Учебные материалы по машинному обучению

Discover the power of Mamba LLM, a transformative architecture from leading universities, redefining sequence processing in AI.

This article provides a comprehensive guide on utilizing the OpenCV library for image and video processing within a Python environment. We dive into the wide range of image processing functionalities OpenCV offers, from basic techniques to more advanced applications.

Learn how to automate model training, evaluation, versioning, and deployment using GitHub Actions with the easiest MLOps guide available online.

Learn an end-to-end workflow to monitor any model in your Jupyter notebook in production environments.

Learn how multilayer perceptrons work in deep learning. Understand layers, activation functions, backpropagation, and SGD with practical guidance.

Unlock the power of Bayesian Optimization for hyperparameter tuning in Machine Learning. Master theoretical foundations and practical applications with Python to enhance model accuracy.

Explore the groundbreaking technique of Low-Rank Adaptation (LoRA) in our full guide. Discover how LoRA revolutionizes the fine-tuning of Large Language Models.

Explore cross-entropy in machine learning in our guide on optimizing model accuracy and effectiveness in classification with TensorFlow and PyTorch examples.

Explore the architecture of Transformers, the models that have revolutionized data handling through self-attention mechanisms.

Explore the importance of Normalization, a vital step in data preprocessing that ensures uniformity of the numerical magnitudes of features.

Learn the inner workings of gradient boosting in detail without much mathematical headache and how to tune the hyperparameters of the algorithm.

Learn how to set up and configure MySQL database inside Docker containers. The tutorial includes concepts such as connecting to MySQL servers, running MySQL clients to connect to containers, and so on.