Deep-Learning-Specialization-Coursera and deep-learning-coursera
The two repositories are competitors, as both offer solutions to the same assignments within the Deep Learning Specialization on Coursera by Andrew Ng.
About Deep-Learning-Specialization-Coursera
abdur75648/Deep-Learning-Specialization-Coursera
This repo contains the updated version of all the assignments/labs (done by me) of Deep Learning Specialization on Coursera by Andrew Ng. It includes building various deep learning models from scratch and implementing them for object detection, facial recognition, autonomous driving, neural machine translation, trigger word detection, etc.
This collection of assignments provides practical examples for understanding and building advanced artificial intelligence models. It offers ready-to-use code for tasks like recognizing objects in images, identifying faces, and translating languages. Anyone learning or teaching deep learning concepts would find these practical solutions helpful.
About deep-learning-coursera
Kulbear/deep-learning-coursera
Deep Learning Specialization by Andrew Ng on Coursera.
Contains Jupyter notebooks implementing core deep learning concepts—from logistic regression and multi-layer perceptrons through CNNs (ResNets, Keras) and sequence models (RNNs)—alongside quiz materials across five course modules. Implementations use NumPy for foundational algorithms and TensorFlow/Keras for practical applications, covering optimization techniques (gradient descent, Adam), regularization, and batch normalization. Spans the full specialization curriculum from foundational neural network theory to advanced architectures for computer vision and natural language processing tasks.
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