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# --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # format_version: '1.5' # jupytext_version: 1.14.4 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- import pandas as pd import random oos = pd.read_csv('...
fuzzy_similarity/OOS_context.ipynb
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LogisticRegression.ipynb
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_notebooks/flights_scrapper.ipynb
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Feature Extraction/.ipynb_checkpoints/ADS_Extensive_Feature_Extraction_Technical_Indicators_Final23Apr-checkpoint.ipynb
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quests/bq-teradata/01_teradata_bq_essentials/labs/bigquery_essentials_for_teradata_users.ipynb
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software/samples/notebooks/Darwin Mini gait generation (research).ipynb
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Transformers/Tasks/named-entity-recognition-simple-usage.ipynb
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Diena_14_JSON/Using_JSON_APIs.ipynb
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ML dataset - Iris.ipynb
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examples/example.ipynb
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notebooks/Segmentor DeepLabV3 v04.ipynb
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04_macierze2.ipynb
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4-seaborn/.ipynb_checkpoints/Exo3-checkpoint.ipynb
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Univar_LSTM/2_LSTM_Univar - 10VNQ.ipynb
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rascunho.ipynb
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apps/annon/evaluate_mask_rcnn_report.ipynb
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Notebook_QBSolv_community_detection.ipynb
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test.ipynb
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notebooks/MyFirstNotebook.ipynb
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docs/tutorials/demo-regression.ipynb
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bottom-up-attention/demo.ipynb
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spectrum-checkpoint.ipynb
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solutions by participants/ex3/ex3-HojunLee-236cnot.ipynb
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Statistics Python Essential Training - Linkedin Learning/4). Introduction to Statistical Modeling/05_06/05_06_bayesian_end.ipynb
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Chapter08/Exercise8.03/Exercise8_03.ipynb
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crowd-counting/crowd-counting.ipynb
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site/ja/tutorials/text/word_embeddings.ipynb
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module1/assignment_applied_modeling_1.ipynb
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Notebooks/NB04b_Peptide_Identification.ipynb
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cw_nets/scripts/Demo-Rasterio.ipynb
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2285069.ipynb
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t_test.ipynb
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appa.ipynb
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1_data-preprocessing.ipynb
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exp/ukrainian_notebook_training/XLSR/1h_per_ukrainian_experiment.ipynb
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_solved/workflow_example_evaluation.ipynb
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code/Proyecto/Jupyter/eval_mun.ipynb
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Ex_Files_Python_Data_Functions/Exercise Files/07_03_violin_plots.ipynb
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examples/Marks/Pyplot/Candles.ipynb
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t81_558_class_03_3_save_load.ipynb
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poster/plots.ipynb
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ch_03/3-cleaning_data.ipynb
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Numpy/Numpy End to End.ipynb
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source/sample_ml/Chapter03/3-3 NMF.ipynb
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2016/tutorial_final/77/Tutorial.ipynb
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ref/gorjetaNebulosa.ipynb
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courses/machine_learning/deepdive2/launching_into_ml/labs/automl-tabular-classification.ipynb
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introduction-to-dask.ipynb
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AI_Generated_Star_Wars.ipynb
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snm/snm/project/adminwikipedia/mineWipipediaData-fords.ipynb
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Chapter13/Exercise 13.6/FeudalQL.ipynb
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Starter_Files/.ipynb_checkpoints/challenge-checkpoint.ipynb
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Tarea10.ipynb
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docs/source/examples/R33/create_plots.ipynb
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explore_ligpy_results.ipynb
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Analyse_TOP_250_IMBD.ipynb
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dev_notes.ipynb
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Datascience_With_Python/Deep Learning/Projects/Fashion MNIST using CNNs/fashion_mnist_using_CNNs.ipynb
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07_Results.ipynb
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nbs/05_model.external.ipynb
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stego_proj/.ipynb_checkpoints/Hide-checkpoint.ipynb
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notebooks/demo.ipynb
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test.ipynb
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notebook/pandas_dataframe_rename.ipynb
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resources/algopy/parenthesisMatch.ipynb
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tensorflow/lite/g3doc/performance/post_training_integer_quant.ipynb
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devel/ML_PredictStressStrain.ipynb
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kNN/notebook/KNN.ipynb
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Problemas Propostos. Pag. 172 - 175/24.ipynb
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notebook/time-warping-normalisation-t2w.ipynb
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15_introduccion_a_sympy.ipynb
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notebooks/Decision Tree - Building.ipynb
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word2vec.ipynb
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src/Basic LSTM.ipynb
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examples/Example2_statistics.ipynb
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notebooks/2_generate_sample.ipynb
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Archive/Other tests/Optimisation analysis.ipynb
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slide_deck_template (1).ipynb
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Unit_3_Sprint_1_Software_Engineering_Study_Guide.ipynb
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Lesson 08/exercise.ipynb
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Test Models.ipynb
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Section02/Walkthrough_Section 2-1_Working with a NLP Pipeline.ipynb
# --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # format_version: '1.5' # jupytext_version: 1.14.4 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %matplotlib inline # # # Add Cell Connectivity To P...
locale/examples/filters-general/add-cell-connectivity-to-points.ipynb
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exercises/04. Let's write a cleaning function-working.ipynb
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Abhishek Doshi 181060025.ipynb
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climatology_analysis_notebooks/Buoyancy_correlation.ipynb
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session/entities/alxlnet-base.ipynb
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notebooks/pyro_intro.ipynb
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exercise-1/exercise.ipynb
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mathematics-python-for-data-analysis/task-similarity-texts/solution.ipynb
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exercicio-03.ipynb
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12_Sorting_searching_and_counting_Solutions.ipynb
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20200823/Experiment3/.ipynb_checkpoints/simulation-checkpoint.ipynb
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Lab_07_2_LogisticRegression_Tweets.ipynb
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Binary_Classification.ipynb
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main/nbs/mdling/fineTuning/ft_vulnerability_gpt2.ipynb
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examples/api-docs/newma_online.ipynb
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TPU_mnist.ipynb
# --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # format_version: '1.5' # jupytext_version: 1.14.4 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # # 概率和信息论 # ### 基本概念 # * 随机变量: 可以随机取不同值得变量,在机器学习算法中,每...
DeepLearningBook/.ipynb_checkpoints/probability and the theory of information-checkpoint.ipynb
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app/python_scripts/deep_dives/.ipynb_checkpoints/large_grid-checkpoint.ipynb