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# <a href="https://colab... | Lab_Notebooks/S4_3_THOR.ipynb |
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# # 10.3 word2vec的实现
# +
import collections
import ma... | code/chapter10_natural-language-processing/10.3_word2vec-pytorch.ipynb |
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# line 1 note
import csv
import numpy as np
import pa... | proj3_cheese_2.ipynb |
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# # install package
# ! pip install .
import lda_pac... | Example.ipynb |
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import sys
from notebook import Notebook
class Me... | notes/running_menu.ipynb |
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'''
- 進化計算アルゴリズム
- ベイズ最適化
-
'''
import pandas as pd
... | analyze.ipynb |
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# + id="AkEzLyObST_n" colab_type="code" colab={}
import pandas as pd
import n... | day4.ipynb |
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import numpy as np
a = np.array([10, 20, 30])
print(... | notebook/numpy_diag_construct.ipynb |
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# ### Imports
import numpy as np, cv2
from matplotlib... | ShowImage.ipynb |
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import tensorflow as tf
import numpy as np
import matp... | TF1_LinearRegression.ipynb |
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from sklearn import datasets
from sklearn.model_se... | notebook/Keras_Iris.ipynb |
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# # Classification with Naive Bayes and SVM
# ## Naiv... | TA/Session6.ipynb |
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# # G2Product Guide - Version
#
# The `version()` meth... | notebooks/senzing-examples/Windows/senzing-G2Product-version.ipynb |
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# + [markdown] id="-PLC9SvcQgkG"
# # DeepDreaming with TensorFlow
#
# ### ___... | deepdream.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | Assignments-colab/ASSIGNMENT_3b.ipynb |
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import pandas as pd
import seaborn as sns
sns.set(colo... | WeatherDataVisualize.ipynb |
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# <h1 align="center">Introduction to SimpleITKv4 Regis... | Python/60_Registration_Introduction.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Lotofacil.ipynb |
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# I'm giving a ... | notebooks/AB_tests/Plots for AB Conference Talk 2019.ipynb |
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# Organizing Topic Modeling Results
# -
import pa... | Sentiment_Analysis/IF_sentiment_analysis.ipynb |
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# # Music Recommendation System Evaluation (MagnaTagAT... | music _recommendation_magnatagatune.ipynb |
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import mwdsbe
import schuylkill as skool
import pandas... | mwdsbe/Notebooks/By Data/Payments/Payments2.ipynb |
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# [finding-important-factors-to-survive-titanic](#http... | kaggle/EDA-finding-important-factors-features.ipynb |
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# Frozen set is just an immutable version of a
# ... | 10. Python Set/7. Python Frozenset.ipynb |
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# # importing library
import pandas as pd
import matp... | pima-diabetes-dataset-machine-learning-approach.ipynb |
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from __future__ import print_function
import sys
i... | examples/pytorch/ProtoNN/protoNN_example.ipynb |
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# + id="B_OZ25dzc5kT" colab_type="code" colab={"base_uri": "https://localhost... | examples/example.ipynb |
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import pandas as pd
import numpy as np
import matplotl... | California Housing Price Prediction/California Housing Price Prediction.ipynb |
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# ! pip install pyspark
# ! pip install findspark
fro... | Lecture-5B.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | 2020_11_17_MD_MT_Covid_19_data_IJ.ipynb |
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# ## CIFAR 10
###code starts here
import sys
import o... | examples/ipynbexamples/lesson7-cifar10-MAEdits.ipynb |
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from IPython.display import clear_output
import os,cv2... | Eman_NN/M-50-30-Yes.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Untitled4.ipynb |
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import pandas as pd
import numpy as np
import impo... | Code/heart_disease.ipynb |
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# # NYC new measles cases by month (2018 - 2019)
#
# *... | notebooks/nyc-new-measles-cases-by-month-final.ipynb |
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# + _cell_guid="b1076dfc-b9ad-4769-8c92-a6c4dae69d19" ... | xgboost-walkthrough-titanic.ipynb |
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# # Machine Learning: A Quantitative Approach
# %matp... | Vehicles_Cross-Validation.ipynb |
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# # BilayerAnalyzer
#
# The BilayerAnalyzer class is t... | jupyter_notebooks/bilayer_analyzer.ipynb |
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# # Activation Test MEA Standard Protocol (Repeat)
im... | Notebooks/Activation Test MEA Standard Protocol (Repeat).ipynb |
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### Synthetic ones ###
import csv
import pandas a... | Report/Data/Plots/Codes/synthetic_ones_indiv.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | module1-introduction-to-sql/Unit_3_Sprint_2_Homework_1.ipynb |
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# ###### Content under Creative Commons Attribution li... | notebooks_en/4_Life_Expectancy.ipynb |
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# + id="Vw7RpVEfZand"
# IMPORTING NECESSARY LIBRARIES
from IPython.display i... | Machine Learning Models/Number_of_Persons_Detector/Persons_Counter.ipynb |
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# # 6 - Sísmica de reflexão: Correção de Normal Moveou... | notebooks/6-reflexao-nmo-empilhamento.ipynb |
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# # Scroll down to get to the interesting tables...
#... | notebooks/Table_of_widget_keys_and_style_keys.ipynb |
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# # Bias in Data - Quality of Wikipedia Po... | hcds-a2-bias.ipynb |
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# # 1 Creating a DataFrame
#
# First, l... | pyspark-ml-crashcourse/notebooks/01 - PySpark DataFrame Introduction Full.ipynb |
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# # PySchools w... | pyschools/analysis2.ipynb |
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import pandas as pd
import numpy as np
from scipy ... | BiomarkerCorrelation.ipynb |
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# + [markdown] deletable=true editable=true
# # Ch `05... | ch05_clustering/Concept02_segmentation.ipynb |
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# %matplotlib inline
import numpy as np
from sklea... | experiments/nlp/.ipynb_checkpoints/results-checkpoint.ipynb |
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# # PCM for tuning regularization parameters i... | docs/demos/demo_regression.ipynb |
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# # MAT281 - Laboratorios N°07
# <a id='p1'></a>
# ##... | labs/lab_07_alvaro.ipynb |
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# # Titanic: Machine Learning from Disaster | Kaggle
... | notebooks/01-dan-titanic-notebook.ipynb |
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# %load_ext autoreload
# %autoreload 2
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-- # Towards In... | example/Haskell/cities-wordcloud/cities-wordcloud.ipynb |
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# # Foundations Of AIML
# ## Session 11
# ### Experime... | Session11/Lab11-Experiment1_3.ipynb |
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import cupy as cp
import cusignal
from scipy import s... | notebooks/api_guide/wavelets_examples.ipynb |
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# # Evaluate Linear Models
#
# Evaluate Linear Models
... | results/19-04-30-PredictiveModelDecayAllSpecies/19-05-01-TrainModels/01-LinearModels.ipynb |
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# # Set up
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# %matplotlib inline
# %run fcast.py
... | notebook/2_ets.ipynb |
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# # THE SPARKS FOUNDATION
# ### GRIP - DATA SCIENCE A... | Task - 1.ipynb |
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# # Exercise 4 : Regression Analysis using Text Data
... | Lesson03/Exercise32.ipynb |
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# # Regressione usando la teoria Bayesiana
#
# La regr... | 3.machine learning/.ipynb_checkpoints/4-Bayesian_Logistic_Polynomial-checkpoint.ipynb |
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# %matplotlib inline
import matplotlib.pyplot as plt, ... | notebooks/07_GLUE.ipynb |
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import pandas as pd
import numpy as np
import os
raw_... | notebooks/Exploring-Processing-data.ipynb |
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# # Golf Ball (One Way Anova)
# # Importing the Libra... | M3 Advance Statistics/W1 ANOVA/GolfBall_OneWayAnova_Solutions.ipynb |
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import random
random.seed(1)
restaurant_list = list(s... | index.ipynb |
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# <table style="font-size: 1em; padding: 0; margin: 0;... | dl-satellite-image/p1_intro/project_data/Part_1_GettingStarted.ipynb |
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# ### TASK
# A Bayesian network (also known as a Baye... | Bayesian Network Implementation for Heart Prediction.ipynb |
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class Solution:
def lengthOfLastWord(self, s: str) -> int:
... | algorithms/58-length-of-last-word.ipynb |
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# + [markdown] deletable=false id="11lq_Y7ygqZo" nbgra... | .ipynb_checkpoints/PCA from scratch-checkpoint.ipynb |
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import pandas as pd
import urllib.parse
import req... | CollectData.ipynb |
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import keras
keras.__version__
# # Using word embeddi... | first_edition/6.1-using-word-embeddings.ipynb |
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# # <center>Plot the figures in paper</center>
#
# ###... | demo/figs_in_paper.ipynb |
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# !pip install shap adjustText xgboost
# +... | data_processing/.ipynb_checkpoints/full_model-checkpoint.ipynb |
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# + colab={} colab_type="code" id="7fPc-KWUi2Xd"
# Cop... | notebooks/samples/optimizer/ai_platform_optimizer_multi_objective.ipynb |
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# # Exploratory data analysis
# # Purpose
# Explore t... | notebooks/02.1_EDA.ipynb |
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import matplotlib.pyplot as plt
import numpy as np
plt... | plot/ODEphase.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="DExKBrWjbLLx" execution... | Code/HRV Classification/SVM.ipynb |
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# # MPS using the deesse wrapper - using a mask
# ## ... | examples/ex_deesse_11_using_mask.ipynb |
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# # Creating our Database
#
# This notebook walks thro... | assets/EMSE6586/MySQL Table Creation.ipynb |
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# + deletable=true editable=true
from bqplot import Pi... | examples/Marks/Object Model/Pie.ipynb |
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# # [PUBLI... | script/explore-clblast-matrix-size/clblast-distribution-tuner-sizes-analysis.ipynb |
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# # Find population of a US CITY based on
#
# ... | Keras-train-MAPE-kfold.ipynb |
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# name: python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east... | hcls/language/medical-transcripts-classification/explore-data.ipynb |
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# # Module 5: Regime Prediction with Machine Learning ... | Investment Management/Course3/Part 3 - Forecasting Regimes_version_July_2020.ipynb |
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from urllib.request import ssl, socket
import datetime... | PythonScripts/TLS Validator.ipynb |
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# # tsam - Animation of pareto-optimal aggregation
# D... | examples/aggregation_segment_period_animation.ipynb |
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# + [markdown] colab_type="text" id="view-in-github"
#... | solutions_do_not_open/Introduction_to_Deep_Learning_with_Keras_solution.ipynb |
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# #... | Ch3/02_Bag_of_Words.ipynb |
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import sys
sys.path.append("../../")
import csv
import... | tests/postresaxis/validate_rotating_ellipse/increased_resolution.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="... | GPU/U-net-2D-EM-segmentation/.ipynb_checkpoints/main-Copy1-checkpoint.ipynb |
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# + _cell_guid="624e2285-cba3-4d1c-ab2e-fcb4751e6985" ... | Mental_Wellness_Data_Exploration.ipynb |
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# # Eclipsing binary: Linear solution for the maps
# ... | notebooks/EclipsingBinary_Linear.ipynb |
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# +
#Scrape the NASA Mars News Site and collect the la... | scrape_mars.py.ipynb |
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# +
"""
<NAME>
CSCI 4350/5350
Dr. <NAME>
Honors Contra... | Hybrid-Clustering.ipynb |
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# + [markdown] id="9g1TMjhX7FbJ"
# ## Model Evaluations
# Purpose of this not... | final_model_evaluation.ipynb |
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import torch
import torchvision
import torchvision.tra... | archive/scratch_pad/pytorch_3_cifar.ipynb |
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# # One-dimensional advection equation
# v1.64... | Fiedler_revised/n050_advectionpde1d.ipynb |