View Code? Open in Web Editor
NEW
This project forked from gmortuza /deep-learning-specialization
This repository contains the programming assignments and slides from the deep learning course from coursera offered by deeplearning.ai
Home Page: https://www.coursera.org/specializations/deep-learning
Jupyter Notebook 99.16%
Python 0.84%
deep-learning-specialization's Introduction
Week 1 --> Introduction, NN, Why Deep learning
Week 2 --> Logistic regression, Gradient Descent, Derivatives, Vectorization, Python Broadcasting
Week 3 --> NN, Activation function, Backpropagate, Random Initialization
Week 4 --> Deep L-layer Neural network, Matrix dimension right, Why Deep representation, Building blocks of NN, Parameters vs Hyperparameters, Relationship with brain
Week 1 --> Train/Dev/Test set, Bias/Variance, Regularization, Why regularization, Dropout, Normalizing inputs, vanishing/exploding gradients, Gradient checking
Week 2 --> Mini-batch, Exponentially weighted average, GD with momentum, RMSProp, Adam optimizer, Learning rate decay, Local optima problem, Plateaus problem
Week 3 --> Tuning process, Picking hyperparameter, Normalizing activations, Softmax regression, Deep learning programming framework
Week 1 --> Why ML Strategy?, Orthogonalization, Single number evaluation metric, Satisficing and optimizing metrics, Train/dev/test distribution, Human level performance, Avoidable bias
Week 2 --> Error analysis, Incorrectly labeled data, Data augmentation, Transfer learning, Multitask learning, End-to-End Deep learning
Week 1 --> Computer vision, Edge detection, Padding, Strided convolution, Convolutions over volume, Pooling layers, CNN, Why CNN?
Week 2 --> LeNet-5, AlexNet, VGG-16, ResNets, 1x1 convolutions, InceptionNet, Data augmentation
Week 3 --> Object localization, Landmark detection, Object detection, Sliding window, Bounding box prediction, Intersection over union(IOU), Non-max suppression, Anchor box, YOLO algorithm
Week 4 --> Face recognition, One-shot learning, Siamese network, Neural style transfer
Week 1 --> RNN, Notation, Vanishing gradient, GRU, LSTM, Bidirectional RNN, Deep RNN
Week 2 --> Word representation, Word embedding, Cosine similarity, Word2Vec, Negetive sampling, GloVe words, Debiasing word
Week 3 --> Beam search, Error analysis in Beam search, Bleu score, Attention model, Speech recognition
Specialization certificate:
deep-learning-specialization's People
Contributors