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Kevin Jacobs's blog post was featured

GRU implementation in TensorFlow

MLPs (Multi-Layer Perceptrons) are great for many classification and regression tasks, but it is hard for MLPs to do classification and regression on sequences. In this code tutorial, a GRU is implemented in TensorFlow.IntroductionA sequence is an ordered set of items and sequences appear everywhere. In the stock market, the closing price is a sequence. Here, time is the ordering. In sentences, words follow a certain ordering. Therefore, sentences can be viewed as sequences. A gigantic MLP…See More
Aug 28
Kevin Jacobs posted a blog post

GRU implementation in TensorFlow

MLPs (Multi-Layer Perceptrons) are great for many classification and regression tasks, but it is hard for MLPs to do classification and regression on sequences. In this code tutorial, a GRU is implemented in TensorFlow.IntroductionA sequence is an ordered set of items and sequences appear everywhere. In the stock market, the closing price is a sequence. Here, time is the ordering. In sentences, words follow a certain ordering. Therefore, sentences can be viewed as sequences. A gigantic MLP…See More
Aug 28
Kevin Jacobs liked Kevin Jacobs's blog post Apache Flink: The Next Distributed Data Processing Revolution?
Jul 11
Kevin Jacobs updated their profile
Jul 11
Kevin Jacobs's blog post was featured

Apache Flink: The Next Distributed Data Processing Revolution?

By Kevin Jacobs, Data Blogger.Disclaimer: The results are valid only in the case when network attached storage is used in the computing cluster.The amount of data is growing significantly over the past few years. It is not feasible for only one machine to process large amounts of data. Therefore, the need of distributed data processing frameworks is growing. It all started back in 2011 when the first version of Apache Hadoop was released (version 1.0.0). The Hadoop framework is capable of…See More
Jul 11
Kevin Jacobs posted a blog post

Apache Flink: The Next Distributed Data Processing Revolution?

By Kevin Jacobs, Data Blogger.Disclaimer: The results are valid only in the case when network attached storage is used in the computing cluster.The amount of data is growing significantly over the past few years. It is not feasible for only one machine to process large amounts of data. Therefore, the need of distributed data processing frameworks is growing. It all started back in 2011 when the first version of Apache Hadoop was released (version 1.0.0). The Hadoop framework is capable of…See More
Jul 11

Profile Information

Short Bio
Kevin Jacobs is a certified Data Scientist and blog writer for Data Blogger (www.data-blogger.com). He is passionate about any project that involves large amounts of data and statistical data analysis. Kevin can be reached using Twitter (@kmjjacobs), LinkedIn (kevinjacobs1991) or via e-mail:
[email protected]
My Web Site Or LinkedIn Profile
http://www.data-blogger.com/looking-for-a-data-scientist/
Field of Expertise
Analytics, Data Integration, Visualization, Big Data, Data Science
Professional Status
Consultant
Years of Experience:
5
Your Company:
ovoWeb
Industry:
ICT
Your Job Title:
Data Scientist
How did you find out about DataScienceCentral?
Via Google and students.
Interests:
Finding a new position, Networking
What is your Favorite Data Mining or Analytical Website?
http://datasciencecentral.com
What Other Analytical Website do you Recommend?
http://kdnuggets.com

Kevin Jacobs's Blog

GRU implementation in TensorFlow

Posted on August 27, 2017 at 3:00am 0 Comments

MLPs (Multi-Layer Perceptrons) are great for many classification and regression tasks, but it is hard for MLPs to do classification and regression on sequences. In this code tutorial, a GRU is implemented in TensorFlow.

Introduction

A sequence is an ordered set of items and sequences appear everywhere. In the stock market, the closing price is a sequence. Here, time is the ordering. In sentences, words follow a certain ordering. Therefore, sentences can be viewed as…

Continue

Apache Flink: The Next Distributed Data Processing Revolution?

Posted on July 8, 2017 at 11:30am 0 Comments

By Kevin Jacobs, Data Blogger.

Disclaimer: The results are valid only in the case when network attached storage is used in the computing cluster.

The amount of data is growing significantly over the past few years. It is not feasible for only one machine to process large amounts of data. Therefore, the need of distributed data processing frameworks is growing. It all started back in 2011 when the first version of Apache Hadoop was released (version 1.0.0). The…

Continue

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