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Kyrylo Kolodiazhnyi's Blog (8)

Machine Learning with C++ - Mask R-CNN with PyTorch C++ Frontend

I made C++ implementation of Mask R-CNN with PyTorch C++ frontend. The code is based on PyTorch implementations from multimodallearning and Keras implementation from …

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Added by Kyrylo Kolodiazhnyi on January 21, 2019 at 7:44am — No Comments

Machine Learning with C++ - Faster R-CNN with MXNet C++ Frontend

I published implementation of Faster R-CNN with MXNet C++ Frontend. You can use this implementation as comprehensive example of using MXNet C++ Frontend, it has custom data loader for MS Coco dataset, implements custom target proposal layer as a part of the project without modification MXNet library, contains code for errors checking (Missed in current C++ API), have Eigen and NDArray integration samples. Feel free to leave comments and proposes. The code is available on Github,…

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Added by Kyrylo Kolodiazhnyi on November 5, 2018 at 11:30pm — No Comments

Machine Learning with C++ - Classification with Dlib

Dlib is an open source C++ framework containing various machine learning algorithms and many other complementary stuff which can be used for image processing, computer vision, linear algebra calculations and many other things. It has very good documentation and a lot of useful examples. In this post I will show how to use this library for solving a classification problem on Iris data…

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Added by Kyrylo Kolodiazhnyi on August 7, 2018 at 7:03am — No Comments

Machine Learning with C++ - Classification with Shark-ML

Shark-ML is an open-source machine learning library which offers a wide range of machine learning algorithms together with nice documentation, tutorials and samples. In this post I will show how to use this library for solving classification problem, with two different algorithms SVM and Random Forest. This post will tell you about how to use API for:

1. Loading data

2. Performing normalization and dimension…

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Added by Kyrylo Kolodiazhnyi on July 30, 2018 at 2:40am — No Comments

Machine Learning with C++ - Classification with Shogun library

Hello, with this article I'm starting series of articles about full featured C++ Machine Learning frameworks . This articles covers how to use Shogun library for solving classification problem. Shogun is an open-source machine learning library that offers a wide range of machine learning algorithms. From my point of view it's not very popular among professionals, but it have a lot of fans among enthusiasts and…

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Added by Kyrylo Kolodiazhnyi on July 17, 2018 at 11:17am — No Comments

Machine Learning with C++ - Polynomial regression with Eigen

Hello, this is my third article about how to use modern C++ for solving machine learning problems. This time I will show how to make a model for polynomial regression problem , with well known linear algebra library called Eigen.

Eigen was chosen because it is widely used and has a long history, it is highly optimized for CPUs, and it is a header only library. One of the famous project using it is…

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Added by Kyrylo Kolodiazhnyi on June 11, 2018 at 11:00pm — No Comments

Machine Learning with C++ - Polynomial Regression on GPU

Hello, this is my second article about how to use modern C++ for solving machine learning problems. This time I will show how to make a model for polynomial regression problem described in previous article, but now with another library which allows you to use your GPU easily.

For…

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Added by Kyrylo Kolodiazhnyi on May 30, 2018 at 1:30am — No Comments

Machine Learning with C++ - Polynomial Regression (CPU)

There are a lot of articles about how to use Python for solving Machine Learning problems, with this article I start series of materials on how to use modern C++ for solving same problems and which libraries can be used. I assume that readers are already familiar with Machine Learning concepts and will concentrate on programming issues only.

The first part is about creating Polynomial Regression model with XTensor library. This is C++ library for numerical analysis with…

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Added by Kyrylo Kolodiazhnyi on April 17, 2018 at 12:30am — 6 Comments

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