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Articles by Denis Pashkov
Solving XOR problem using dynamic weights
In this short article, I would like to solve the XOR problem using a combination of both worlds using the dynamic weights approach. Introduction There are many different approaches to solve the XOR problem. Some of them are based on declarative methods, some on imperative approaches like neural networks, etc… In this article, we will try to use a combined approach to solve XOR problem. This approach can be also used to solve different search problems.
Configure AutoMapper using custom attributes
Please Sign up or sign in to vote. In this tip we gonna build a custom AutoMap builder that will configure a mapper instance based on custom attributes instead of profiles. Recently in our project, we had to map many objects from an old version to the new pdo’s and because of refactoring making profiles for each object type wasn’t the best idea.
C# using k-means algorithm for text clustering.
In this tip, you will learn how to apply K-means algorithm for text clustering using c#. Please Sign up or sign in to vote. K-means clustering is a type of unsupervised learning, which is used when you have unlabeled data (i.e., data without defined categories or groups). The goal of this algorithm is to find groups in the data, with the number of groups represented by the variable K.
Monte Carlo tree search
Using Monte Carlo simulation to find the best state inside tree of actions In other words, Monte Carlo simulation allows you to build forecasts models by randomly sampling given collection of states. Which can be very useful in building a vast range of forecasts and game ai development. At First step, we starting from State(0) we have to ask: “Is current Node is a leaf node?
C# A-Star, Graph Path-finding implementation.
A* algorithm is widely used for finding the optimal path in a graph with less cost. A-Star Algorithm works in following way: There are two lists the open list and the closed list. The open list holds potential best path nodes that have not yet been considered starting from "start" node. The closed list starts out empty and contains all nodes that have already been considered/visited. The algorithm selects the node from the open list with the lowest estimated score to reach the goal.
c# parallel tree traversing
In this tip we will traverse random data tree structure using Background Workers. At first we will implement traversal algorithm using Thread Pool and synchronization primitives to compare this approach with regular background worker.
Create And Consume JWT Tokens in c#
Create And Consume JWT Tokens in c# There are plenty materials of how to manage jwt tokens in c# environment. But I found most of them are either too complicated for the beginner or outdated. In this example, we will create and read jwt token using simple console app, so we can get a basic idea how can we use it in any type of projects. Let's Create a simple console project and add these libraries as references : Next, we will need JWT Tokens Package Now we are ready to play with Jwt Tokens :
Using Owin Middleware for mvc response logging
How to get mvc response body inside your owin middleware class With Owin Pipeline you can easily get response body stream inside your custom middleware class, but not in case of MVC, because the mvc framework doesn't stream response body thru the owin pipeline. In this Tip we will use a simple trick to get MVC response body inside your custom middleware class. First of all, let's make a helper class that will manage streams by copying the output stream into a memory stream.
This tip will show you how you can easily use k-means algorithm to group news articles using article overview text.
This tip will show you how you can easily use k-means algorithm to orginize news articles into similar groups using k-means algorithm This tip will show you how you can easily use k-means algorithm to group news articles using article overview text. k-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining.
How To Easily Use k-means Algorithm to Group News Articles using Article Overview Text
This tip will show you how you can easily use k-means algorithm to organize news articles into similar groups using k-means algorithm How To Easily Use k-means Algorithm to Group News Articles using Article Overview Text k-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining. I found k-Means clustering very handy in situations when you need to organize similar documents into groups based on document overview.
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