After 210 days, 600 commits, tens of debugging nights, and thousands of messages in the project chat, I finally released AngouriMath 1.2.

This is an open-source symbolic algebra library for C# and F#, maybe it is interesting for someone?

Recently we found out that the new version of the fheroes2 project was released. In our company there are many fans of Heroes of Might and Magic game series. So, we couldn't pass it up and checked the project by PVS-Studio.

Introduction

Introduction

In my opinion transaction management is a really important topic for each backend developer. In general, people don’t pay attention to it while using Spring framework.

But I think, it is important to know how to use transactions properly. Because sometimes can happen that there was an exception thrown inside your method, but transaction was not rolled back and it is not clear why? Or some other “strange” cases.

Intro

PXE is a great solution for booting a diskless computer (or a computer without an OS installed). This method is often used for terminal stations and OS mass installation.

Stock ubuntu (16.04) in pxe-mode can mount rootfs only from NFS. But this is not a great idea: any difficulties with the network/NFS server and the user gets problems.

In my opinion, it's best to use other protocols, such as http/ftp. Once booting, you will have an independent system

Deadlocks

Many thanks to Elena Indrupskaya for the translation.

JSONPath

Source: Google Images

You've optimized all of the low-hanging fruits of your game. Except that you didn't. You missed a sneaky, non-so-obvious spot: optimizing your Unity Scene Hierarchy.

What's the crack with the hierarchy now?

I want to show you something.

<dependency>
     <groupId>com.github.michaelgantman</groupId>
     <artifactId>MgntUtils</artifactId>
     <version>1.5.1.2</version>
</dependency>

 <dependency>
     <groupId>com.github.michaelgantman</groupId>
     <artifactId>MgntUtils</artifactId>
     <version>1.5.1.2</version>
     <classifier>javadoc</classifier>
</dependency>

<dependency>
     <groupId>com.github.michaelgantman</groupId>
     <artifactId>MgntUtils</artifactId>
     <version>1.5.1.2</version>
     <classifier>sources</classifier>
</dependency>

• Map

Parameters used

Working

How to implement?

const map = (transformFunction, array1) =>
  array1.reduce((newArray1, xyz) => 
{
	newArray1.push(transformFunction(xyz));

	return newArray1;
  }, 
[]
);

Use case:

const double = (x) => x * 2;
const reverseString = (string) =>
  string
	.split('')
	.reverse()
	.join('');

map(double, [200, 300, 400]);

Output: [400, 600, 800]

map(reverseString, ['Hello Alka', 'I love cooking']);
// ['alkA olleH', ‘gnikooc evol I']

Future Software Development Is Here!

Let’s Try Out With Some Code

X=np.array([[0,1,1,0],[0,1,1,1],[1,0,0,1]])
y=np.array([[0],[1],[1]])

def sigmoid ():
   return 1/(1 + np.exp(-x))
def derivatives_sigmoid ():
   return x * (1-x)

epoch=10000
lr=0.1
inputlayer_neurons = X.shape[1]
hiddenlayer_neurons = 3
output_neurons = 1

wh=np.random.uniform(size=(inputlayer_neurons,hiddenlayer_neurons))
bh=np.random.uniform(size=(1,hiddenlayer_neurons))
wout=np.random.uniform(size=(hiddenlayer_neurons,output_neurons))
bout=np.random.uniform(size=(1,output_neurons))

ML.NET Model Builder

• Image classification scenario – locally train image classification models with your own images
• Try your model – make predictions on sample input data right in the UI

• .NET Core 3.1 Preview 2 SDK and Runtime
• Docker images

• .NET Core 3.1 release notes
• GitHub release
• GitHub issue for Preview 2

• UI-dense forms over data (FOD) applications
• Responsive low-latency UI
• Applications that need to run offline/disconnected
• Applications with dependencies on custom device drivers