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Jeff Heaton offers a brief, under 1-hour tutorial on Python and Google CoLab for those familiar with other programming languages, focusing on data science and machine learning.
Learn to train StyleGAN with your own images in less than an hour with Jeff Heaton. Covers image preparation and using Colab for training.
Learn to install TensorFlow/Keras with GPU support on Windows 11 from Jeff Heaton in under an hour, using a pip install for the latest version.
Learn to create and denoise autoencoders in Keras and Tensorflow with Jeff Heaton in less than an hour. This online material is part of a hybrid format taught at Washington University.
Learn to create ensembles with random forests and deep neural networks using Keras and scikit-learn in less than an hour with Jeff Heaton.
Learn to use cross-validation with Keras and scikit-learn in less than an hour with Jeff Heaton. This online material is part of a hybrid program at Washington University in St. Louis.
Learn to implement early stopping and encode a feature vector for a Keras neural network in less than an hour with Jeff Heaton.
Learn to construct neural networks using TensorFlow and Keras for classification and regression in less than an hour with Jeff Heaton.
Learn deep neural network basics with Jeff Heaton in under an hour. Understand activation functions, bias neurons, and how to calculate network output.
Learn to train 256x256 GANs on NVIDIA GEFORCE RTX 3060 Ti with 8GB RAM, by adjusting evaluation metrics and increasing swap size, in under an hour with Jeff Heaton.
Learn to create your own GAN images with Jeff Heaton's guide. Understand the process from image collection to GAN training, using a GPU. Less than 1-hour workload.
Learn to install NVIDIA StyleGAN2 ADA for PyTorch on Windows 10, including training and image generation, in under an hour with Jeff Heaton.
Learn Python 3D programming with Blender from Jeff Heaton. This less than 1-hour material covers scripting, interface, rendering, and more.
Learn from Jeff Heaton's student, Jifan Zhang, about using convolution neural networks in an ensemble for computer vision counting. Less than 1-hour workload.
Learn to use FFMPEG for encoding/decoding videos for offline machine learning applications with Jeff Heaton. Less than 1-hour workload.
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