MyPhatshala

Deep Learning

Neural networks with TensorFlow and PyTorch.

Advanced6 modules21 lessonsFree · no sign-up
0 of 21 lessons published
View syllabus

Syllabus

01 FoundationsHow neural networks work. 6 lessons
  1. 1.1What is deep learning?Coming soon
  2. 1.2The perceptronComing soon
  3. 1.3Activation functionsComing soon
  4. 1.4Forward propagationComing soon
  5. 1.5Backpropagation step by stepComing soon
  6. 1.6Loss functions and optimisersComing soon
02 FrameworksBuilding networks in code. 2 lessons
  1. 2.1TensorFlow and Keras basicsComing soon
  2. 2.2PyTorch basicsComing soon
03 TrainingMaking networks learn well. 3 lessons
  1. 3.1Overfitting, dropout and regularisationComing soon
  2. 3.2Batch normalisationComing soon
  3. 3.3Hyperparameter tuning for neural networksComing soon
04 CNNsNetworks for images. 4 lessons
  1. 4.1Convolutional neural networksComing soon
  2. 4.2Pooling and paddingComing soon
  3. 4.3Famous architectures: LeNet, VGG, ResNetComing soon
  4. 4.4Transfer learningComing soon
05 RNNsNetworks for sequences. 3 lessons
  1. 5.1Recurrent neural networksComing soon
  2. 5.2LSTM and GRUComing soon
  3. 5.3Sequence-to-sequence modelsComing soon
06 AdvancedModern architectures. 3 lessons
  1. 6.1AutoencodersComing soon
  2. 6.2GANsComing soon
  3. 6.3Attention and transformersComing soon