北京雁栖湖应用数学研究院

Course Intruduction:
Master the fundamentals of deep learning and break into AI. Recently updated with cutting-edge techniques!
Deep Learning with code, math, and projects. Learning by doing!
Implemented with PyTorch, NumPy/MXNet, TensorFlow, Jax, and PaddlePaddle.
Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications
Train test sets, analyze variance for DL applications, use standard techniques and optimization algorithms, and build neural networks in PyTorch, etc.
Build a CNN and apply it to detection and recognition tasks, use neural style transfer to generate art, and apply algorithms to image and video data
Build and train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering
Skills you'll gain after complete the course:
Machine Learning expert
Recurrent Neural Network
PyTorch, NumPy/MXNet, TensorFlow, Jax, and PaddlePaddle
Convolutional Neural Network
Artificial Neural Network
Transformers
Course Complete Certification issued by BIMSA?