data_science-master
.gitignore
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technical_assessments
README.md
107B
company1
challenge.html
1.36MB
instrucoes.pdf
135KB
challenge.ipynb
1.02MB
cheatsheets
probability.pdf
789KB
interview_questions.pdf
655KB
linux.png
460KB
conda.pdf
292KB
deep_learning_notation.pdf
256KB
machine_learning.pdf
1.25MB
machine_learning_performance_improvement.pdf
134KB
git_github.pdf
369KB
README.md
40B
rnn_input_shape.png
332KB
sql.pdf
225KB
example_numpy_style_python_docstrings.py
10KB
README.md
97B
neural_networks
tensorboard_tutorial.ipynb
32KB
seglearn_plotting_neural_network_training_curves.ipynb
90KB
stateful_stateless_lstm.ipynb
158KB
seglearn_time_series_forecasting.ipynb
90KB
MNIST_data
train-images-idx3-ubyte.gz
9.45MB
train-labels-idx1-ubyte.gz
28KB
t10k-labels-idx1-ubyte.gz
4KB
t10k-images-idx3-ubyte.gz
1.57MB
README.md
60B
figures
convolutional_recurrent_neural_network2.png
10KB
tensorboard_tutorial.png
282KB
how_to_develop_deep_learning_models_for_univariate_time_series_forecasting_all.png
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how_to_develop_deep_learning_models_for_univariate_time_series_forecasting_cnn.png
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how_to_develop_deep_learning_models_for_univariate_time_series_forecasting_cnn_lstm_causal.png
21KB
README.md
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convolutional_recurrent_neural_network.png
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how_to_develop_deep_learning_models_for_univariate_time_series_forecasting_conv_lstm.png
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how_to_develop_deep_learning_models_for_univariate_time_series_forecasting_lstm.png
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how_to_develop_deep_learning_models_for_univariate_time_series_forecasting_cnn_lstm.png
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how_to_develop_deep_learning_models_for_univariate_time_series_forecasting_mlp.png
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how_to_develop_deep_learning_models_for_univariate_time_series_forecasting.ipynb
138KB
ibm
README_moviedataset.txt
8KB
the_best_classifier.ipynb
209KB
collaborative_filtering_movies.ipynb
58KB
content_based_movies.ipynb
72KB
README.md
200B
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