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Aprenda a construir um pipeline completo de machine learning usando scikit-learn para previsão de empréstimos, desde a ingestão de dados até o uso do modelo salvo para previsões.
Explore SpinLaunch's innovative, cost-effective, and eco-friendly kinetic launch system for satellites. Learn about the founders, technology, market position, business model, and future outlook of this groundbreaking space tech startup.
Learn to process Pandas DataFrames using shift() for row/column manipulation, timeseries updates, rolling calculations, and advanced data transformations in Python.
Learn to create modular layouts in React using Chakra UI, including header, footer, sidebar, and floating panel components. Gain practical skills for efficient and methodical UI development.
Explore and experiment with Chakra UI components directly on their website. Learn to edit, merge, and customize UI elements for faster React-based frontend development.
Comprehensive GitHub tutorial covering essential tasks using command line and desktop app, from repo setup to pull requests and stash feature.
Explore ChatGPT's fundamentals, GPT models, and training process in this concise whiteboarding session, enhancing your understanding of AI language models.
Explore modern and postmodern data stack architectures, their features, and importance in data engineering. Learn why organizations need to evolve their data infrastructure for improved analytics and decision-making.
Hands-on guide to TorchStudio: Access PyTorch datasets, train models, and compare results. Ideal for beginners and experienced users in the PyTorch ecosystem.
Learn face stylization with JoJoGAN: transfer styles to images using minimal data and GPU assistance. Covers setup, existing models, custom training, and animal face styles.
Hands-on exploration of Diffusion Models using Google Colab, covering probabilistic implementations and prebuilt models. Includes code examples and practical demonstrations of the denoising process.
Explore Variational AutoEncoders and Vector Quantized VAE, focusing on codebook explanations. Learn how these advanced techniques improve upon traditional autoencoders for better image generation and representation.
Explore AutoEncoders, latent space, and reconstruction error in VQGAN. Learn key concepts and their applications in AI, with practical examples and in-depth explanations.
Learn to build a text-to-image application using DALL-E mini in Python. Covers model setup, code implementation, and result generation, providing hands-on experience with AI-driven image creation.
Learn to create NeRF scenes from videos or images using NVIDIA Instant-ngp. This hands-on tutorial covers environment setup, data preparation, and various NeRF visualization techniques on Ubuntu 22.04.
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