- .ipynb_checkpoints
- .localenv
- datasets
- docker
- images
- 01_the_machine_learning_landscape.ipynb
- 02_end_to_end_machine_learning_project.ipynb
- 03_classification.ipynb
- 04_training_linear_models.ipynb
- 05_support_vector_machines.ipynb
- 06_decision_trees.ipynb
- 07_ensemble_learning_and_random_forests.ipynb
- 08_dimensionality_reduction.ipynb
- 09_up_and_running_with_tensorflow.ipynb
- 10_introduction_to_artificial_neural_networks.ipynb
- 11_deep_learning.ipynb
- 12_distributed_tensorflow.ipynb
- 13_convolutional_neural_networks.ipynb
- 14_recurrent_neural_networks.ipynb
- 15_autoencoders.ipynb
- 16_reinforcement_learning.ipynb
- _overview.md
- app_spec.yml
- book_equations.ipynb
- extra_autodiff.ipynb
- extra_capsnets-cn.ipynb
- extra_capsnets.ipynb
- future_encoders.py
- index.ipynb
- LICENSE
- math_linear_algebra.ipynb
- README.md
- requirements.txt
- tensorflow_graph_in_jupyter.py
- tools_matplotlib.ipynb
- tools_numpy.ipynb
- tools_pandas.ipynb
hands-on-machine-learning