neural networks

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a HEARING PROXIA (B) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a TRAFFIC COUNTING (TC) PROXIA when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an OBJECT MASKING PROXIA when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an OBJECT DETECTION proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an OBJECT DETECTION proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an IMAGINATION (D) proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an IMAGINATION proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an IMAGINATION (C) proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an IMAGINATION (A1) PROXIA when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a BRAIN PROXIA (B) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an ASTRAL VISION PROXIA (C) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an ASTRAL VISION PROXIA when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

✭ MAGNETRON ✭: GPT-3: Language Models are Few-Shot Learners

✭ MAGNETRON ™ ✭: Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

✭ MAGNETRON ™ ✭: Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

✭ MAGNETRON ™ ✭: DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.

Python project for my master's thesis.

Распознавание дорожных знаков при помощи камеры и YOLOv5, вывод их иконок на экранную форму.

Graph analysis tools such as embedding techniques and similarity measures.

TensorFlow examples for Artificial Neural Networks course including: MLP with softmax output layer; MLP and CNN for MNIST dataset; CNN for CIFAR-10 dataset with data augmentation; LSTM with CNN layer for IMDB sentiment classification task.