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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 torch import gpytorch import matplotlib.pyp...
GP_experiments/GP_Overfitting/mlp_gp_mean.ipynb
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spectral_analysis.ipynb
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Benchmark/ProtBert.ipynb
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session/vad/export/vggvox-v2.ipynb
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notebooks/.ipynb_checkpoints/00-exploratory-checkpoint.ipynb
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autoencoder_keras/Anomaly_Detection.ipynb
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troubleshooting-debugging-techniques/week-2/quiz-slow-code.ipynb
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ipynb/T02-OOP-in-Python-Part-1.ipynb
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examples/Text_Preprocessing.ipynb
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hypergbm/examples/18.pseudo_labeling.ipynb
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doc/integrations/cortx_jupyter_integration/Examples/Pytorch-Demo.ipynb
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docs/src/internals/Mimi Meeting_5_26_2021.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 # --- # ## Introduction # This notebook is intented for the ...
no_ui.ipynb
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ConvertChatHistory.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 # --- # # Lady Tasting Tea - An Investigation # # About the ...
lecture_notes/4lady-tasting-tea.ipynb
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notebooks/data_cleaning.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 # --- # # SparkContext - number of workers and lazy evaluati...
SparkContext_Workers_Lazy_Evaluations.ipynb
# --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # format_version: '1.5' # jupytext_version: 1.14.4 # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- import geopandas as gpd import cobra.postg...
data/jupyter/Samples/CountryGrid.ipynb
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crawling_code/megastudy.ipynb
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src/ascent/python/ascent_jupyter_bridge/notebooks/Widget Tests.ipynb
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Queue.ipynb
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D26_JunaediFahmi.ipynb
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notebooks/Tests and research/4. Hyperparameters tunning.ipynb
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HW#1.ipynb
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notebooks/PowerlawSphere.ipynb
# --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # format_version: '1.5' # jupytext_version: 1.14.4 # kernelspec: # display_name: Python 2 # language: python # name: python2 # --- # <small><i>This notebook was prepared by [<NAME>](htt...
linked_lists/remove_duplicates/remove_duplicates_challenge.ipynb
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Jupyter Notebook/Yelp/Yelp-API-Data-Collection.ipynb
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MAIA_image_processing_demo_complete_case.ipynb
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Linked_list/rotate_image.ipynb
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Figure_7.ipynb
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graph neural networks/6_heterogeneous_networks.ipynb
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SeamountGeochemistry_Workflow_Update.ipynb
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pretrain/test.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 # --- # # Tutorial 3: Activation Functions # # ![Status](htt...
docs/tutorial_notebooks/tutorial3/Activation_Functions_empty.ipynb
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python/general-python/download-attachments/DownloadAttachments.ipynb
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Spam Classifier using Naive Bayesian Classifier.ipynb
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04.2 Build a recommender system based on outgoing Wikipedia links.ipynb
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lessons/09_Lesson09_flowOverCylinder.ipynb
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Set.ipynb
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notebooks/1.1_vn_power_plants.ipynb
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Clifford.ipynb
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Headbrain_Simple_linear_regression.ipynb
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examples/TFIM_example.ipynb
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docs/notebooks/cold_plasma_tensor_elements.ipynb
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Polynomial_Regression_Loan.ipynb
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09 - Translation.ipynb
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clase_4.ipynb
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python_solve_maze.ipynb
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notebooks/.ipynb_checkpoints/Intro_02_JupyterNotebooks-checkpoint.ipynb
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pittsburgh-bridges-data-set-analysis/resources/scikit-learn-examples/Classifier comparison.ipynb
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canadian_weather/04-kmeans.ipynb
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15_ContextManagersAndSomethingElse/15_ContextManagersAndSomethingElse.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 # --- # # Preprocessing Step # # ! pip install -U pip # ! p...
examples/frameworks/pytorch/notebooks/table/preprocessing_and_encoding.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 # orphan: true # --- # (tune-rllib-example)= # # # Using R...
doc/source/tune/examples/pbt_ppo_example.ipynb
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python/data_scientist_from_scratch/7_hypothesis_and_inference.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 # --- # # Constantes en Python import math math.pi math.t...
scripts/tema1/05-math-pythonADIPIZ.ipynb
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spark-training/spark-python/jupyter-advanced-caching/Iterative Algorithms - Full.ipynb
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Bank.ipynb
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scripts/Fiedler_vec_example.ipynb
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impedancia/Espectroscopia_de_Capacitancia.ipynb
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single_perceptron.ipynb
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locale/examples/01-filter/clipping-with-surface.ipynb
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User Profiles/.~user_profile.ipynb
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question-answer/squad/notebook/squad-dev-1.1-ms.ipynb
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example/RunModel/Matlab_Model_Example/Matlab_Model_Example.ipynb
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day3.ipynb
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1 - Python for Data Science/Module 3 - Python Programming Fundamentals/code/1-PY0101EN-3-1-Conditions.ipynb
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INN_VAE/INN_autoencoder_example/INN Autoencoder_mnist-glow.ipynb
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02_reproducibility_V_and_V.ipynb
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Gadgets/Fuzzy_String_Matching.ipynb
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advanced-python/2DataAndPlotting.ipynb
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python/ch10/10.3.1-2dconv-image-smoothing.ipynb
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NeuronBinaryClassification/Jupyter_Notebook/MultiLayerPerceptrop_3_train_10_test.ipynb
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MSDA_Query/query3_clinicians.ipynb
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python/detection/Add_TFLiteNMS_Plugin.ipynb
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practice-note/week_04/W04-3_text-mining-for-practice_python-crawling-practice-4.ipynb
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Project/Facebook_Portfolio.ipynb
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notebooks/final_results/seasonality_result_local_plotter.ipynb
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practice_unit-2-sprint_3.ipynb
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IPY/TKO_ADHD.ipynb
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notebooks/dprep12021.ipynb
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01_dwpc.ipynb
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explorative_analyse.ipynb
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assignment_1/total_segmentation_and_classification_model_v1.ipynb
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Design/1027/1603. Design Parking System.ipynb
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2021/12/12.ipynb
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5.2_Phenotype-LSTM-Sentences-30WordLimit.ipynb
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g3median.ipynb/g3median_test_gcn-tb1.ipynb
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ms_snips2018_2.ipynb
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docs/notebooks/api_low_level.ipynb
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workshop/lessons/03_surfaces/Working With Surfaces_lesson.ipynb
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NAACP/Doc2vec/model/Doc2Vec_Hong.ipynb
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Untitled.ipynb
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Section 5/UseSelenium.ipynb
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JupyterNotebooks/Lessons/Lesson 1.ipynb
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Notebooks/Analysis.ipynb
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am/summary.ipynb
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notebooks/tutorial/01-Introduction_and_Data_Format.ipynb
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Ly_alpha_emitters2.ipynb
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2018/PAN_AA_2018-Obfuscation.ipynb