
Learn to build a real-time body segmentation app using TensorFlow.js and React.js. Explore installation, app development, and live segment detection with a webcam in under 30 minutes.

Learn to implement real-time pose estimation using Posenet, Tensorflow.js, and React.js. Create a web app that detects body joints from webcam feed, helping perfect physical movements like sports or dance.

Learn Python fundamentals for machine learning, covering data manipulation, visualization, and deep learning tools in this comprehensive 30-day challenge.

Explore machine learning in JavaScript with TensorFlow.js, from computer vision to creative prototypes. Learn to implement ML in browsers and beyond, unlocking new possibilities for your projects.

Learn to create a custom machine learning model using TensorFlow.js for object recognition in the browser. Explore transfer learning techniques to build and train models quickly for various applications.

Explore neural networks using TensorFlow 2.0, covering key concepts, architecture, and practical implementation in Python for beginners and intermediate learners.

Explore real-time fraud analysis using open-source and closed-source solutions in a hybrid cloud environment, focusing on credit card fraud detection, AI model training, and deployment strategies.

Explore TensorFlow.js with Bekah Hawrot Weigel: learn its applications, get started with hands-on demos, and discover resources for machine learning in JavaScript.

Learn to recreate the popular TikTok timewarp filter using a webcam and TensorFlow.js. Explore machine learning techniques to create engaging visual effects for web applications.

Explore Project Panama's modern APIs for safe and efficient foreign memory and code access in Java, replacing traditional JNI methods.

Explore deep learning infrastructure considerations for cloud and on-premises deployments, covering scalability, performance optimization, and operational challenges in AI model training.

Explore how memory-augmented LLMs can revolutionize operating systems, focusing on multi-AI integration and continuous chat capabilities for next-generation computing architectures.

Explore KERAS 3's framework-agnostic capabilities for building neural networks and transformers across TensorFlow, PyTorch, and JAX platforms with advanced customization options.

Explore quantization techniques in deep learning, from uniform to non-uniform approaches, and learn practical implementation strategies for optimizing large-scale neural networks.

Master BERT model pre-training, fine-tuning, and inference using TF2 and KERAS NLP through hands-on implementation of transformers for domain-specific tasks.

Master text vectorization techniques in Keras preprocessing layers for transforming natural language inputs into numerical sequences and building efficient AI input processing pipelines.

Dive into advanced feature scaling with KERAS Feature Space, building a medical AI system to predict heart attack probabilities using structured data classification and optimized data pipelines.

Explore deep learning frameworks with Alibaba's VP AI, covering Caffe, Caffe2, and TensorFlow development insights from a pioneering expert in the field.

Develop a dog breed classification system using TensorFlow, Kubeflow, and convolutional neural networks. Compare AI predictions with DNA results for accuracy.

Step-by-step guide to implement and train a Res-UNet model for Melanoma detection using TensorFlow and Keras. Learn to build, train, test, and visualize results for accurate skin lesion segmentation.

Explore responsible AI and inclusive technology with Google's Tulsee Doshi. Learn about ethical product development, AI principles, and tools for building trustworthy, personalized experiences that benefit users.