Build a Deep Facial Recognition App - Preparing Data for Deep Learning - TF Dataloader
Learn to build a deep facial recognition app using TensorFlow, covering data preparation, image processing, and pipeline creation for training and testing a Siamese Neural Network model.
Ways to Use ChatGPT AI with GTM
Discover 10 innovative ways to leverage ChatGPT AI for enhancing Google Tag Manager efficiency, streamlining tracking processes, and optimizing data collection strategies.
Stable Diffusion - Master AI Art: Installation, Prompts, Txt2img-Img2img, Out-Inpaint and Resize Tutorial
Comprehensive tutorial on Stable Diffusion AI art generation, covering installation, prompts, text-to-image, image-to-image, outpainting, inpainting, and advanced techniques for creating diverse AI-generated artwork.
High Fidelity Neural Audio Compression - Paper & Code Explained
Explore neural audio compression techniques achieving 10x compression rates, with in-depth analysis of paper and code implementation, including VQ-VAE, VQ-GAN, and AudioGen applications.
AudioGen- Textually Guided Audio Generation - Paper Explained
Explore text-guided audio synthesis with AudioGen, delving into its architecture, audio representation, language modeling, and innovative approaches for generating diverse sounds from textual descriptions.
OpenAI Whisper - Robust Speech Recognition via Large-Scale Weak Supervision
Explore OpenAI's Whisper: a robust speech recognition system using large-scale weak supervision. Dive into the paper, code, and architecture, covering dataset collection, evaluation metrics, and practical implementation.
BigScience BLOOM - 3D Parallelism Explained - Large Language Models - ML Coding Series
Explore 3D parallelism in large language models: pipeline, model, and data parallelism. Dive into BLOOM's codebase to understand scaling techniques behind recent ML breakthroughs.
Training Large Language Models - GPT-NeoX-20B, BigScience BLOOM, OPT-175B Explained
Explore three groundbreaking large language models: BLOOM, OPT, and GPT-NeoX-20B. Gain insights into their development, challenges faced during training, and unique features of each project.
Get Started With Stable Diffusion - Code, HF Spaces, Diffusers Notebooks
Learn three methods to use Stable Diffusion: HuggingFace Spaces, Colab notebooks, and local setup. Gain practical skills in image generation, metadata reproduction, and interpolation techniques.
DALL-E Mini Explained - ML Coding Series
Comprehensive exploration of DALL-E mini, covering its architecture, components, and implementation details. Includes code walkthrough and explanations of key concepts in image synthesis.
Diffusion Models Beat GANs on Image Synthesis - ML Coding Series - Part 2
Explore diffusion models for image synthesis, focusing on classifier guidance, training, and sampling techniques. Includes code walkthrough and paper analysis.
End to End Object Detection With Transformers
Comprehensive walkthrough of Facebook's DETR model, covering implementation details, attention visualization, and training process for end-to-end object detection using transformers.
NeuroEvolution of Augmenting Topologies and Compositional Pattern Producing Networks
Explore NEAT and CPPN algorithms for evolving neural network architectures and weights, and their applications in developmental biology modeling and image generation.
POET - Paired Open-Ended Trailblazer - Paper Explained
Explore POET algorithm: generating complex learning environments and solutions. Dive into evolutionary search, environment encoding, agent modeling, and curriculum comparison for AI advancement.
Tensor Programs - Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer
Explore μTransfer: a technique for tuning large neural networks via zero-shot hyperparameter transfer, making optimal hyperparameters stable with respect to width scaling.
VOS - Learning What You Don't Know By Virtual Outlier Synthesis
Explore virtual outlier synthesis for robust image classification and object detection, enhancing out-of-distribution awareness in AI models through innovative feature space sampling techniques.
ConvNeXt- A ConvNet for the 2020s - Paper Explained
Explore ConvNeXt, a modern ConvNet outperforming vision transformers in computer vision tasks. Learn about its design, training, and performance across various applications.
Machine Learning with Flax - From Zero to Hero
Comprehensive guide to Flax, a JAX-based ML library. Learn basics, custom models, optimization, and practical examples like linear regression and CNN on MNIST. Ideal for ML enthusiasts.
A Neural Network Solves and Generates Mathematics Problems by Program Synthesis - Paper Explained
Explore how OpenAI's Codex model solves university-level math problems through program synthesis, covering calculus, differential equations, and linear algebra. Learn about prompt engineering and problem generation techniques.
OpenAI GLIDE - Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
Explore OpenAI's GLIDE model for photorealistic image generation and editing using text-guided diffusion models, outperforming DALL-E with advanced techniques and impressive results.
Efficient Geometry-Aware 3D Generative Adversarial Networks - GAN Paper Explained
Explore cutting-edge 3D generative models with a deep dive into efficient geometry-aware GANs, NeRF technology, and novel scene representation techniques for advanced computer vision applications.