Neural Networks | Нейронные сети
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hkchengrex/CascadePSP

🔗 hkchengrex/CascadePSP
[CVPR2020] CascadePSP: Toward Class-Agnostic and Very High-Resolution Segmentation via Global and Local Refinement - hkchengrex/CascadePSP
​Какие нейросети умеют петь и исполнять дэт-метал

🔗 Какие нейросети умеют петь и исполнять дэт-метал
Расскажем об интеллектуальных инструментах, способных генерировать треки и даже тексты песен. Речь пойдет о решениях корпораций и лабораторий, а также разработка...
​Какие нейросети умеют петь и исполнять дэт-метал

🔗 Какие нейросети умеют петь и исполнять дэт-метал
Расскажем об интеллектуальных инструментах, способных генерировать треки и даже тексты песен. Речь пойдет о решениях корпораций и лабораторий, а также разработка...
🎥 The Spectrogram and the Gabor Transform
👁 1 раз 795 сек.
Here I introduce the spectrogram, which is a moving-window Fourier transform, giving insight into the time-frequency content of a data set.

Book Website: http://databookuw.com
Book PDF: http://databookuw.com/databook.pdf

These lectures follow Chapter 2 from:
"Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Brunton and Kutz

Amazon: https://www.amazon.com/Data-Driven-Science-Engineering-Learning-Dynamical/dp/1108422098/

Brunton Website: eigensteve.com
🎥 Machine Learning in R | Data Science for Beginners | Random Forest | Boston House Data | Regression
👁 1 раз 552 сек.
#datascience #machinelearning #dataanalyst #R
Download End-to-End Notebooks in Python and R for Citizen Data Scientists and Machine Learning Developers from https://wacamlds.podia.com/end-to-end-notebooks-for-citizen-data-scientists?coupon=WACAMLDS80

Practice makes perfect. Please practise this recipe on your own IDE to speed up your learning in the field of Applied Data Science & Machine Learning. Search the title at https://setscholars.net and Download code from https://setscholars.net

This end-to-end
🎥 What are GANs ? | Introduction to Generative Adversarial Networks | Face Generation & Editing - 30
👁 1 раз 231 сек.
Artificial Intelligence terms explained in a minute for everyone! This week's term is GAN. More precisely, Generative Adversarial Networks, a recent class of machine learning frameworks that was first introduced by Ian Goodfellow and his colleagues in 2014. Ask any questions or remarks you have in the comments, I will gladly answer to everything!



Read more about the first example "The Zootopia transformations": https://www.vice.com/en_us/article/884wek/ai-algorithm-turns-humans-into-animals
The 2014 pa
​Домашний кластер на Dask

🔗 Домашний кластер на Dask
Я недавно проводил исследование, в рамках которого было необходимо обработать несколько сотен тысяч наборов входных данных. Для каждого набора — провести некото...
🎥 TensorFlow 2.0 Tutorial - Part 1 | Introduction To TensorFlow 2.0 | TensorFlow Training | Edureka
👁 1 раз 1275 сек.
🔥Edureka TensorFlow Training: https://www.edureka.co/ai-deep-learning-with-tensorflow
This Edureka TensorFlow 2.0 Tutorial - Part 1 ( Part 2 - https://youtu.be/H-L59o4SfxE ) covers the basics of TensorFlow with various new features and applications with respect to AI and Deep Learning. Below are the topics covered in this TensorFlow tutorial:
AI, ML & Deep Learning
Introduction To TensorFlow
What's New in TensorFlow 2.0?
Why TensorFlow?
Applications Of TensorFlow

🔹Check our complete Deep Learning With Te
🎥 TensorFlow.js: Machine Learning in JavaScript by Jason Mayes
👁 1 раз 2614 сек.
An event hosted in association with TensorFlow User Group Mysuru.

Talk Abstract
TensorFlow. js is an open-source hardware-accelerated JavaScript library for training and deploying machine learning models. Develop ML in the Browser. Use flexible and intuitive APIs to build models from scratch using the low-level JavaScript linear algebra library or the high-level layers API.

Join us for a short introductory talk to learn more about machine learning in JavaScript and some of the superpowers you gain by usin
🎥 Build a Probabilistic Classification using Scikit-learn | Machine Learning Tutorials | Codegnan
👁 1 раз 5075 сек.
In this video you'll learn how to build a probabilistic classification using Machine Learning library SciKit-Learn. Basically Probability means it is the ratio of total number of outcomes and favorable number of outcomes. Watch the full video to get deep understanding on how probability relates to Machine Learning and how you can build one using sci-kit learn and also working on text and simple data set

Master Machine Learning Online/Classroom with Hewlett Packard Certification
Visit our Website here: http