• Regeln für den Video-Bereich:

    In den Börsenbereich gehören nur Angebote die bereits den Allgemeinen Regeln entsprechen.

    Einteilung

    - Folgende Formate gehören in die angegeben Bereiche:
    - Filme: Encodierte Filme von BluRay, DVD, R5, TV, Screener sowie Telesyncs im Format DivX, XviD und x264.
    - DVD: Filme im Format DVD5, DVD9 und HD2DVD.
    - HD: Encodierte Filme mit der Auflösung 720p oder darüber von BluRay, DVD, R5, TV, Screener sowie Telesyncs im Format x264.
    - 3D: Encodierte Filme von BluRay, die in einem 3D Format vorliegen. Dies gilt auch für Dokus, Animation usw.
    - Serien: Cartoon/Zeichentrick, Anime, Tutorials, Dokumentationen, Konzerte/Musik, Sonstiges sind demnach in die entsprechenden Bereiche einzuordnen, auch wenn sie beispielsweise im High Definition-Format oder als DVD5/DVD9/HD2DVD vorliegen. Ausnahme 3D.
    - Bereich Englisch: Englische Releases gehören immer in diesen Bereich.
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    Angebot/Beitrag erstellen

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    - Bei einem Sammelthread für eine Staffel entfällt aus dem Releasename natürlich der Name der Folge. Beispiel: Die Simpsons S21 German DVDRip XviD - ITG
    - Dementsprechend sind also u.a. verboten: Erweiterungen wie "Tipp", "empfehlenswert", "only", "reup", usw. / jegliche andere Zusatzinformation oder Ergänzung, welche nicht in obiger Beschreibung zu finden ist.

    Aufbau des Angebots und Threadtitel

    Der Titel nach folgendem Muster erstellt zu werden. <Name> [3D] [Staffel] [German] <Jahr> <Tonspur> [DL] [Auflösung] <Quelle> <Codec> - <Group>
    Beispiel: The Dark Knight German 2008 AC3 DVDRip XviD - iND
    Beispiel: The Dark Knight 2008 DTS DL BDRip x264 - iND
    Beispiel: The Dark Knight 2008 AC3 DL BDRip XviD - iND
    Beispiel: The Dark Knight German 2008 AC3 720p BluRay x264 iND
    Beispiel: The Dark Knight 2008 DTS DL 1080p BluRay x264 iND
    Beispiel: Die Simpsons S01 German AC3 DVDRip XviD iND
    Beispiel: Die Simpsons S20 German AC3 720p BluRay x264 iND
    Beispiel: Sword Art Online II Ger Sub 2014 AAC 1080p WEBRip x264 - peppermint
    Entsprechend sind also u.a. verboten: Sonderzeichen wie Klammern, Sterne, Ausrufezeichen, Unterstriche, Anführungszeichen / Erweiterungen wie "Tipp", "empfehlenswert", "only", "reup", usw. / jegliche andere Zusatzinformation oder Ergänzung, welche nicht in obiger Beschreibung zu finden ist
    Ausnahmen hiervon können in den Bereichen geregelt sein.

    Die Beiträge sollen wie folgt aufgebaut werden:
    Überschrift entspricht dem Threadtitel
    Cover
    kurze Inhaltsbeschreibung
    Format, Größe, Dauer sind gut lesbar für Downloader außerhalb des Spoilers zu vermerken
    Nfo sind immer Anzugeben und selbige immer im Spoiler in Textform.
    Sind keine Nfo vorhanden z.B. Eigenpublikationen, sind im Spoiler folgende Dateiinformationen zusätzlich anzugeben :
    Quelle
    Video (Auflösung und Bitrate)
    Ton (Sprache, Format und Bitrate der einzelnen Spuren)
    Untertitel (sofern vorhanden)
    Hosterangabe in Textform außerhalb eines Spoiler mit allen enthaltenen Hostern.
    Bei SD kann auf diese zusätzlichen Dateiinformationen verzichtet werden.

    Alle benötigten Passwörter sind, sofern vorhanden, in Textform im Angebot anzugeben.
    Spoiler im Spoiler mit Kommentaren :"Schon Bedankt?" sind unerwünscht.


    Releases

    - Sind Retail-Release verfügbar, sind alle anderen Variationen untersagt. Ausnahmen: Alle deutschen Retail-Release sind CUT, in diesem Fall sind dubbed UNCUT-Release zulässig.
    - Im Serien-Bereich gilt speziell: Wenn ein Retail vor Abschluss einer laufenden Staffel erscheint, darf diese Staffel noch zu Ende gebracht werden.62
    - Gleiche Releases sind unbedingt zusammenzufassen. Das bedeutet, es ist zwingend erforderlich, vor dem Erstellen eines Themas per Suchfunktion zu überprüfen, ob bereits ein Beitrag mit demselben Release besteht. Ist dies der Fall, ist der bereits vorhandene Beitrag zu verwenden.
    - P2P und Scene Releases dürfen nicht verändert oder gar unter einem iND Tag eingestellt werden.


    Support, Diskussionen und Suche

    - Supportanfragen sind entweder per PN oder im Bereich Talk zu stellen.
    - Diskussionen und Bewertungen sind im Talk Bereich zu führen. Fragen an die Uploader haben ausschließlich via PN zu erfolgen, und sind in den Angeboten untersagt.
    - Anfragen zu Upload-Wünschen sind nur im Bereich Suche Video erlaubt. Antworten dürfen nur auf Angebote von MyBoerse.bz verlinkt werden.


    Verbote

    - Untersagt sind mehrere Formate in einem einzigen Angebotsthread, wie beispielsweise das gleichzeitige Anbieten von DivX/XviD, 720p und 1080p in einem Thread. Pro Format, Release und Auflösung ist ein eigener Thread zu eröffnen.
    - Grundsätzlich ebenso verboten sind Dupes. Uploader haben sich an geeigneter Stelle darüber zu informieren, ob es sich bei einem Release um ein Dupe handelt.
    - Gefakte, nur teilweise lauffähige oder unvollständige Angebote sind untersagt. Dies gilt auch für eigene Publikationen, die augenscheinlich nicht selbst von z.B. einer DVD gerippt wurden. Laufende Serien, bei denen noch nicht alle Folgen verfügbar sind, dürfen erstellt und regelmäßig geupdatet werden.
    - Untersagt sind Angebote, welche nur und ausschließlich in einer anderen Sprache als deutsch oder englisch vorliegen. Ausnahmen sind VORHER mit den Moderatoren zu klären.


    Verstoß gegen die Regeln

    - Angebote oder Beiträge, die gegen die Forenregeln verstoßen, sind über den "Melden"-Button im Beitrag zu melden.
  • Bitte registriere dich zunächst um Beiträge zu verfassen und externe Links aufzurufen.




Englische Tutorials

The Complete Healthcare Artificial Intelligence Course 2021 (Updated 04/2021)

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The Complete Healthcare Artificial Intelligence Course 2021 (Updated 04/2021)
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 117 lectures (17h 56m) | Size: 6.5 GB

Creating powerful AI model for Real-World Healthcare applications with Data Science, Machine Learning and Deep Learning

What you'll learn:
Pandas.
Matplotlib.
Sigmoid activation function.
Tanh activation function.
ReLU activation function.
Leaky Relu activation function.
Exponential Linear Unit activation function.
Swish activation function.
Markov models.
Support Vector Machines
Other common classifiers
Import data from the UCI repository.
Convert text input to numerical data.
Build and train classification algorithms.
Compare and contrast classification machine learning.
Building the AI.
Machine learning and deep learning model based on the given data with high accuracy.
RF with Response Coding.
Maximum voting Classifier.
Stacking model.
Random Forest Classifier.
One-hot Encoding.
NLP (Natural Language Processing)
NLTK (Natural Language Toolkit)
Logistic Regression.
Naive Bayes
Response Encoding
Linear Support Vector Machines
Geolocation Features.
Handling Missing Data And Anomalies in Python.
Data standardization.
Temporal Features.
Seaborn
Deep Learning.
Keras.
Google Colab .
Anaconda.
Jupiter Notebook.

Requirements
There will be no Prerequisites.
Basic knowledge of Python will be good.
But everything will be taught from the round up.


Description
Interested in the field of Machine Learning, Deep Learning and Artificial Intelligence? Then this course is for you!

This course has been designed by a software engineer. I hope with my experience and knowledge I did gain throughout years, I can share my knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.

I will walk you step-by-step into the Machine Learning, Artificial Intelligence and Deep Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time, we dive deep into Machine Learning, Deep Learning and Artificial Intelligence . Throughout the brand new version of the course we cover tons of tools and technologies including:

Deep Learning.

Google Colab

Anaconda

Jupiter Notebook

Artificial Intelligent In Healthcare.

Artificial Neural Network.

Neuron.

Activation Function.

Keras.

Pandas.

Seaborn.

Feature scaling.

Matplotlib.

Generating a DNA Sequence.

Data Pre-processing.

Sigmoid Function.

Tanh Function.

ReLU Function.

Leaky Relu Function.

Exponential Linear Unit Function.

Swish function.

Markov Models.

K-Nearest Neighbors Algorithms (KNN).

Support Vector Machines (SVM).

Importing library and data.

Deep feedforward networks.

Analysing Data.

Exploratory Analysis.

Handling Missing Data And Anomalies in Python.

Data standardization.

Temporal Features.

Geolocation Features.

Data Scaling.

Data Visualization.

Visualizing Geolocation Data.

Understanding Machine Learning Algorithm.

Splitting Data into Training Set and Test Set.

Training Neural Network.

Model building.

Analysing Results.

Model compilation.

A Comparison Of Categorical And Binary Problem.

Make a Prediction.

Testing Accuracy.

Confusion Matrix.

ROC Curve.

One-hot Encoding.

NLP (Natural Language Processing).

NLTK (Natural Language Toolkit).

Logistic Regression.

Naive Bayes.

Response Encoding.

Linear Support Vector Machines.

RF with Response Coding.

Random Forest Classifier.

Stacking model.

Maximum voting Classifier.

Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models. There are five big projects on healthcare problems and one small project to practice. These projects are listed below:

Predicting Taxi Fares in New York City

DNA Classification Project.

Heart Disease Classification Project.

Diagnosing Coronary Artery Disease Project.

Breast Cancer Detection Project.

Predicting Diabetes with Multilayer Perceptrons Project.

Iris Flower.

Medical Treatment Project.

And as a bonus, this course includes one extra big projects for each month.

Who this course is for
Anyone interested in Machine Learning.
Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence
Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning, Deep Learning, Artificial Intelligence.
Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets.
Any students in college who want to start a career in Data Science
Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence.
Any people who are not satisfied with their job and who want to become a Data Scientist.
Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.
Any people who want to create added value to the local hospital by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools.
Any people who want to work in healthcare field as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.
Any people who want to work in a Taxi Company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.

Homepage

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Linkedin Learning Microsoft Teams Building Custom Apps with the Dataverse-XQZT

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Linkedin Learning Microsoft Teams Building Custom Apps with the Dataverse-XQZT | MKV | 132.16 MiB

555 kb/s 1280x720 | AAC 160 kb/s 2 CH eng



NFO:
File List:

File: 01.01-create_no-code_teams_apps.mkv
Size: 5054176 bytes (4.82 MiB), duration: 00:01:12, avg.bitrate: 562 kb/s
Audio: aac, 48000 Hz, stereo (eng)
Video: h264, yuv420p, 1280x720, 30.00 fps(r) (eng)
Subtitles: eng






Download ( Size: 132.16 MiB ):
Filehosts: Nitroflare, Rapidgator



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1 Link/s
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Environment Creation: Snowy Cabin

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Environment Creation: Snowy Cabin
Emiel Sleegers | Duration: 21h 52m | Video: H264 1920x1016 | Audio: AAC 44,1 kHz 2ch | 14,1 GB | Language: English

Learn How to Model, Texture & Light a Snowy Game Environment using 3ds Max, Substance, Marmoset, & Unreal

In this course, we will go over how to create a snowy environment using 3ds Max, Substance Designer, Marmoset and Unreal. This environment will include having a snowy cabin with terrain, nice trees and plants and will be setup in Unreal Engine. We will learn how to create procedural textures in Substance Designer and we will go over how to edit those textures very quickly so we can have multiple variations. We will then go over how to model our cabin and foliage inside 3ds Max. Once all of that is done, we will go into Unreal Engine where we will set up our scene, our materials, and apply different variations such as dirtness, parallax, mapping, vertex painting, and many more. We will add decals to enhance the overall scene, do some nice lighting and finally polish the scene.

Homepage

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Sci-Fi Game Environment

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Sci-Fi Game Environment
Manuel Rondon | Duration: 27h 07m | Video: H264 1280x720 | Audio: AAC 44,1 kHz 2ch | 9,49 GB | Language: English

Learn How to Create a Sci-Fi Scene using 3ds Max, Substance Painter, Photoshop & Unity

In this course, you will learn how to build a professional sci-fi environment from scratch using 3ds Max, Substance, Photoshop and Unity. You will be taken through the whole workflow from the initial modeling to the final built and render within Unity. As a freelancer, being efficient is a very valuable asset. In this course, you will learn how to save lots of time when building an complete detailed environment. Making an environment for games is an exciting task and hope you join this journey of taking a small 2d concept to the final 3d game-ready level.

Homepage

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Natural Language Processing & Deep Learning: Zero to Hero

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Natural Language Processing & Deep Learning: Zero to Hero
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | VTT | Size: 8.43 GB | Duration: 15h 29m

Linguistics & Machine Learning: Grammar Syntax, Sentiment, ScrapeTweets, RNN/LSTM,Chatbot, SQuAD, Summary, Audio To Text


What you'll learn
Libraries: Tensorflow, Pytorch, NLTK, SpaCy, Sci-kit Learn, Twint
Linguistics Foundation To Help Learn NLP Concepts
Deep Learning: Neural Networks, RNN, LSTM Theory & Practical Projects
Machine Reading Comprehension: Create A Question Answering System with SQuAD
No Tedious Anaconda or Jupyter Installs: Use Modern Google Colab Cloud-Based Notebooks for using Python
How To Build Generative AI Chatbots
Create A Netflix Recommendation System With Word2Vec
Perform Sentiment Analysis on Steam Game Reviews
Convert Speech To Text
Machine Learning Modelling Techniques
Markov Property - Theory & Practical
Optional Python For Beginners Section
Cosine-Similarity & Vectors
Word Embeddings: My Favourite Topic Taught In Depth
Scrape Unlimited Tweets Using An Open Source Intelligence Tool
Speech Recognition
LSTM Fake News Detector
Context-Free Grammar Syntax
Scrape Wikipedia & Create An Article Summarizer


Description
This course takes you from a beginner level to being able to understand NLP concepts, linguistic theory, and then practice these basic theories using Python - with very simple examples as you code along with me.

Get experience doing a full real-world workflow from Collecting your own Data to NLP Sentiment Analysis using Big Datasets of over 50,000 Tweets.

Data collection: Scrape Twitter using: OSINT - Open Source Intelligence Tools: Gather text data using real-world techniques. In the real world, in many instances you would have to create your own data set; i.e source your data instead of downloading a clean, ready-made file online

Use Python to search relevant tweets for your study and NLP to analyze sentiment.

Language Syntax: Most NLP courses ignore the core domain of Linguistics. This course explains the fundamentals of Language Syntax & Parse trees - the foundation of how a machine can interpret the structure of s sentence.

New to Python: If you are new to Python or any computer programming, the course instructions make it easy for you to code together with me. I explain code line by line.

No Installs, we go straight to coding - Code using Google Colab - to be up-to-date with what's being used in the Data Science world 2021!

The gentle pace takes you gradually from these basics of NLP foundation to being able to understand Mathematical & Linguistic (English-Language-based, Non-Mathematical) theories of Deep Learning.

Natural Language Processing Foundation

Linguistics & Semantics - study the background theory on natural language to better understand the Computer Science applications

Pre-processing Data (cleaning)

Regex, Tokenization, Stemming, Lemmatization

Name Entity Recognition (NER)

Part-of-Speech Tagging

Libraries:

NLTK

Sci-kit Learn

Tensorflow

Pytorch

SpaCy

DeepPavlov

Twint

The topics outlined below are taught using practical Python projects!

Parse Tree

Markov Chain

Text Classification & Sentiment Analysis

Company Name Generator

Unsupervised Sentiment Analysis

Topic Modelling

Word Embedding with Deep Learning Models

Open Domain Question Answering (like asking Google)

Closed Domain Question Answering (Like asking a Restaurant-Finder bot)

LSTM using TensorFlow, Keras Sequence Model

Speech Recognition

Convert Speech to Text

Neural Networks

This is taught from first principles - comparing Biological Neurons in the Human Brain to Artificial Neurons.

Practical project: Sentiment Analysis of Steam Reviews

Word Embedding: This topic is covered in detail, similar to an undergraduate course structure that includes the theory & practical examples of:

TF-IDF

Word2Vec

One Hot Encoding

gloVe

Deep Learning

Recurrent Neural Networks

LSTMs

Get introduced to Long short-term memory and the recurrent neural network architecture used in the field of deep learning.

Build models using LSTMs


Who this course is for:
Anyone who is curious about data science & NLP
Those who are in the Business & Marketing world - learn use NLP to gain insight into customers & products. Can help at interviews & job promotions.
If you intend to enrol in an NLP/Data Science course but are a total newbie, complete this course before to avoid being lost in class since it can seem overwhelming if classmates already have a foundation in Python or Datascience.


Homepage

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Futuristic Game Environment in Blender

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Futuristic Game Environment in Blender
Emiel Sleegers | Duration: 18h 57m | Video: H264 1920x1016 | Audio: AAC 44,1 kHz 2ch | 11,1 GB | Language: English

Learn How to Create a Game-Ready Environment Using Blender, Substance Painter & Unreal

Finding a Blender course on creating a game environment that will take your skills to a whole new level can be hard to find. But don't worry, I am here to show you my workflow that will guide you in creating a professional environment like you see in AAA video games that you play today.

In this course, we will go through the entire pipeline of creating a game-ready environment. The major topics we will be covering are:

• High Poly to Low Poly Modeling using Blender
• Proper UV unwrapping in Blender
• Baking maps in Marmoset Toolbag
• Detailing & Texturing in Substance Painter
• Scene setup, lighting, & post effects in Unreal Engine
• By the end of this course, you will be able to create a clean and amazing futuristic game environment.

Before beginning this course, you should have a basic knowledge of Blender, Substance Painter, Marmoset Toolbag and Unreal Engine.

If you want to be a 3D environment artist, you need to know the latest tools, methods, and strategies to better strengthen your skills to get closer to your goal. This course will put you ahead of 99.9% of all beginners out there when it comes to game environment creation. In this course, you will learn the proper workflow and techniques that will allow you to build a complete production-ready scene.

Homepage

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Full Stack Mobile Application Development - Master Class

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Full Stack Mobile Application Development - Master Class
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | VTT | Size: 8.66 GB | Duration: 10h 36m

Native Android,Native IOS,Flutter,React Native,Xamarin


What you'll learn
You will learn about Full Stack Mobile App Development with native and Hybrid mobile apps framework.
Android with Java and Kotlin
IOS with Swift
Flutter with Dart
React Native with JavaScript
Xamarin with C#
Tools - Android Studio - Xcode - Visual Studio and Visual Studio Code
Weekly Updates with new Material on demand


Description
There's strong motivation for companies to find someone who can "do it all".

This Course explores the features of full-stack mobile development environments and covers several core native and hybrid mobile alternatives and the factors that influence the selection of each platform.

Full-stack mobile app development lies at the nexus of content and technology. Billions of people worldwide now use smartphones and tablets, which form the client side of the full-stack app. The server side is often a distributed collection of microservices, authenticating servers, and CDN assets that are compiled at runtime each time an application is opened. Between the two lies the processes that connect them, including testing, continuous integration and continuous deployment, scaling and containerization, and proprietary device requirements.

To be a full-stack mobile developer, you need to have an understanding, or vision, of the big picture in app development.

This includes:

The look and feel in devices

The servers and containers that are accessed to provide content and data processing

Development processes like testing and debugging

Reasons and trade-offs behind choosing solutions among many alternatives

This course will provide an overview of some of the most popular tools (in 2021) for developing full-stack mobile apps. I touched on some of the core concepts, considerations, dependencies, and ecosystems, while leaving the heavy lifting to upcoming articles and tutorials.

What you will learn in this course ?

App development lifecycle Introduction

Android and IOS Layout and Widgets

Android and IOS MultiMedia

Android and IOS Maps

Android and IOS Networking

Android and IOS Storage

Android and IOS Firebase

Android and IOS GraphQL

Android and IOS Camera

Android and IOS Best Practices for coding and design pattern

Git and GitHub Intro

Android and IOS Mobile Application Security Tips

Android and IOS App Publication

Programming Language Used

Java

Kotlin

Swift

Dart

C#

JavaScript

XML and XMAL

SQL and GraphQL


Homepage

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Face Rigging in Blender 2.8 Tutorial

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Face Rigging in Blender 2.8 Tutorial
MP4 | Video: h264, yuv420p, 1920x1080 | Audio: aac, 48000 Hz | Duration: 6h 39min | File Size: 6.03 GB
Genre: eLearning | Language: English

In this course, I'll present to you my workflow of creating realistic Face Rig based on shape keys. In the begging, after a small introduction to Face Action Coding system and some advice on organizing the work, I will walk you through the process of sculpting necessary expressions. I'll show you how to utilize references, and give some tips and tricks on forming the face, managing stretches and sculpting important wrinkles. In the sculpting process I will be using ZBRUSH, but after some minor workflow adjustments you can without a problem do it in BLENDER (I show how to sculpt realistic face just in Blender in my "Realistic Face Creation in Blender" course.

Afterward, we will take all of the expressions sculpted in Zbrush and implement them to the face rig. Face deformations will be made by shape keys driven by the bones. Moreover, we will use high detail information made in Zbrush to create Dynamic Wrinkle System in Eevee (it works in Cycles as well).
Then I'll show you how to make your animation work way more convenient, by creating puppeteering systems for a more intuitive animating process.
In the end, I'll present to you, how to prepare your rig for the export to Unreal Engine. And how to set up the Dynamic Wrinkle system in it as well.

01. Introduction.mp4
02. Exp. Smile And Sad.mp4
03. Exp. Contempt And Angry.mp4
04. Exp. Disgust And Surprise.mp4
05. Additional Shape Keys.mp4
06. Additional Shape Keys.mp4
07. Additional Shape Keys.mp4
08. Additional Shape Keys.mp4
09. Basic Bone Rigging.mp4
10. Importing Shape Keys - Part 1.mp4
11. Importing Shape Keys - Part 2.mp4
12. Corrective Shape Keys.mp4
13. Bones And Drivers Setup.mp4
14. Visual Controlers Setup.mp4
15. Wrinkle Map Preparation.mp4
16. Eevee Dynamic Wrinkle System.mp4
17. Eyes Shape Keys And Facial Hair.mp4
18. Face Rig Puppeteering System.mp4
19. Rig Preparation To Export.mp4
20. Unreal Dynamic Wrinkle System.mp4

Homepage

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Embedded Systems STM32 Low-Layer APIs(LL) Driver Development

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Embedded Systems STM32 Low-Layer APIs(LL) Driver Development
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 73 lectures (25h 41m) | Size: 11.7 GB

STM32 Low-Level (LL) Drivers: ADC,UART,TIMERS, GPIO,SPI,I2C,RTC,WWDG,IWDG,RCC etc

What you'll learn:
Write firmware using only Low-Level Functions
Understand the Cortex-M Architecture
Write Analog-to-Digital Converter (ADC) drivers using Low-Level Functions
Write PWM drivers using Low-Level Functions
Write UART drivers using Low-Level Functions
Write TIMER drivers using Low-Level Functions
Write Interrupt drivers using Low-Level Functions
Write SPI drivers using Low-Level Functions
Write I2C drivers using Low-Level Functions
Write RTC drivers using Low-Level Functions
Write DMA drivers using Low-Level Functions
Write RCC drivers using Low-Level Functions
Write WWDG drivers using Low-Level Functions
Write IWDG drivers using Low-Level Functions

Requirements
No programming experience needed - I'll teach you everything you need to know.
STM32F411-NUCLEO
We shall be using the STM32CubeIDE which is FREE.


Description
Welcome to the Embedded Systems STM32 Low-Layer APIs(LL) Driver Development course.

The STM32 Low-Layer APIs ( as known as LL) offers a fast light-weight expert-oriented layer which is closer to the hardware than the HAL APIs (Hardware Abstraction Layer). The LL offers low-level APIs at the register level with better optimization. These require deep knowledge of the MCU and peripheral specifications which we shall cover in this course.

With a programming based approach, this course is designed to give you a solid foundation in firmware and peripheral driver development for the STM32 family of microcontrollers. The goal of this course is to teach you how to navigate the microntroller reference manual and datasheet to extract the right information to professionally build peripheral drivers and firmware using the STM32 Low-Layer APIs

By the end of this course you will be able to develop drivers for peripherals like the ADC, UART,PWM, GPIO, TIMER,I2C, SPI, RTC, WWDG, IWDG, RCC, EXTI etc. You will also master the STM32 architecture and how to build professional embedded firmware for STM32 microcontrollers.

Please take a look at the full course curriculum.

REMEMBER : I have no doubt you will love this course. Also it comes with a FULL money back guarantee for 30 days! So put simply, you really have nothing to loose and everything to gain.

Sign up and let's start toggling some register bits.

--------------------------------------Some highlights------------------------------------

Write Analog-to-Digital Converter (ADC) drivers using Low-Level functions

Write PWM drivers using Low-Layer functions

Write UART drivers using Low-Layer functions

Write TIMER drivers using Low-Layer functions

Write Interrupt drivers using Low-Layer functions

Write SPI drivers using Low-Layer functions

Write I2C drivers using Low-Layer functions

Write RTC drivers using Low-Layer functions

Write DMA drivers using Low-Layer functions

Write RCC drivers using Low-Layer functions

Write WWDG drivers using Low-Layer functions

Write IWDG drivers using Low-Layer functions

Who this course is for
If you are an absolute beginner to embedded systems, then take this course.
If you are an experienced embedded developer and want to learn how to professionally develop embedded applications for ARM processors, then take this course.

Homepage

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Delta VFD Real Applications With Plc - Modbus -HMI -VFDSoft

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Delta VFD Real Applications With Plc - Modbus -HMI -VFDSoft
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 69 lectures (7h 4m) | Size: 5.33 GB

Learn Delta AC Drive Applications with Real Hardware and AS200 Plc - DOP 100 HMIs - RS-485 Communication - VFDSoft

What you'll learn:
Delta AC Drives
Modbus Communication
HMI Programming
DOPSoft
ISPSoft
Plc Programming Basics
Motor Control Basics
AS200 Series Plc Basics
Technical Informations About Industrial Automation
Applications and Realities
VFD Basics
PID Control of VFD
VFDSoft

Requirements
You need to be willing to learn and be patience .You need to keep following instructions and applications carefully


Description
Dear friends,

In this course, we made applications for you by using delta vfds and real hardware.

You will see how we can control a 3 phase motor.

You will see how the parameters of delta vfds affect the motor.

We read all the values ​​of the vfd over Modbus communication and wrote the values ​​to the vfd.

We run the vfd with the keypad on it.

We run the vfd with the buttons on it.

We run the vfd frequency with digital potentiometer or up and down keys.

At the same time, we checked the vfd with the external terminals.

We wrote a frequency value to the vfd with an external potentiometer.

We controlled the vfd with serial communication over PLC and wrote all frequency values ​​over communication.

At the same time, we gave the forward-reverse and stop-run commands of the vfd over communication.

We have programmed the terminals on the vfd and made applications for you to do almost any application.

We did PID control with the vfd.

We applied different voltages to the vfd and the motor, applied dc brakes and monitored all results.

With the Dopsoft program, we checked the vfd via hmi.

While learning dopsoft on the one hand, we showed all the values ​​of the vfd on the screen with dopsoft on the other hand.

And we wrote to the vfd from the screen.

We learned about plc programming by making small applications with basic plc programming training.

With the VFDSoft program, we connected to the vfd and checked the vfd on the computer.

We backed up the vfd parameters and uploaded the backed-up parameters to the vfd.

We watched and recorded the vfd's information with the trend.

We have seen how we can easily change the parameters of the vfd with vfdsoft.

In short, what you will learn in this training;

- Delta AC Vfds

- Delta VFD Parameters and Applications

- VFDSoft

- ISPSoft

- Basics of Plc Programming

- AS200 Series Plc

- DOPSoft

- DOP 100 HMI Basics

- Complete Modbus (RS-485) Communication

- PID Control

- Motor Control for Different Conditions and Applications

And much more than these.

The most important point for this course is that all the information is included in the course practically.

All technical details are practically demonstrated and applied.

Who this course is for
Anyone wanting full control of delta vfds
Anyone who wants to do modbus communication with Delta vfds
Anyone who wants to use delta vfds in all kinds of applications
Anyone who wants to improve plc programs and applications

Homepage

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Database Engineer/DBA - (PostgreSQL, IBM-DB2, MariaDB,NoSQL)

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Database Engineer/DBA - (PostgreSQL, IBM-DB2, MariaDB,NoSQL)
MP4 | Video: h264, 1280x720 | Audio: AAC, 44100 Hz
Language: English | Size: 5.45 GB | Duration: 18h 16m



What you'll learn
Installing Database Servers
Creating Databases
Creating Tables
Extracting and joining data from multiple tables
Dropping and Truncating Tables
Performing CRUD Operations
Sorting and Filtering Data
Creating Stored Procedures
Querying database with various operators
Creating Triggers
Creating Views
Implementing Database Security
Backing up and restoring database
Aggregating data with Aggregate Functions
Analyzing data with Analytic Functions
Creating NoSQL Databases
Interacting with NoSQL Databases

Requirements
A Computer is required + Internet connection

Description
Database engineers design new databases based on company needs, data storage needs, and the number of users accessing the database. Monitor Databases and Programs. Database engineers continuously monitor databases and related systems to ensure high functionality.

Database administrator ensures that data is available, protected from loss and corruption, and easily accessible as needed. Also they oversee the creation, maintenance and security of your databases. manages, backs up and ensures the availability of the data.

PostgreSQL is commonly known as Postgres and it is also open source database. PostgreSQL is a powerful, open source object-relational database system.

IBM Db2 is a family of related data management products,including relational database servers, developed and marketed by IBM.

MariaDB is great for its open-source innovation and enterprise-grade reliability, as well as its modern relational database.

SQL -Structured Query Language is an internationally recognized language used to communicate and manipulate various database systems.

Data is everywhere and growing at a rapid rate. Most Software application we interact with daily deals with stored data . From our interaction with our banks to social media applications like Facebook and Instagram..

Due to the relevance and dependency on data , professionals that are skilled in SQL are always in high demand to help interact with various databases to help business intelligence and other sectors that relies on data.

NoSQL (Non-SQL or Not-only-SQL) databases are increasing in popularity due to the growth of data as they can store non-relational data on a super large scale, and can solve problems regular databases can't handle. They are widely used in Big data operations. Their main advantage is the ability to handle large data sets effectively as well as scalability and flexibility issues for modern applications.


Who this course is for:
Beginner Database Engineers
Beginner Database Administrators
Beginner Data Analyst


Homepage

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Create a Laravel server with mobile integration

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Create a Laravel server with mobile integration
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 29 lectures (10h 23m) | Size: 5.3 GB

Integration between laravel and a ionic mobile framework.

What you'll learn:
How to setup a laravel server aplication.
Mobile integration with a laravel backend server.
Basic of api request.
Laravel Sanctum.
Login logic for a mobile aplication.
Basic of ionic framework.

Requirements
Basic knowledge of laravel.
Basic knowledge of javascript
Composer tool
Npm tool
Basic knowledge of vue js.
Basic knowledge of php.
Basic knowledge of mysql.


Description
In this course you are going to learn how to create a Web Server application with Laravel Framework using a clean laravel packages structure. I am going to teach you how to use a basic login system , api auth with laravel sanctum, and custom middleware, basic laravel commands structure for installation and packages resource import and export. At the beggining of the course, I am going to show you a basic structure with tailwind and vue js preset , features such as a basic login which you can find in the course's resources.

Later on, we are going to focus on the Mobile Application and on how to use ionic framework with vue js, axios, local storage, basic vue js setup, simple token storage and authentications with the laravel server using axios requests, simple project organizations.

This course is good for anyone who wants to learn how to create a mobile application side by side with a server. The skills required for this course are: basic laravel knowledge such as request validations, model creations, controllers resources ,routes setup, migrations, and some basic knowledge of javascript, vue js 3 , axios, javascript local storage.

At the end of this course, you will be able to create any kind of mobile application working side by side with a backend laravel server.

Who this course is for
Laravel Developers
Front end Developers
Backend Developers
Medium Developers.
Laravel Migrations.
Laravel packa

Homepage

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