Deep Learning Specialization

Colleagues, in the “Deep Learning Specialization” you will 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 TensorFlow, create 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, and train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering. You will be equipped with leading-edge skills involving Machine Learning, Deep Learning, Artificial Neural Networks, Machine Learning Algorithms, Applied Machine Learning, Python Programming, Network Model, Algorithms, Computer Programming, Computer Vision, Network Architecture, and Human Learning. You will build and train neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more. Applied Learning Project. Training lessons include: 1) Named Entity Recognition and Question Answering, 2) Neural Networks and Deep Learning, 3) Improve Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization, 4) Structuring Machine Learning Projects, 5) Convolutional Neural Networks, and 6) Sequence Models. 

Enroll today (teams & execs welcome): https://imp.i384100.net/EK3BjP 

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