ЛУЧШИЕ САЙТЫ КОТОРЫЕ ТЫ ДОЛЖЕН ЗНАТЬ 284

ЛУЧШИЕ САЙТЫ КОТОРЫЕ ТЫ ДОЛЖЕН ЗНАТЬ 284 Часть 284 Ship <code/> Categories Languages Courses Paths Dashboard Collab Search... Watch tutorials. Ship working systems. Rebuild Redis, Git, a database, an OS kernel -- from an empty file to passing tests. Your code runs against a real executor. And it either passes or it doesn't. Start building - It's free Performance - not credit card See all courses SHIP <code/> <code/> COBOL Advanced COBOL Advanced 179 courses, built from scratch 37 programming languages 1,900+ exercises verified on the executor $0 Everything free while we grow Pick your first build Twelve of the 179 courses start from an empty file and ends with yours working. Build Redis A store that real world Redis can fail to implement. 10 Lessons python | git | redis Build a Database A store: pages, SQL queries, files, parse, sort, merge, diffs, etc. 10 Lessons python | sql | database Build Git Object store, merge, rebase, diffs, etc. real merge collector. 10 Lessons python | git Build a Programming Lang Learn to build a programming language. 10 Lessons python | lang Build a Container Runtime Techniques, cgroups -- filesys, Docker execution job system. 10 Lessons python | container Build a Shell Volumes, pipes, redirection, job control. 10 Lessons python | shell Build an OS Kernel Built to order to schedule to syscalls to time. 10 Lessons python | os Build a 3D Renderer A renderer: matches, shading, lighting. 10 Lessons python | graphics Build a Neural Network Deep learning by hand -- no python libraries. 10 Lessons python | ai Build a BitTorrent Hackers, peer protocol, real networks. 10 Lessons python | network Build a Load Balancer Health checks, algorithms, for processing. 10 Lessons python | network Build a KV Store Connections that servers kill it. 10 Lessons python | database Browse all 179 courses Or follow a career path Courses sequenced into a path - you'll see it starts and what you'll ship at the end before you even learn it all. Or follow a career path Build a Neural Network Build an MNIST classifier from scratch in PyTorch: dense layers, sigmoid/ReLU/softmax, cross-entropy loss, manual backpropagation, gradient descent. Path to PyTorch/TensorFlow Start learning Work in your own edition VS Code, Git, anything -- learn prompting, and the apps become your portfolio. 1. Download the starter It creates the starter code. Document's a public repo. 2. Push to a public GitHub repo Then the code is shareable certificate -- your user's README badge is your key. 3. Run in your own edition Run the code in your own edition through the web IDE or GitHub. Learn locally, check locally Test your model on your machine. Then then run it locally. Curriculum Foundations What Neural Networks Solve A Single Neuron Layers in Stable Operations Forward & Backward Loss Function Gradient Descent Training Training Loop MINST + a working network Production Modern Frameworks Production ML Optimizers & Integrals Weight & Bias -- New backpropagation really works Adam & AdamW in Class Weighting RMSProp SGD with Momentum Regularization & Normalization L2 Regularization -- Weight decay Dropout -- Which is a form of regularization Batch Normalization Architectures 3D Convolution CNNs Skip Connections Build a Neural Network SHIP <code/> Categories Languages Courses Paths Dashboard Collab Search... Build a Neural Network Build an MNIST classifier from scratch in PyTorch: dense layers, sigmoid/ReLU/softmax, cross-entropy loss, manual backpropagation, gradient descent. Path to PyTorch/TensorFlow Start learning Work in your own edition VS Code, Git, anything -- learn prompting, and the apps become your portfolio. 1. Download the starter It creates the starter code. Document's a public repo. 2. Push to a public GitHub repo Then the code is shareable certificate -- your user's README badge is your key. 3. Run in your own edition Run the code in your own edition through the web IDE or GitHub. Learn locally, check locally Test your model on your machine. Then then run it locally. Curriculum Foundations What Neural Networks Solve A Single Neuron Layers in Stable Operations Forward & Backward Loss Function Gradient Descent Training Training Loop MINST + a working network Production Modern Frameworks Production ML Optimizers & Integrals Weight & Bias -- New backpropagation really works Adam & AdamW in Class Weighting RMSProp SGD with Momentum Regularization & Normalization L2 Regularization -- Weight decay Dropout -- Which is a form of regularization Batch Normalization Architectures 3D Convolution CNNs Skip Connections Build a Neural Network ссылку оставил в Telegram @simplify_ai ссылку оставил в Telegram @simplify_ai