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# # Use Decision Optimization to plan your diet with `... | cpd4.0/notebooks/python_sdk/deployments/decision_optimization/Use Decision Optimization to plan your diet.ipynb |
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# ## Seminar and homework (10 points total)
#
# Today ... | week04_seq2seq/practice.ipynb |
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# name: python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east... | 00_quickstart/wip/09_Detect_Model_Bias_Clarify.ipynb |
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# Remove input cells at runtime (nbsphinx)
import IPyt... | docs/contribute/benchmarks_latest_results/Prod3b/CTAN_Zd20_AzSouth_NSB1x_baseline_pointsource/DL3/overall_performance_plot_CTA.ipynb |
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# # Transfer Learning and Fine Tuning... | 2.4 Transfer Learning & Fine-Tuning.ipynb |
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# # Plot the Env and some trees
# %load_ext autoreloa... | notebooks/Simple_Rendering_Demo.ipynb |
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# # Cycleways and their impact in New Zealand
#
# ###... | notebooks/new_zealand_cycleways.ipynb |
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# # Wrangle Report
# The objective of this report is ... | wrangle_report.ipynb |
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# + colab={} colab_type="code" id="6VXPfRp... | 4.ML_models.ipynb |
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# ## Extinction risks for cartilaginous fish
#
# An ex... | twitch/.ipynb_checkpoints/Simple regression diagnostics-checkpoint.ipynb |
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# <img src="https://raw.githubusercontent.com/Qiskit/q... | hello_world/quantum_8ball.ipynb |
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# # Data preparation for tutorial
#
# This notebook co... | data/data-preparation.ipynb |
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import pickle
import joblib
objects = []
with (open... | deepgravewell/dns-query-log/result/Untitled.ipynb |
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# # Monoecious Hydrilla
# #### *Hydrilla verticillata ... | notebooks/MonoeciousHydrilla.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # M... | _build/html/_sources/rise/10c-pandas-agrupamento-rise.ipynb |
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# %matplotlib inline
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import numpy as np
import pa... | DRNN.ipynb |
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# # Diversificación y fuentes de riesgo en un portafol... | Modulo2/Clase10_DiversificacionFuentesRiesgoII.ipynb |
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import numpy as np
import pandas as pd
import pick... | Models/WBC/Diffact-keras-noncv-breastcancer.ipynb |
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# # Projeto Final
#
# ## Reconhecimento de convicção a... | scripts/Projeto_IA369_1Class_All.ipynb |
# -*- coding: utf-8 -*-
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# executing this cell will... | Mississippi_projection_illustration.ipynb |
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# ## Exercise 19: Lambda Expression for Sorting
# 1.... | Chapter02/.ipynb_checkpoints/Exercise 19-checkpoint.ipynb |
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import pandas as pd
import numpy as np
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from czifile import CziFile
import numpy as np
pwd
d... | notebooks/20181030-czifile_test.ipynb |
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# ## RSS
# You can find RSS feeds on many different s... | rss/rss_notebook.ipynb |
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# # Assignment 2
#
# Before working on this assignment... | Applied Plotting, Charting & Data Representation in Python/Assignment2.ipynb |
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# # Chapter: Recurrent Neural Networks
#
#
# # Topic: ... | Chapter_RNN/predictiveMaint_regression_RNN.ipynb |
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import sqlite3
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print("imports done")
# -
de... | Practice/Database Management/ip.ipynb |
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# Copyright (c) Facebook, Inc. and its affiliates.... | samples/contrib/pytorch-samples/Pipeline-Cifar10-hpo.ipynb |
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# <img width="10%" alt="Naas" src="https://landen.imgi... | Database/Airtable/Airtable_Get_data.ipynb |
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# # Decision Analysis
# + [markdown] tags=[]
# Think ... | notebooks/chap09.ipynb |
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# # IV.G - Timestamp Estimation
#
# Code for generatin... | paper_evaluation/IV.G_time_estimation/tifs_timeEstimation_singleImage.ipynb |
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# <div style="color:#777777;background-color:#ffffff;f... | community/awards/teach_me_quantum_2018/bronze/bronze/B20_Lists_Matrices.ipynb |
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import numpy
import cv2
im_grey = cv2.imread("smallg... | s07/lecture109.ipynb |
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# %matplotlib notebook... | Model Pruning/logs/.ipynb_checkpoints/ResultPlotScript-checkpoint.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Machine-Learning/cat_dog_classification.ipynb |
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# ! git clone https://github.com/sz128/slot_filling_and... | ATIS.ipynb |
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## Notebook for Creating Generator code for Keras ... | cw_nets/cw_generator/cw_generator.ipynb |
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# <a href="https://colab... | verMay23-2.ipynb |
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# <a href="https://colab... | Apex_Improved.ipynb |
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# <a href="https://colab... | coding_act_3.ipynb |
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def table_to_df():
import boto3
dynamodb = bo... | example/Demo_get_NoSQL_Data.ipynb |
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d... | Notebook/Example.ipynb |
# -*- coding: utf-8 -*-
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# # Unsupervised Learning ... | 1_GaussianMixtureModel.ipynb |
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% matplotlib inline
import numpy as n... | 03.Probability Concepts/Probability Concepts.ipynb |
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# Often, you have data and you need to determine which... | data-analysis/finding-null-values.ipynb |
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import operator
import random
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from ... | weighting/PSO_deap_01.ipynb |
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import zipfile
import tarfile
import ... | notebooks/convert-falling-things.ipynb |
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# # Tuning the parameters of a PID controller
# In th... | introduction/notebooks/Continuous-PID.ipynb |
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# ## Cleaning FERC 1 Fuel data
# This notebook is mean... | results/notebooks/ferc1/ferc1_fuel_cleaning/ferc1_fuel_cleaning_cost_delivered_burned.ipynb |
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from numpy import loadtxt
from numpy import unique... | Data Cleansing Master/Sparse Column Identification and Removal.ipynb |
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# https://data36.com/scatter-plot-pandas-matplotlib/
i... | pandas_tutorial_1.ipynb |
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# # Canvas Drawing Test
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from ipycanvas import Canvas... | docs/jupyter/canvas-test.ipynb |
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# * https://github.com/netty/netty
# * htt... | Reference.ipynb |
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import numpy as np
import torch
import torch.nn as nn
... | experiments/asynch/SiteVisitAsynchronous.ipynb |
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# # Science Case #5: MAPS: an ALMA large program
#
... | notebooks/Case5.ipynb |
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# Built-in libraries
from datetime import datetime... | Preprocessing/.ipynb_checkpoints/load_cuve_generation-checkpoint.ipynb |
# ##### Copyright 2021 Google LLC.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writ... | examples/notebook/contrib/secret_santa.ipynb |
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# ### Question 1
#
import numpy as np
input_mat = np... | Assignments/HW4_Q1.ipynb |
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# # Image processing
#
# ## Load an image to numpy
fr... | exp2021-02/exp2021-02.ipynb |
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# + [markdown] colab_type="text" id="v1CUZ0dkOo_F"
# #... | site/en/tutorials/generative/cyclegan.ipynb |
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# # Python - Sequenze (Stringa, Lista e Tupla)
#
# > #... | laboratorio/lezione2-01ott21/lezione2-python-sequenze.ipynb |
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# # Run this cell but don't modify it.
# # %load_... | Trials/Lane_Lines_Trial_Class.ipynb |
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# # Introduccción
#
# Luego de un primer período con b... | augusto.ipynb |
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# %load_ext autoreload
# %autoreload 2
import sys
... | SSL/simclr/simclr_run-PANDAs.ipynb |
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# [![Github](https://img.shields.io/github/stars/lab-m... | notebooks/evaluate.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | streamlit/findmyfigurineapp.ipynb |
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import os
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
im... | mlmodels/model_dev/nlp_tfflow/neural-machine-translation/48.google-nmt.ipynb |
# # 📝 Exercise M6.01
#
# The aim of this notebook is to investigate if we can tune the hyperparameters
# of a bagging regressor and evaluate the gain obtained.
#
# We will load the California housing dataset and split it into a training and
# a testing set.
# +
from sklearn.datasets import fetch_california_housing
fr... | notebooks/ensemble_ex_01.ipynb |
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# # Bag of Words (Or: *What is unique about working wi... | week_04/Bag of Words.ipynb |
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# ## Containers
# ### Checking for containment.
# Th... | ch00python/025containers.ipynb |
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# # Calculating Charity Scores from relevant charity d... | Score_Calculation.ipynb |
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import numpy as np
import numpy.ma as ma
import os
imp... | pseudocorals/coral_Emile_Geay_all_files_15May.ipynb |
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import keras_ocr
# keras-ocr will automatically d... | OCR.ipynb |
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# # Eodag basics
# ____________
#
# We present `eodag`... | examples/tuto_basics.ipynb |
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# # Programming_Assingment7
# ### 1. Write a Python P... | Programming_Assingment7.ipynb |
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# ## Tutorial 15. Feature engineering with audio files... | notebooks/t15-TCD_feature_engineering_audio_files.ipynb |
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# + deletable=true editable=true
"""Required imports"""
impor... | Good Reads.ipynb |
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# # Set routines
import numpy as np
np.__version__
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# The neuron can be thought of as an electrical circui... | NEU_DYN_COUR/RC-Circuit.ipynb |
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# ## Feature Selection
#
# In the following cells, we ... | Research_environment/ML pipeline research environment/ML_pipeline_research_feature_selection.ipynb |
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'''
Graph and Loss visualization using Tensorboard... | Section 7/Code/tensorboard_MNIST_Section7.ipynb |
# + [markdown] colab_type="text" id="view-in-github"
# [View in Colaboratory](https://colab.research.google.com/github/DillipKS/MLCC_assignments/blob/master/intro_to_sparse_data_and_embeddings.ipynb)
# + [markdown] colab_type="text" id="JndnmDMp66FL"
# #### Copyright 2017 Google LLC.
# + colab={} colab_type="code" id... | intro_to_sparse_data_and_embeddings.ipynb |
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from PIL import Image, ImageDraw
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import psycopg2
import pandas as pd
import numpy as np... | ADS-Fall2019A/Las Vegas Hotel TripAdvisor Reviews/Restaurant Suggestion (2).ipynb |
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import matplotlib.pyplot as plt
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# - This notebook... | notebooks/viz/imshow.ipynb |
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# #README
#
# This is our readme file about Data Curat... | dhcuration.README.ipynb |
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# + [markdown] colab_type="text" id="k0IFBGCx8_im"
# #... | courses/machine_learning/deepdive/10_recommend/cf_softmax_model/solution/cfmodel_softmax_model_solution.ipynb |
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# Map and Lambda Function
cube = lambda x: x*x*x
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#hide
from lagnn.core import *
# # Lagrangian Neural ... | notebooks/index.ipynb |