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docs: Update README #1330

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19 changes: 9 additions & 10 deletions README.rst
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Expand Up @@ -85,6 +85,7 @@ FEDOT предоставляет возможность использовать
================

FEDOT предоставляет высокоуровневый API, который удобно использовать. API может использоваться для задач классификации, регрессии и прогнозирования временных рядов.

Чтобы использовать API, выполните следующие действия:

1. Импортируйте класс ``Fedot``
Expand Down Expand Up @@ -185,8 +186,9 @@ Jupyter ноутбуки с примерами находятся в репоз
В настоящее время мы работаем над новыми функциями и пытаемся улучшить производительность и удобство использования FEDOT.
Основные текущие задачи и планы:

* Реализация методов и алгоритмов мета-обучения
* Повышение эффективности оптимизационного ядра GOLEM.
* Реализация большой языковой модели для задач автоматического машинного обучения в `FEDOT.LLM <https://github.com/ITMO-NSS-team/FEDOT.LLM>`__.
* Реализация методов и алгоритмов мета-обучения в `GAMLET <https://github.com/ITMO-NSS-team/GAMLET>`__.
* Повышение эффективности оптимизационного ядра `GOLEM <https://github.com/aimclub/GOLEM/>`__.
* Поддержка более сложных вариантов пайплайнов, особенно для задач прогнозирования временных рядов.


Expand All @@ -211,17 +213,17 @@ Jupyter ноутбуки с примерами находятся в репоз

Дополнительные проекты
======================
- Оптимизационное ядро, вынесенное в библиотеку `GOLEM <https://github.com/aimclub/GOLEM/>`__.
- Прототип реализации Meta-AutoML - `MetaFEDOT <https://github.com/ITMO-NSS-team/MetaFEDOT>`__.
- Прототип web-GUI для FEDOT - `FEDOT.WEB <https://github.com/aimclub/FEDOT.Web>`__.

- Оптимизационное ядро, вынесенное в библиотеку GOLEM.
- Прототип web-GUI для FEDOT доступен в `FEDOT.WEB <https://github.com/aimclub/FEDOT.Web>`__ репозитории.
- Прототип реализации Meta-AutoML - MetaFEDOT.
- Прототип реализации LLM для AutoML - FEDOT.LLM.

Контакты
========
- `Telegram-канал <https://t.me/FEDOT_helpdesk>`_ для решения проблем и ответов на вопросы о FEDOT
- Команда `Natural System Simulation <https://itmo-nss-team.github.io/>`_
- `Анна Калюжная <https://scholar.google.com/citations?user=bjiILqcAAAAJ&hl=ru>`_, руководитель ([email protected])
- `Новости <https://t.me/NSS_group>`_
- `Новостной Telegram-канал <https://t.me/NSS_group>`_
- `Youtube канал <https://www.youtube.com/channel/UC4K9QWaEUpT_p3R4FeDp5jA>`_

Разработка ведётся при поддержке
Expand All @@ -248,9 +250,6 @@ Jupyter ноутбуки с примерами находятся в репоз
pages={926-933},
doi={10.1109/CEC45853.2021.9504773}}


Другие статьи доступны на `ResearchGate <https://www.researchgate.net/project/Evolutionary-multi-modal-AutoML-with-FEDOT-framework>`_.

.. |docs| image:: https://readthedocs.org/projects/ebonite/badge/?style=flat
:target: https://fedot.readthedocs.io/en/latest/
:alt: Documentation Status
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15 changes: 8 additions & 7 deletions README_en.rst
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Expand Up @@ -186,10 +186,13 @@ Current R&D and future plans
Currently, we are working on new features and trying to improve the performance and the user experience of FEDOT.
The major ongoing tasks and plans:

* Implementation of meta-learning based at GNN and RL (see `MetaFEDOT <https://github.com/ITMO-NSS-team/MetaFEDOT>`__)
* Implementation of large language model for AutoML tasks in `FEDOT.LLM <https://github.com/ITMO-NSS-team/FEDOT.LLM>`__.
* Implementation of meta-learning based at GNN and RL (see `GAMLET <https://github.com/ITMO-NSS-team/GAMLET>`__).
* Improvement of the optimisation-related algorithms implemented in `GOLEM <https://github.com/aimclub/GOLEM/>`__.
* Support for more complicated pipeline design patters, especially for time series forecasting.

In addition, we are working on a number of research tasks related to benchmarking of time series forecasting using AutoML and multimodal modelling.

Any contribution is welcome. Our R&D team is open for cooperation with other scientific teams as well as with industrial partners.

Documentation
Expand All @@ -209,16 +212,17 @@ We acknowledge the contributors for their important impact and the participants

Side Projects
=============
- The optimisation core implemented in `GOLEM <https://github.com/aimclub/GOLEM/>`__ repository.
- The optimisation core implemented in the GOLEM.
- The prototype of the web-GUI for FEDOT is available in the `FEDOT.WEB <https://github.com/aimclub/FEDOT.Web>`__ repository.
- The prototype of FEDOT-based meta-AutoML in the `MetaFEDOT <https://github.com/ITMO-NSS-team/MetaFEDOT>`__ repository.
- The prototype of FEDOT-based meta-AutoML in the GAMLET.
- The prototype of FEDOT-based LLM for nexgen AutoML in the FEDOT.LLM.

Contacts
========
- `Telegram channel for solving problems and answering questions about FEDOT <https://t.me/FEDOT_helpdesk>`_
- `Natural System Simulation Team <https://itmo-nss-team.github.io/>`_
- `Anna Kalyuzhnaya <https://scholar.google.com/citations?user=bjiILqcAAAAJ&hl=ru>`_, Team leader ([email protected])
- `Newsfeed <https://t.me/NSS_group>`_
- `Telegram newsfeed channel <https://t.me/NSS_group>`_
- `Youtube channel <https://www.youtube.com/channel/UC4K9QWaEUpT_p3R4FeDp5jA>`_

Supported by
Expand All @@ -245,9 +249,6 @@ Citation
pages={926-933},
doi={10.1109/CEC45853.2021.9504773}}


Other papers - in `ResearchGate <https://www.researchgate.net/project/Evolutionary-multi-modal-AutoML-with-FEDOT-framework>`_.

.. |docs| image:: https://readthedocs.org/projects/ebonite/badge/?style=flat
:target: https://fedot.readthedocs.io/en/latest/
:alt: Documentation Status
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