized in an iterative manner. Extensive experiments demonstrate the effectiveness of FashionNet and the usefulness of DeepFashion.>
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Reinforcement Learning - Course

Reinforcement learning is a paradigm that aims to model the trial-and-error learning process that is needed in many problem situations where explicit instructive signals are not available. It has roots in operations research, behavioral psychology and AI. The goal of the course is to introduce the basic mathematical foundations of reinforcement learning, as well as highlight some of the recent directions of research.
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Approaching (Almost) Any Machine Learning Problem | Abhishek Thakur

Approaching (Almost) Any Machine Learning Problem | Abhishek Thakur | Data is big | Scoop.it
An average data scientist deals with loads of data daily. Some say over 60-70% time is spent in data cleaning, munging and bringing data to a suitable format such that machine learning models can b…
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How To Identify Patterns in Time Series Data: Time Series Analysis

How To Identify Patterns in Time Series Data: Time Series Analysis | Data is big | Scoop.it
In the following topics, we will first review techniques used to identify patterns in time series data (such as smoothing and curve fitting techniques and autocorrelations), then we will introduce a general class of models that can be used to represent time series data and generate predictions (autoregressive and moving average models). Finally, we will review some simple but commonly used modeling and forecasting techniques based on linear regression. For more information see the topics below.
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Data Science - all the fun stuff in one place

Data Analysis, Machine Learning, Python, Visualization, Stats, Tutorials, Blogs, Algorithms, etc. In short, all the fun stuff in one place!
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Clustering Algorithms: From Start To State Of The Art

Clustering algorithms are very important to unsupervised learning and are key elements of machine learning in general. These algorithms give meaning to data that are not labelled and help find structure in chaos. But not all clustering algorithms are created equal; each has its own pros and cons. In this article, Toptal Freelance Software Engineer Lovro Iliassich explores a heap of clustering algorithms, from the well known K-Means algorithm to the elegant, state-of-the-art Affinity Propagation technique.
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Introducing the p-hacker app: Train your expert p-hacking skills

Introducing the p-hacker app: Train your expert p-hacking skills | Data is big | Scoop.it
  Start the p-hacker app! My dear fellow scientists! “If you torture the data long enough, it will confess.” This aphorism, attributed to
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