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Welcome to the DeepLearning tour wiki!

The tour sequence is now moved to the homepage README.md

The tour sequence

• Linear Classifier
• Linear Regression
• Gradient Descent (No framework)
• Forward props & Back props
• Multilayer Perceptron
• Neural Net (No framework, only numpy)
  • vectors & tensors
  • Different neural net layers (dense, dropout, max-pooling layers)
• Data preprocessing (house price dataset, catvsdog, IMDB)
• CNN (Pytorch, TF, Keras) -> classify whales photos
• Callbacks (early stopping and etc)
• TF Dashboard
• Training model in the cloud
• Sentiment Analysis (binary classification)
• Sentiment analysis (multi-classification)
• Word2vec
• Generate song lyrics and stories
• Hyperparameter tuning
• Feature engineering
• Linear regression Kaggle competition using the above knowledge
• Generative Models
• GAN basic
• StarGAN
• CycleGAN
• Reinforcement learning

Why does this page exist?

Purpose of this page is to maintain topics to be explored in a centric forum where people can contribute to add new topics or reorder them in the correct order of learning.

References / Study group role models

• https://github.com/sachinruk/deepschool.io
• https://github.com/the-deep-learners/study-group
• https://machinelearningmastery.com/deep-learning-with-python/
  • It is a book but we may pick some topics from this