Enjoy the purring of Siamese newborn kittens

more videos on my channel:
Sounds of Kittens - https://youtu.be/cDDBI7ea0q0
Sounds of cats - https://youtu.be/Jp38wD2mSqI
Sounds of dinosaurs - https://youtu.be/RzKuin7VWcg
Sounds of other animals - https://youtube.com/playlist?l....ist=PLDapvKFiGTl48th

#animalsounds #kidsvideo #animals #relaxing #relax #satisfying #satisfyingvideo #pets #learninganimals #soundsofanimals

Downloading and installing Python 3, along with an editor and writing our very first, though super basic, program!

Playlist: https://www.youtube.com/playli....st?list=PLQVvvaa0QuD

#python #programming #tutorial

A Budget 8K Camera Made For YouTubers The BOSMA 8K Cinema Camera #CES2020
To Learn More About Bosma Click Here: https://www.bosmatechnology.com/

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Time series forecasting has a wide range of applications: finance, retail, healthcare, IoT, etc. Recently deep learning models such as ESRNN or N-BEATS have proven to have state-of-the-art performance in these tasks. Nixtlats is a python library that we have developed to facilitate the use of these state-of-the-art models to data scientists and developers, so that they can use them in productive environments. Written in pytorch, its design is focused on usability and reproducibility of experiments. For this purpose, nixtlats has several modules:

Data: contains datasets of various time series competencies.
Models: includes state-of-the-art models.
Evaluation: has various loss functions and evaluation metrics.

Objective:

- To introduce attendees to the challenges of time series forecasting with deep learning.
- Commercial applications of time series forecasting.
- Describe nixtlats, their components and best practices for training and deploying state-of-the-art models in production.
- Reproduction of state-of-the-art results using nixtlats from the winning model of the M4 time series competition (ESRNN).

Project repository: https://github.com/Nixtla/nixtlats.

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