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Burak Himmetoglu
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  • Santa Barbara
  • United States
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Latest Activity

Burak Himmetoglu liked Ahmet Taspinar's blog post Using Convolutional Neural Networks to detect features in sattelite images
Monday
Mark Pickett liked Burak Himmetoglu's blog post Pancake: A Python package for model stacking
Jan 24
Srikanth Ramakrishna liked Burak Himmetoglu's blog post Pancake: A Python package for model stacking
Jan 18
Burak Himmetoglu posted a blog post

Pancake: A Python package for model stacking

In a previous post, I have provided a discussion of model stacking, a popular approach in data science competitions for boosting predictive performance. Since then, the post has attracted some attention, so I have decided to put together a Python package which provides a simple API to stack models with minimal effort.In this post, I will present the …See More
Jan 17
Burak Himmetoglu's blog post was featured

Pancake: A Python package for model stacking

In a previous post, I have provided a discussion of model stacking, a popular approach in data science competitions for boosting predictive performance. Since then, the post has attracted some attention, so I have decided to put together a Python package which provides a simple API to stack models with minimal effort.In this post, I will present the …See More
Jan 17
Stephan O'Bryan liked Burak Himmetoglu's blog post An overview of feature selection strategies
Sep 25, 2018
Burak Himmetoglu posted a blog post

An overview of feature selection strategies

IntroductionFeature selection and engineering are the most important factors which affect the success of predictive modeling. This remains true even today despite the success of deep learning, which comes with automatic feature engineering. Parsimonious and interpretable models provide simple insights into business problems and therefore they are deemed very valuable. Furthermore, in many occasions the underlying size and structure of the data being analyzed may not allow the use of complex…See More
Sep 20, 2018
Burak Himmetoglu's blog post was featured

An overview of feature selection strategies

IntroductionFeature selection and engineering are the most important factors which affect the success of predictive modeling. This remains true even today despite the success of deep learning, which comes with automatic feature engineering. Parsimonious and interpretable models provide simple insights into business problems and therefore they are deemed very valuable. Furthermore, in many occasions the underlying size and structure of the data being analyzed may not allow the use of complex…See More
Sep 20, 2018
Burak Himmetoglu and Mirio De Rosa are now friends
Sep 19, 2018
Nitin Pasumarthy liked Burak Himmetoglu's blog post Time series classification with Tensorflow
Jun 30, 2018
Hendra Bunyamin commented on Burak Himmetoglu's blog post Yet another introduction to Neural Networks
"Hello Vincent,    Thank You so much for the update! Best, Hendra"
Jun 21, 2018
Vincent Granville commented on Burak Himmetoglu's blog post Yet another introduction to Neural Networks
"Hi Hendra, the link has been fixed."
Jun 16, 2018
Hendra Bunyamin commented on Burak Himmetoglu's blog post Yet another introduction to Neural Networks
Jun 16, 2018
Filip Van Grembergen liked Burak Himmetoglu's blog post Time series classification with Tensorflow
May 19, 2018
Mirio De Rosa liked Burak Himmetoglu's blog post Stacking models for improved predictions: A case study for housing prices
Apr 12, 2018
Teena Thomas Vattukalathil liked Burak Himmetoglu's blog post Time series classification with Tensorflow
Feb 23, 2018

Profile Information

Professional Status
Consultant
Your Job Title:
HPC Specialist
Interests:
Finding a new position, Networking

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Burak Himmetoglu's Blog

Pancake: A Python package for model stacking

Posted on January 14, 2019 at 10:42pm 0 Comments

In a previous post, I have provided a discussion of model stacking, a popular approach in data science competitions for boosting predictive performance. Since then, the post has attracted some attention, so I have decided to put together a Python package which provides a simple API to stack models with minimal effort.

In this post, I will present the …

Continue

An overview of feature selection strategies

Posted on September 19, 2018 at 9:58pm 0 Comments

Introduction

Feature selection and engineering are the most important factors which affect the success of predictive modeling. This remains true even today despite the success of deep learning, which comes with automatic feature engineering. Parsimonious and interpretable models provide simple insights into business problems and therefore they are deemed very valuable. Furthermore, in many occasions the underlying size and structure of the data being analyzed may not allow the use…

Continue

Time series classification with Tensorflow

Posted on August 22, 2017 at 7:00am 6 Comments

Time-series data arise in many fields including finance, signal processing, speech recognition and medicine. A standard approach to time-series problems usually requires manual engineering of features which can then be fed into a machine learning algorithm. Engineering of features generally requires some  domain knowledge of the discipline where the data has originated from. For example, if one is dealing with signals (i.e. classification of EEG signals), then possible features would involve…

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Feature Engineering with Tidyverse

Posted on April 10, 2017 at 7:30am 0 Comments

In this blog post, I will discuss feature engineering using the Tidyverse collection of libraries. Feature engineering is crucial for a variety of reasons, and it requires some care to produce any useful outcome. In this post, I will consider a dataset that contains description of crimes in San Francisco between…

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