Python for Machine Learning

python tutorial, staging for deep/machine learning course

Run the jupyter notebook on anaconda3 environment

This course is the basic deep learning course that follows closely on Jeremy Howard's course.fast.ai

Name		Name	Last commit message	Last commit date
Latest commit History 121 Commits
.idea		.idea
docs		docs
experiments		experiments
papers		papers
1.1_2_variables_functions_and_loops.ipynb		1.1_2_variables_functions_and_loops.ipynb
1.1_lesson1.ipynb		1.1_lesson1.ipynb
1.2_lesson2.ipynb		1.2_lesson2.ipynb
1.3_lesson3.ipynb		1.3_lesson3.ipynb
1.4_lesson4.ipynb		1.4_lesson4.ipynb
1.5_lesson5.ipynb		1.5_lesson5.ipynb
1.6_generators_and_comprehensions.ipynb		1.6_generators_and_comprehensions.ipynb
1.7.2_decorators.ipynb		1.7.2_decorators.ipynb
1.7.3_class_and_magic_functions.ipynb		1.7.3_class_and_magic_functions.ipynb
1.7_labyrinth_game.ipynb		1.7_labyrinth_game.ipynb
1.9_python_test.ipynb		1.9_python_test.ipynb
2.1.1_linux_lesson1.ipynb		2.1.1_linux_lesson1.ipynb
2.1.2_linux_environment.ipynb		2.1.2_linux_environment.ipynb
2.2_matplot_excercise_LTC_BTC.ipynb		2.2_matplot_excercise_LTC_BTC.ipynb
3.0_mnist_basic_intro.ipynb		3.0_mnist_basic_intro.ipynb
3.1.2_how_machine_learns_to_read.ipynb		3.1.2_how_machine_learns_to_read.ipynb
3.1_nn_2_cnn_2_densenet.ipynb		3.1_nn_2_cnn_2_densenet.ipynb
3.2_understand_rnn_lstm.ipynb		3.2_understand_rnn_lstm.ipynb
3.3_fun_with_pic_and_optimizer.ipynb		3.3_fun_with_pic_and_optimizer.ipynb
3.4_dataset_split.ipynb		3.4_dataset_split.ipynb
9.0.1_pythorn2mysql_template.ipynb		9.0.1_pythorn2mysql_template.ipynb
README.md		README.md
USvideos.csv		USvideos.csv
class_in_python.png		class_in_python.png
image.png		image.png

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