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# # How to generate publication quality tables
#
# es... | docs/source/how_to_guides/miscellaneous/how_to_generate_publication_quality_tables.ipynb |
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from scipy.stats import shapiro
import numpy as np
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import numpy as np
import matplotlib.p... | notebooks/LH_lab03_convergence.ipynb |
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import glob
im... | python/labelwise_skeleton_distance_analysis.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Day3_Assignment_2.ipynb |
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# In this exercise, try to write a program that
# ... | particle filter/new_particle.ipynb |
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from qiskit import QuantumRegister, ClassicalRegister,... | teleport.ipynb |
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# # Transfer Learning
#
# In this notebook, you'll lea... | Udacity/PyTorch Scholarship Challenge Nanodegree Program/Week-4-Introduction to PyTorch/Part-7-Loading Image Data/.ipynb_checkpoints/Part 8 - Transfer Learning (Solution)-checkpoint.ipynb |
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# ## Analyzing m5C patterns in Human oocyte and embryo... | m5C study/Human_oocyte/Human_development.ipynb |
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# # Federated Keras MNIST Tutorial
# +
#Install Tenso... | openfl-tutorials/Federated_FedProx_Keras_MNIST_Tutorial.ipynb |
# -*- coding: utf-8 -*-
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# # Tutorial de instalación de Anaconda... | setup-conda/.ipynb_checkpoints/setup_conda-checkpoint.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | RegressaoLinear_2_Curos.ipynb |
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import pandas as pd
import numpy as np
import matplotl... | BBB_logit.ipynb |
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# # How to calculate Sharpness from .wav file (time-va... | tutorials/tuto5_Sharpness-time-varying.ipynb |
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import os
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import matplotlib.pyplot ... | doc/SuppTechInfo/python/STO-SpecificStorage.ipynb |
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# + [markdown] editable=true
# # ETL Processes
# Use t... | .ipynb_checkpoints/etl-checkpoint.ipynb |
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from pprint import pprint
import pickle
from pymo... | dwh_analytic/dags/data_warehouse_prod/daily_task_eclaims.ipynb |
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import csv
fn = 'trip_data_8.csv'
f =... | Question 10.ipynb |
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# <a id="title_ID"></a>
# # JWST Pipeline Validation T... | jwst_validation_notebooks/resample/jwst_resample_miri_test/jwst_resample_miri_testing.ipynb |
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# + id="it1c0jCiNCIM" colab_type="code" outputId="e9cc62e6-5fe6-4912-f7d8-964... | cnn-in-tensorflow/rock_paper_scissors.ipynb |
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# + [markdown] id="Ueilyqz9VChj" colab_type="text"
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library(tidyver... | nb/5.fig3.auroc/plot_auroc.ipynb |
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import numpy as np
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Project 1/Project1_task2.ipynb |
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# # RL and Advanced DL: Домашнее задание 1... | RL_HW1/RL_HW1_part2.ipynb |
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# # 6) Git for good programming practices
# Related m... | source/notebooks/lecture06_git_and_github.ipynb |
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... | notebook/01-Analysis/01_IMDb_Huggingface_data_analysis.ipynb |
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# + [markdown] id="xnY85mGJjqZs"
#
# + id="40kP6K0J0W... | models/lstm/Keras_tuner_multi_BTC_3.ipynb |
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import numpy as np
import sklearn as sk
import pan... | frauddetection.ipynb |
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# # Short Bursts Distributions
#
# We look at short bu... | misc/projections_to_the_line_and_observed_distributions.ipynb |
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# Movies have form www.imdb.com/title/tt2406566/ #atom... | notebooks/IMDB-Downloader.ipynb |
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# Notebook for testing the physics module
import ... | junk/test_notebooks/physics.ipynb |
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# %matplotlib nbagg
import matplotlib.pyplot as plt
im... | 05 - Cross-validation.ipynb |
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Non-personalized
Content based
Attributes
... | notebooks/recommendations/Untitled.ipynb |
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# # Introduction
#
# This notebook predicts the `... | notebooks/8_pytorch.ipynb |
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# # Tutorial: fitting a FSRQ broad-band SE... | docs/tutorials/ec_dt_sherpa_fit.ipynb |
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# # WeatherPy
# -... | WeatherPy/WeatherPy.ipynb |
# -*- coding: utf-8 -*-
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versioninfo()
g=6.0
ENV["... | notebooks/main.ipynb |
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user_item_res = {'MAP@10': (0.06967576301474467,... | data exploration/Visualization of result.ipynb |
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# ## Numpy
# Импортировать NumPy под именем np
impor... | HomeWork 1/exercises-19469-b3240b.ipynb |
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import requests
from bs4 import BeautifulSoup
url = 'h... | Jupyter Notebooks/How to isolate data.ipynb |
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# # Face Detection
#
# Hello! In this task you will cr... | CNN/Face_Detection-(v2).ipynb |
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import numpy as np
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import scipy
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# # Analysis of Neural Networks by computin... | demos/saliency_map.ipynb |
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# + [markdown] _uuid="8510ac1d600e8b4c1e27a34a84fb4cc7... | machine learning/kernel-missing-vars.ipynb |
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# Copyright (c) Microsoft Corporation. All rights r... | tutorials/img-classification-part2-deploy.ipynb |
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... | TI Web API.ipynb |
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# Copyright 2021 NVIDIA Corporation. A... | examples/getting-started-movielens/01-Download-Convert.ipynb |
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import matplotli... | Problems/Clean_NYC_Property_Sales/Clean_NYC_Property_Sales.ipynb |
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# # Spark Accumulators
#
# Spark accumu... | spark-training/spark-python/jupyter-advanced/07 - Accumulators - Skeleton.ipynb |
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# + [markdown] id="bwPlsCuR8DZG" colab_type="text"
# A **Double Deep Q Networ... | DQN_variants/DDQN/double_DQN_cartpole.ipynb |
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# # Bagging
#
# This notebook introduces a very natural strategy to build ensembles of
# machine learning models named "bagging".
#
# "Bagging" stands for Bootstrap AGGregatING. It uses bootstrap resampling
# (random sampling with replacement) to learn several models on random
# variations of the training set. At predi... | notebooks/ensemble_bagging.ipynb |
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# # Ejercicio 1: Peticiones HTTP usando Sockets
# Aqu... | ejercicios/protocolo-http.ipynb |
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import theme
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# # Lesson 20: The Ad... | Lessons/Lesson13_AdvectionDiffusion.ipynb |
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# B... | docs/source/prevalence_notebook.ipynb |
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# # This colab notebook must be run on a **P... | Image Classification/CGIAR Wheat Growth Stage Challenge/neurofitting/zindi_cgiar_wheat_growth_stage_challenge/train_lq2_only_effnet_b3_step1/train_lq2_only_effnet_b3_step1_fold0.ipynb |
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# # Train S-CNN baseline
# +
# %load_ext autoreload
#... | exps/04_CNN_baseline/train.ipynb |
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# # Creating a Real-Time Inferenci... | 06-Deploying_a_model.ipynb |
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# ![Callysto.ca Banner](https://github.com/callysto/cu... | _build/html/_sources/curriculum-notebooks/Health/CALM/CALM-moving-out-6.ipynb |
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# # ISM Lecture 2 Part 2
#
# This content is authored ... | week02/w01_part2.ipynb |
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# <h1>Table of Contents<span c... | week2/Linear Algebra, Distance and Similarity.ipynb |
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# + [markdown] id="LohRBS18e9hB"
# # Imports
# + id="... | task3/charts.ipynb |
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# #... | community/en/nmt.ipynb |
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# Copyright (c) Microsoft Corporat... | projects/azure-ml-tutorials/machine-learning-pipelines-advanced/tutorial-pipeline-batch-scoring-classification.ipynb |
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# <a href="https://colab... | LS_DS_223_assignment.ipynb |
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# # Intertemporal consumer problem
# Team: M&M
#
# Me... | modelproject/modelproject.ipynb |
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# # Basics of Signal Processing
# **Author... | notebook_sol.ipynb |
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# # Discrete Choice Models
# ## Fair's Affair data
#... | examples/notebooks/discrete_choice_example.ipynb |
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# + [markdown] id="T3KiRqhj_jaT" colab_type="text"
# ## Week 1
#
# Use Convol... | Convolutional Neural Networks in TensorFlow/week1 Exploring a Larger Dataset/CNN in TensorFlow Week1 Note.ipynb |
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from cricsheet.fow_ana... | notebooks/ag-format-collapses-1.3.ipynb |
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# + id="A-AWSHU1NdiY"
# %%capture
# !pip install flair
# + id="22ZrZO2Qyewo"... | dependency-tagger-for-turkish-with-BERT.ipynb |
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# + id="_uYS6xIIpmWc" colab_type="code" colab={"base_uri": "https://localhost... | mental_health_chatbot.ipynb |
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# ### Exercise: Creating Cells, Executing Code
#
# 1. ... | 02-basic-python/lecture-02-exercise-solution.ipynb |
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import numpy... | Code/Analysis/models/Attention/attention_lstm1.ipynb |
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# MAP RUNNING TIME
#
# https://github.com/Make-School-... | Classwork/09.25.19..../Pyspark array manip 1.ipynb |
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# <h1>Table of Contents<span class="tocSkip"></span></h1>
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impor... | notebook/Presentazione.ipynb |
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# # Lab 02... | lab/Lab 02 - Simple Linear Regression.ipynb |
# -*- coding: utf-8 -*-
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# # GIS Client
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