YouTube’s evolution in 2023 is not just about technological advancements but a commitment to empowering creators globally. These new features and tools reflect YouTube’s dedication to fostering a diverse and thriving community of content creators. By enhancing monetization options, providing AI-driven content creation tools, offering improved analytics, strengthening copyright protection, and enhancing the live streaming experience, YouTube is equipping creators with the resources they need to succeed.
Making a video for YouTube can seem like a daunting task, but with the right tools and approach, anyone can create content that engages and entertains an audience. Here are the basic steps to make a video for YouTube:
FreeTube is a YouTube client for Windows, Mac, and Linux built around using YouTube more privately. You can enjoy your favorite content and creators without your habits being tracked. All of your user data is stored locally and never sent or published to the internet. FreeTube grabs data by scraping the information it needs (with either local methods or by optionally utilizing the Invidious API). With many features similar to YouTube, FreeTube has become one of the best methods to watch YouTube privately on desktop.
https://www.heise.de/tipps-tricks/Youtube-Video-herunterladen-am-Computer-so-geht-s-3931676.html
Downloaden und speichern Sie Videos direkt von Youtube, Facebook und viele mehr. Einfaches Kopieren und Einfügen.
Radikalisiert der Empfehlungsalgorithmus von Youtube die Zuschauer? Eine interdisziplinare Untersuchung verneint und schlägt vor, nach neuen Gründen zu suchen.
Spheres are nice and all, but there comes a time when more complex shapes are needed. One popular algorithm for testing collisions is the Gilbert–Johnson–Keerthi algorithm, or GJK for short. With it we can detect collisions between any two convex polygons.
Check out the full article: https://blog.winter.dev/2020/gjk-algorithm/
Physics is a part of games that has always amazed me. I find it funny how impossible it seemed to do correctly when I was younger. While making a custom game engine, it was finally demystified!
The full article: https://blog.winter.dev/2020/designing-a-physics-engine/
The background game demo: https://winter.dev/demo
In this video we will take an in depth look at the fast inverse square root and see where the mysterious number 0x5f3759df comes from. This algorithm became famous after id Software open sourced the engine for Quake III. On the way we will also learn about floating point numbers and newton's method.
This is the Graph Neural Networks: Hands-on Session from the Stanford 2019 Fall CS224W course.
In this tutorial, we will explore the implementation of graph neural networks and investigate what representations these networks learn. Along the way, we'll see how PyTorch Geometric and TensorBoardX can help us with constructing and training graph models.
Pytorch Geometric tutorial part starts at -- 0:33:30
Details on:
* Graph Convolutional Neural Networks (GCN)
* Custom Convolutional Model
* Message passing
* Aggregation functions
* Update
* Graph Pooling
Gegen die großen Digitalkonzerne kommt man nicht an? Das ändert sich gerade. Neue Kooperationen zwischen Internetbewegungen und klassischen Gewerkschaften ernten erste Erfolge. Der Fall Youtube zeigt es.
DownSub is a free web application that can download subtitles directly with playlist from Youtube, Drive, Viu, Vimeo, Viki, OnDemandKorea, Vlive and more.
Can organized labor and the threat of lawsuits force YouTube to treat users more fairly? The YouTubers Union, which last week joined forces with Europe’s largest trade union, hopes so. The group is pushing YouTube to be more transparent in decision-making—and arguing that the company’s current practices violate data privacy laws. It’s an unconventional approach.…
This course will introduce the student to classic neural network structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN) and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered. High Performance Computing (HPC) aspects will demonstrate how deep learning can be leveraged both on graphical processing units (GPUs), as well as grids. Focus is primarily upon the application of deep learning to problems, with some introduction to mathematical foundations. Students will use the Python programming language to implement deep learning using Google TensorFlow and Keras.
Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2019 Notebook: http://deeplearning.cs.cmu.edu/document/recitation/recitation...
Y. Wang, A. Mendez Mendez, M. Cartwright, и J. Bello. ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), стр. 880-884. (мая 2019)
I. Orsolic, L. Skorin-Kapov, и T. Hoßfeld. 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX) (QoMEX 2019), (июня 2019)