Practical Deep Learning for Coders 2019
Comprehensive deep learning course covering image classification, NLP, tabular data, and advanced topics. Includes hands-on coding and ethical considerations.
Deep Learning from the Foundations
Explore advanced deep learning techniques, from model training to optimization, with hands-on lessons covering ULMFiT, Swift for deep learning, and more.
Practical Deep Learning for Coders - 2020
Learn essential deep learning skills for modern applications through hands-on coding exercises and comprehensive lessons, suitable for both beginners and experienced programmers.
Deep Learning Tutorials
Explore TensorFlow syntax and compare versions in this comprehensive tutorial, covering machine learning fundamentals and practical applications in data science.
Restricted Boltzmann Machines
Explore Restricted Boltzmann Machines: their layered structure, hidden and visible layers, statistical independence, and applications in modeling high-dimensional data like images.
R Tutorials
Learn essential R skills for data analysis, visualization, and machine learning, covering statistics, deep learning, Plotly, and real-world applications like COVID-19 data extraction.
Introduction to Deep Learning for Everyone
Learn deep learning fundamentals using Keras and TensorFlow in R, covering regression, neural networks, regularization, and convolutional networks for practical applications.
Social Science Methods & Automated Data Algorithms
Explore cutting-edge data algorithms in social science, covering AI ethics, privacy implications, and innovative applications like deep learning for urban analysis.
Convolution
Explore convolution through intuitive descriptions, equations, and worked examples of typical functions, covering various applications and related concepts.
Convolution in One Dimension for Neural Networks
Comprehensive exploration of 1D convolution in neural networks, covering theory, implementation, and practical application for time series data analysis and model building.
Convolution in Two Dimensions
Explore 2D convolution, softmax, and batch normalization. Build a CNN for MNIST digits using Cottonwood, covering model architecture, training, and evaluation techniques.
Laplace Transforms and Solving ODEs
Explore Laplace Transforms to solve complex differential equations, focusing on discontinuities and impulses. Learn key properties, applications, and techniques for various mathematical scenarios.
Group Equivariant Deep Learning - 2022
Explore group equivariant deep learning, covering group theory, convolutional neural networks, steerable kernels, and equivariant graph neural networks for advanced machine learning applications.
How Neural Networks Work
This video sequence tracks the lecture sequence in course 313 from the End to End Machine Learning School, How Neural Networks Work.
Understanding the Machine Learning Process and Embedding Models into Apps
Learn to build ML models with Azure ML and VS Code, operationalize them in apps, and implement MLOps practices. Covers PyTorch Lightning, model prediction, and integration with DevOps and Kubernetes.
AI Show Live - PyTorch Enterprise
Explore PyTorch Enterprise on Azure with Alon Bochman: Learn about the collaboration, features, and benefits of this exciting announcement from Microsoft's AI Show Live.
Tagging Audio Using Deep Learning
Learn to use deep learning for audio tagging, converting sounds to images and building a classifier model to categorize songs by mood. Includes hands-on demo and practical insights.
Intro to PyTorch Tutorial - Building Fashion Recognizer
Learn to build a fashion recognizer using PyTorch in this hands-on tutorial. Covers core functionality, network architecture, loss functions, optimizers, and TensorBoard integration for effective model training.
Get Started with PyTorch
Explore PyTorch's fundamentals, from data handling to model building and deployment. Learn about its unique features, strong community, and ecosystem for effective deep learning development.
AI Show - AI Playground & Cognitive Services Vision APIs
Explore Azure Machine Learning Designer, VS Code ML extension, and PyTorch basics with experts. Demystify ML and NLP concepts while learning about Cognitive Services and AI Playground development.
Learning Machine Learning with .NET, PyTorch and the ONNX Runtime
Explore machine learning with .NET, PyTorch, and ONNX Runtime. Learn model training, accuracy assessment, and cross-framework interoperability for efficient ML development and deployment.