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Learn Transfer Learning, earn certificates with free online courses from Stanford, UC Irvine, Peking University, IIT Bombay and other top universities around the world. Read reviews to decide if a class is right for you.
Master PyTorch for neural networks: classification, CNNs, object detection, style transfer, and RNNs. Hands-on exercises in data preparation, model building, and advanced techniques for image and audio processing.
Master deep learning with Keras: from wine quality prediction to advanced image classification using CNNs, transfer learning, and GPU acceleration. Optimize models, implement data augmentation, and deploy in real-world scenarios.
Master advanced CNNs, transfer learning, and RNNs. Apply cutting-edge techniques to real-world datasets, from medical imaging to text generation. Gain practical skills through hands-on case studies and industry-relevant projects.
Unlock the potential of deep learning by mastering Convolutional Neural Networks and Transfer Learning with hands-on TensorFlow and Keras experience for image and text classification.
Dive into foundational concepts of Large Language Models, exploring neural networks, transformer architecture, and practical applications while mastering pre-training and fine-tuning techniques.
Master advanced AI techniques, from ensemble methods to ethical GenAI implementation, while building scalable systems and completing a real-world capstone project using Microsoft Azure.
Comprehensive exploration of Artificial Neural Networks and Convolutional Neural Networks, covering fundamental principles, applications, and practical implementation in diverse domains.
Explore deep learning fundamentals, computer vision, TensorFlow, Keras, transfer learning, and advanced topics like TPUs in this comprehensive introduction to neural networks.
We will cover the basics of Tensorflow and Machine Learning in the initial sessions and advanced topics in the latter part. After this course, the students will be able to build ML models using Tensorflow.
"Deep Learning with PyTorch: Zero to GANs" is a beginner-friendly online course offering a practical and coding-focused introduction to deep learning using the PyTorch framework. Enroll now to start learning.
Explore a user-friendly approach to working with transformers and large language models for natural language processing.
Explore unsupervised meta-learning techniques for few-shot image classification, including task construction, augmentation methods, and performance on benchmark datasets.
Explore intriguing properties of neural networks, including adversarial attacks, transfer, training overlap, and semantic information in units. Analyze weaknesses and spectral instability.
Learn about transformers, the go-to architecture for NLP and computer vision tasks.
Learn about using transformers in natural language processing with TensorFlow.
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