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This course includes
- 40h 20m of video
- 23 lessons
- Level: Intermediate
- Spoken in Հայերեն
- Your place is remembered
- Free in full, no card
Lessons
3 sections · 23 lessons · 40h 20m total length
Lessons 1 to 1010 lessons · 17h 16m
- Lecture 1 | Introduction to Neural Networks1h 34m
- Lecture 2 | Gradient Descent, Linear Regression1h 44m
- Lecture 3 | Logistic Regression, Regularization, Softmax Classifier1h 45m
- Lecture 4 | Stochastic Gradient Descent, Back Propagation1h 54m
- Lecture 5 | Tensorflow (part 1)1h 51m
- Lecture 6 | Normalization Initialization1h 27m
- Lecture 7 | Dropout, Batch Normalization1h 40m
- Lecture 8 | Adaptive Momentum (ADAM), Tensorflow keras1h 36m
- Lecture 9 | Convolution1h 54m
- Lecture 10 | Famous Convolutional Neural Networks1h 51m
Lessons 11 to 2010 lessons · 18h 12m
- Lecture 11 | Receptive Field, Transfer Learning1h 57m
- Lecture 12 | Multitask Learning Metrics1h 51m
- Lecture 13 | Recurrent Neural Networks1h 51m
- Lecture 14 | Long short-term memory (LSTM)1h 48m
- Lecture 15 | Attention Transformers1h 55m
- Lecture 16 | Dilated & Transposed Convolutions1h 44m
- Lecture 17 | Kullback–Leibler divergence, Autoencoders1h 50m
- Lecture 18 | Variational Autoencoders, Generative Adversarial Networks1h 51m
- Lecture 19 | Generative Adversarial Networks1h 43m
- Lecture 20 | Wasserstein Generative Adversarial Networks1h 42m
Lessons 21 to 233 lessons · 4h 52m
What you need
- Some grounding helps; this one picks up past the basics.
Description
Նեյրոնային ցանցեր։ Ներածություն
Who this course is for
- People who know the basics of Machine learning and want to go further.
Those two are our reading of the course's level. The description is the author's own.