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Nyandwi

added new guide on mlops

May 10, 2023

e769f56 · May 10, 2023

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Name		Name	Last commit message	Last commit date
parent directory ..
assets		assets
extras		extras
.DS_Store		.DS_Store
00_intro_to_python.ipynb		00_intro_to_python.ipynb
01_intro_to_Numpy_for_data_computation.ipynb		01_intro_to_Numpy_for_data_computation.ipynb
02_data_manipulation_with_pandas.ipynb		02_data_manipulation_with_pandas.ipynb
03_data_visualizations_with_matplotlib.ipynb		03_data_visualizations_with_matplotlib.ipynb
04_data_visualization_with_seaborn.ipynb		04_data_visualization_with_seaborn.ipynb
05_data_visualization with_pandas.ipynb		05_data_visualization with_pandas.ipynb
06_exploratory_data_analysis.ipynb		06_exploratory_data_analysis.ipynb
07_intro_to_data_preparation.ipynb		07_intro_to_data_preparation.ipynb
08_encoding_categorical_features.ipynb		08_encoding_categorical_features.ipynb
09_feature_scaling.ipynb		09_feature_scaling.ipynb
10_handling_missing_values.ipynb		10_handling_missing_values.ipynb
11_ml_fundamentals.md		11_ml_fundamentals.md
12_intro_to_sklearn.ipynb		12_intro_to_sklearn.ipynb
13_linear_models_for_regression.ipynb		13_linear_models_for_regression.ipynb
14_linear_models_for_classification.ipynb		14_linear_models_for_classification.ipynb
15_support_vector_machines_for_regression.ipynb		15_support_vector_machines_for_regression.ipynb
16_support_vector_machines_for_classification.ipynb		16_support_vector_machines_for_classification.ipynb
17_decision_trees_for_regression.ipynb		17_decision_trees_for_regression.ipynb
18_decision_trees_for_classification.ipynb		18_decision_trees_for_classification.ipynb
19_random_forests_for_regression.ipynb		19_random_forests_for_regression.ipynb
20_random_forests_for_classification.ipynb		20_random_forests_for_classification.ipynb
21_ensemble_models.ipynb		21_ensemble_models.ipynb
22_intro_to_unsupervised_learning_with_kmeans_clustering.ipynb		22_intro_to_unsupervised_learning_with_kmeans_clustering.ipynb
23_a_practical_intro_to_principal_components_analysis.ipynb		23_a_practical_intro_to_principal_components_analysis.ipynb
24_intro_to_neural_networks.ipynb		24_intro_to_neural_networks.ipynb
25_intro_to_tensorflow_for_deeplearning.ipynb		25_intro_to_tensorflow_for_deeplearning.ipynb
26_neural_networks_for_regresion_with_tensorflow.ipynb		26_neural_networks_for_regresion_with_tensorflow.ipynb
27_neural_networks_for_classification_with_tensorflow.ipynb		27_neural_networks_for_classification_with_tensorflow.ipynb
28_intro_to_computer_vision_and_cnn.ipynb		28_intro_to_computer_vision_and_cnn.ipynb
29_cnn_for_real_world_data_and_image_augmentation.ipynb		29_cnn_for_real_world_data_and_image_augmentation.ipynb
30_cnn_architectures_and_transfer_learning.ipynb		30_cnn_architectures_and_transfer_learning.ipynb
31_intro_to_nlp_and_text_preprocessing.ipynb		31_intro_to_nlp_and_text_preprocessing.ipynb
32_using_word_embeddings_to_represent_texts.ipynb		32_using_word_embeddings_to_represent_texts.ipynb
33_recurrent_neural_networks.ipynb		33_recurrent_neural_networks.ipynb
34_using_cnns_and_rnns_for_texts_classification.ipynb		34_using_cnns_and_rnns_for_texts_classification.ipynb
35_using_pretrained_bert_for_text_classification.ipynb		35_using_pretrained_bert_for_text_classification.ipynb
index.md		index.md
outline.md		outline.md
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