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import pandas as pd
import matplotlib.pypl... | Energy signature/energy_signature.ipynb |
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import ipydagred3
# Instantiate new graph
g = ipydagr... | docs/examples/example.ipynb |
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# + [markdown] id="H7LoMj4GA4n_" colab_type="text"
# # GPT-2 finetuned on Sha... | Next_Word_Prediction_GPT2_FineTuned.ipynb |
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import pandas as pd
planes_df = pd.read_csv('../data/p... | notebooks/JZ_05_select_filter.ipynb |
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# In this pactice we will be introducing the different... | .ipynb_checkpoints/HomologyModelling-checkpoint.ipynb |
# -*- coding: utf-8 -*-
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# # 解析学A 2018
#
# 黒木玄
#
# ... | .ipynb_checkpoints/Analysis A 2018-checkpoint.ipynb |
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# # Python Classes Quick Reference
#
# ## Table Of Con... | Python Quick Reference/Classes.ipynb |
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import numpy as np
class linear_xor(object):
... | hinton/lineardeltaxor.ipynb |
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# # Creation of synthetic data for stroke thrombolysis... | 02_stroke_pathway/02_SMOTE_log_regression.ipynb |
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# These lessons are adapted from [aymericdamien Tensor... | Deep_Learning/TensorFlow-aymericdamien/notebooks/1_Introduction/helloworld.ipynb |
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# A notebook to process experimental results of ex1_va... | ipynb/ex1_results.ipynb |
# -*- coding: utf-8 -*-
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# + [markdown] tags=[]
# #... | notebooks/Simple Chain.ipynb |
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# + [markdown] nbsphinx="hidden"
# # The $z$-Transform... | z_transform/table_theorems_transforms.ipynb |
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# + [markdown] id="YgOf7-J1EjBh" colab_type="text"
# https://colab.research.g... | Chapter03/Audio_classification.ipynb |
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# # Listing a recipe in a notebook
#
# The goal o... | find and list recipes in notebook.ipynb |
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# All imports and setups
# %run ../../../common_... | machine-learning-concepts-and-procedures/learning-algorithms/notebooks/gradient-descent.ipynb |
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import matplotlib as mpl
import matplotlib... | matplotlib/Untitled.ipynb |
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# <div style="text-align: right; font-style: italic"> ... | electrical power output prediction in a CCPP.ipynb |
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# # Grid Search for Binary Classification
#
# This not... | notebooks/Grid Search for Binary Classification.ipynb |
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import math, numpy as np
from sklearn import prepr... | Stock Prediction SkLearn.ipynb |
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# # 5. Derivatives
# In this section we will give some... | Course Notebooks/Lecture 5 - Derivatives.ipynb |
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# # Tutorial: Private Deep Learning
#
# Welcome to PyS... | examples/tutorials/Part 1 - The Basic Tools of Private Data Science.ipynb |
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# # Introduction to Linear Regression
#
# *Adapted fro... | 08_linear_regression.ipynb |
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# # FFT Phase Correlation
# > How to use FFT Phase Cor... | _notebooks/2020-12-19-FFT-Phase-Correlation.ipynb |
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# ## Final Distribution
# + pycharm={"name": "#%%\n"}... | final_distribution.ipynb |
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# %load_ext autoreload
# %autoreload 2
import os
i... | experiments/notebooks/05_simulation.ipynb |
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# # Classify SEC 10K/Q Filings to Industry ... | sagemaker-jumpstart/multicategory_sec/SEC_MNIST_ML.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # I... | docs/notebooks/StackInspector.ipynb |
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import numpy as np
import pandas as pd
import json
fro... | work/3 - ScoreAll.ipynb |
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# # Theano version of positive/negative samples
# +
i... | attalos/imgtxt_algorithms/sampledSM/theano/traintheano.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | OOP_Concepts_2.ipynb |
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import microdrop_sync.microdrop_sync as ms... | Electrodes.ipynb |
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# %matplotlib inline
import matplotlib.pyplot as plt
i... | notebooks/05.Supervised_Learning-Classification.ipynb |
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# # Interpretable drift detection with the... | doc/source/examples/cd_spot_the_diff_mnist_wine.ipynb |
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# + [markdown] papermill={"duration": 0.020563, "end_t... | Current_public_solutions/sartorius-starter-torch-mask-r-cnn-lb-0-173.ipynb |
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# ## 1. Introduction
# This workbook wil... | 00-surface-viz.ipynb |
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# # Exercise 02
#
# The goal of this exercise is to ev... | rendered_notebooks/03_basic_preprocessing_categorical_variables_exercise_01.ipynb |
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import numpy as np
import pandas as pd
from pandas... | BoW/Old methods - Feature Extraction/Archive/kmer count to DataFrame.ipynb |
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'''
This notebook filters mapped nanoCOP data to remov... | data_filtering/filter_data_nanoCOP.ipynb |
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# + id="3MjeM-gGCc4N" colab_type="code" colab={}
import pandas as pd
import ... | jupyters/co_experiment.ipynb |
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# # Lecture 7. Parametric vs. Nonparametric mo... | Lecture_7/Lecture_7_1.ipynb |
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import pandas as pd
from... | assignments/HW2.2.2.2-shahzaib.ipynb |
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# Copyright (c) Microsoft Corporation. All rights r... | how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-parameter-tuning-with-hyperdrive.ipynb |
# -*- coding: utf-8 -*-
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# # Schelling’s Segregatio... | 00-linear-model.ipynb |
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# # Node2Vec representation learning with Stellargraph... | demos/embeddings/keras-node2vec-embeddings.ipynb |
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# # COVID-19 Data in Aruba
# ## Background... | final_project.2.ipynb |
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# + [markdown] id="_SQuhKClaHez"
# #Run this piece of ... | Helmet_detection.ipynb |
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# ## Ejemplo de como correr interactivamente la librer... | ElCuadernillo/20160214_TensorFlowTutorialBasico/TensorFlow_Interactivo_IPython.ipynb |
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import pandas as pd
import plotly.graph_ob... | WebDashboard/dataprocessing.ipynb |
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import gmpy2
import mat... | Shor.ipynb |
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# ### Feature Engineering - Geo Clustering
#
# We want... | Feature Engineering/Clustering/Binary_Clustering.ipynb |
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import wandb
wandb.init(project='Vae-test')
import ma... | notebooks/wandb/run-20200201_144258-a9vectsn/code/notebooks/7.2-EXE-variational-autoencoder.ipynb |
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# Code source: <NAME> and <NAME>, based on <NAME> ... | iml2020/examples/Bias, Variance, and Noise Trade-off.ipynb |
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from pycalphad import Model, Database
from pycalph... | UfuncifyTest.ipynb |
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from Cr... | notebooks/API Tryout.ipynb |
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# + id="YYZbQz28Ti1w"
import pandas as pd
# + [markdown] id="koqLx0qff2MN"
#... | Merge_Join,_Concat.ipynb |
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# # Self-tuning random forests
#
# A demonstratio... | examples/random_forest/random_forest.ipynb |
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using Convex
using LPLib
solver = LPSolver()
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abc = {"A":1,"B":2,"C":3}
try:
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except (Lo... | People/Juan/Week 2/Notes testing.ipynb |
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import os
hello_world_script_fl = os.path.join(os.pard... | notebooks/Machine_Learning_API.ipynb |
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## Using 6m Smoked Mice Fibroblasts object to demo... | notebooks/marker_correlation_score.ipynb |
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import numpy as np
import sys
from os.path import expa... | ManipulatingDataCubes.ipynb |
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# # Text drift detectio... | examples/cd_text_imdb.ipynb |
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import pandas as pd
import numpy as np
vixy_df = ... | Untitled2.ipynb |
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# <b> Sabendo disso, determine se possível x e y de fo... | Lista 02/04.ipynb |
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import os
import sys
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# + ExecutionTime={"end_time": "2022-02-11... | index_error.ipynb |
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import numpy as np
np.random.seed(2066)
i... | github/preprocess.ipynb |
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# ## Load normalized data
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import pandas as pd
imp... | Source/age_prediction.ipynb |
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# Data persistence with json
import json
# Creati... | Section 1/#1.3 Parse with json and pickling.ipynb |
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# + [markdown] colab_type="text" id="kPFD7mlSFqlG"
# #... | notebooks/.ipynb_checkpoints/Visualisation2D-checkpoint.ipynb |
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name = 'Python'
print(name)
num = 10
num = num + 10
p... | sample/Python_GOKUI/Python_GOKUI/chap02/sec01/AssignmentOperator.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Day6_question2.ipynb |
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# ## first model
#
# Data can be loaded downloaded [here](https://drive.google.com/drive/folders/1yZI5v3ws3b8GZMl_ACe4TO_qebdS2fUz?usp=sharing... | reports/srp/notebooks/5-first_model.ipynb |
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# # Crash Carts Lab
# ## PH 211 COCC
# ### <NAME> 24/1... | Crash Car/.ipynb_checkpoints/CrashCartsLab21-checkpoint.ipynb |
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# # Example use of Aroma Classification
# +
# %matplo... | ipynb/ExampleAromaAnalysis.ipynb |
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# <a href="https://colab.research.google.com/github/khamies//LSTM-Sequence-VA... | play_with_model.ipynb |
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impo... | CNN/VGGNET16.ipynb |
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import configparser
cp = configparser.ConfigParser(al... | src/seq2seq/ConfigParser.ipynb |
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import numpy as np
import scipy
from scipy import stat... | Hue/Distance BS Parent-Child.ipynb |
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import torch
import torch.nn as nn
import torch.nn.fun... | posy_apollo.ipynb |
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# %reload_ext autoreload
# %autoreload 2
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from nipype.interfaces import freesurfer
from nipype.interf... | notebooks/FMRI_invwarp.ipynb |
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# # COVID-19 in high minority populated counties acros... | projectv1.ipynb |
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# ## Visualize dataset using categorical embedding
# ... | .ipynb_checkpoints/interactive_dashboard-checkpoint.ipynb |
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# # Self-Supervision Examples (Language)
# ## Imports... | language/examples.ipynb |
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# # 中文三元组联合抽取
#
# ## 介绍
#
# 在这个notebook中我们将使用o... | ske.ipynb |
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# # Initial Exploration and Organization of Data
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import requests
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# _You are currently looking at **version 1.1*... | Course 1 Introduction to Data Science in Python/Week 4 Assignment/Assignment 4.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
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# # Lab 6: Random processes and variations on a random... | ECE314/lab6/Lab 6.ipynb |
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# # %load stateflowers.py
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# + [markdown] id="ZkvJS-IZRM8l" colab_type="text"
# ##Content Based Filterin... | Content_based_filtering_debashishmalakar.ipynb |
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# ## Step1 Importing all the required lib
import pan... | IncomeGroupClassification(KNN)/Income group classification.ipynb |
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# # 파이썬 예제12) 짝지어 제거하기
# > [Programmers >... | _notebooks/2021-10-28-ENG-python12.ipynb |
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# Import packages
from IPython.display import Image, ... | notebooks/mmpose.ipynb |
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# ### Important Note:
#
# For your convenience, we hav... | Chapter09/create-onnx.ipynb |
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# # CALL OF DATA: the day after
#
# Understanding how ... | Oxfam_Intermon.ipynb |