Machine learning and neural networks

Machine Learning (ML) and Neural Networks are at the heart of modern artificial intelligence. Machine Learning is a scientific discipline that gives computers the ability to learn from data. Instead of explicitly programming each task, we provide algorithms with large volumes of data and let them independently find patterns, build models, and make predictions or decisions. Neural networks, in turn, are one of the most powerful and flexible classes of models in machine learning. Their structure mimics the network of neurons in the human brain, consisting of interconnected layers capable of processing and transforming data at various levels of abstraction. Deep Learning, a subfield of ML using multi-layered neural networks, has revolutionized many areas, from image and speech recognition to natural language processing and predictive analytics. This category features tools, frameworks, and platforms used by data scientists, researchers and developers to build, train, test, and deploy machine learning and neural network models. Here you will find libraries for building models (e.g., TensorFlow, PyTorch, scikit-learn), platforms for managing the model lifecycle, tools for visualizing data and training results, as well as solutions for deploying models on various devices and in the cloud. If you want to delve into AI development at a fundamental level, this category is your starting point. Explore tools that will help you master machine learning and unlock the potential of neural networks!