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from math import pi, pow
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# # Global Imports
# %matplotlib inline
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# In this notebook , we will train a neural network mo... | notebooks/contrastive_embeddings.ipynb |
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# # DAT210x - Programming with Python for DS
# ## Mod... | Module4/Module4 - Lab2.ipynb |
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import linora as la
corpus = [
'This is the first... | example/la.text.ipynb |
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# # Machine Learning Re... | machine_learning/Machine Learning Notebook.ipynb |
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import configparser
# v1 OANDA API
# pip install g... | oandamomentumv1.ipynb |
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# name: python3-azur... | 07 - Text Analytics.ipynb |
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# %pylab inline
import seaborn as sbn
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import pandas as pd
import matplotlib.pyplot as plt
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import numpy as np
import matplotli... | notebooks/firing_squad_deterministic_petri_base.ipynb |
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import pandas as pd
from sklearn.linear_model import L... | CODE.ipynb |
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# + [markdown] colab_type="text" id="s6wRWQbM8YWK"
# #... | Python-101/10-dictionary.ipynb |
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# + [markdown] id="VLUqsUmXvf2_" colab_type="text"
# # Compiling GRF from scr... | gfootball/colabs/gfootball_example_from_scratch.ipynb |
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import copy
from keras.models import clone_model
from ... | proof_of_work/deep_q/v0/experiments/midtraining_policy.ipynb |
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# # Double-feature Models
# +
import datetime
from pa... | webapp/results_survey_molecular_similarity/.ipynb_checkpoints/create_double_feature_models_3Classes_01-checkpoint.ipynb |
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# + [markdown] origin_pos=0
# # 自然语言推断与数据集
# :label:`sec_natural-language-inference-and-dataset`
#
# 在 :numref:`sec_sentiment`中，我们讨论了情感分析问题。这个... | submodules/resource/d2l-zh/mxnet/chapter_natural-language-processing-applications/natural-language-inference-and-dataset.ipynb |
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# Write a Python program to find urls in a string.... | regex/find_url_solution.ipynb |
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# In the first chart of the first example, you can see... | src/notebooks/94-use-normalization-on-seaborn-heatmap.ipynb |
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# + [markdown] tags=[]
# # MATH665
#
# _<N... | assignments/MATH665 Final Project.ipynb |
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# ## Compare oil type volumes by vessel
# +
import p... | notebooks/monte_carlo_dev/CompareOilTypeVolumeByVessel.ipynb |
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# Imports
import os
import matplotlib.pyplot as plt
fr... | 4_Fruit_classification/.ipynb_checkpoints/Nhap_fruit_class-checkpoint.ipynb |
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# + [markdown] colab_type="text" id="UEDYQfp6SkIf"
# # Lab 4. Text Classifica... | labs/lab4/Lab4_TextClassificationCNN.ipynb |
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import numpy as np
import pandas as pd
import matplotl... | Multiple Linear Regression.ipynb |
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# ### ESMA 3016
# ### <NAME>
# ### Lab22: Uso del modu... | Notebooks/Lab22v3.ipynb |
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# %load_ext autoreload
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# # Problem definition
#
# Create some data, in th... | docs/Usage.ipynb |
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# %% [markdown]
# # ... | 002-Methods/004-Dashboards/001-Dash/002-Examples/001-Covid19dynstat/covid19dynstat-dash.ipynb |
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# + [markdown] pycharm={"name": "#%% md\n"}
# # Dynami... | tutorial/03 - Trajectory Optimization and Optimal Control/03 - The AeroSandbox Dynamics Stack/04 - 2D Aircraft Dynamics for Mission Performance Analysis.ipynb |
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# Imports
import cv2 as cv
import matplotl... | exercises/lecture_01.ipynb |
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# # Benchmarking
# ## 0. Setup the loggin... | tutorials/03_Benchmarking.ipynb |
from pyspark.sql import SparkSession
spark=SparkSession.builder.appName('mach2.0').getOrCreate()
from pyspark.ml.regression import LinearRegression
df=sqlContext.sql("SELECT * FROM ship")
df.head(1)
from pyspark.ml.linalg import Vectors
from pyspark.ml.feature import VectorAssembler
df.columns
df.printSchema()
fro... | Machine project.ipynb |
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import requests
from urllib.request i... | Final Capstone/Beautiful Soup for CV.ipynb |
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import pandas as pd
import numpy as np
import matplotl... | M4 Data Mining/W4 Artificial Nural Network/Neural Networks - Video Code.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | 11Enero.ipynb |
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# # Build a Customer Churn Model for Music Streaming A... | use-cases/customer_churn/0_cust_churn_overview_dw.ipynb |
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# # 7.11 Flat heating Coils - Water
# Water at 80 deg... | docs/Examples/Crane TP 410 Solved Problems/7.11 Flat heating Coils - Water.ipynb |
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# Importing the libraries
import numpy as np
i... | Apriori - Market Basket.ipynb |
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# # Visualisation des données fournies avec OPEN
impo... | Data/OPEN_provided_data_viz.ipynb |
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# + [markdown] deletable=true editable=true... | explore_ht-vs-wt_sport.ipynb |
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# %config Completer.use_jedi = False #for intellis... | FOMC.ipynb |
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# #### 1. What is TensorFlow? (choose all that apply)
... | Coursera/Intro to TensorFlow/Week-1/Quiz/Core-TensorFlow.ipynb |
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# # Freq_meth_calculate usage
# Calculat... | docs/demo/Freq_meth_calculate_usage.ipynb |
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import pandas as pd
import tweepy
import csv
impor... | Prediction/NB_PRED.ipynb |
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# 我们今天要解决的问题是**自然语言处理中的序列标注问题**, 在目前, 比较主流的技术是**语言模型(如... | 05_NER_hidden_markov_model/.ipynb_checkpoints/HMM_NER-checkpoint.ipynb |
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# # Strings
#
# ## We can do things with strin... | 03-Close-Reading-I/01-Strings.ipynb |
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# # Creating a Unit
# A Unit object is created with a... | docs/tutorial/Creating_a_Unit.ipynb |
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# # Tips and tricks:
#
# 1. [Comprehensions (list/dict... | notebooks/03_02_TipsAndTricks.ipynb |
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# # Squeezing in atomic qudits
# In this ... | examples_before_PR_accept_by_RPB/Fisher_information.ipynb |
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# ## 2020년 8월 4일 화요일
# ### leetCode - Word Pattern (Py... | DAY 101 ~ 200/DAY180_[leetCode] Word Pattern (Python).ipynb |
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# +... | _notebooks/2020-03-14-covid19_growth.ipynb |
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import numpy as np
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# # Optimizing two mo... | nbs/demo_2models.ipynb |
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# ## Model Perfromance Metrics
#
# Note: Notebook has ... | modeling/model_metrics.ipynb |
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import numpy as np
import matplotl... | Yandex data science/1/Week 4/Untitled.ipynb |
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# # Keyboard Input: Converting Fahrenheit temperatures... | draftfolder/Module2Assignment-Gordon.ipynb |
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# # Student Alcohol Consumption
# ### Introdu... | 04_Apply/Students_Alcohol_Consumption/Exercises.ipynb |
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# best&less account stuff
#
# Python command line scri... | posts/bestandless.ipynb |
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# Name: <NAME>, <NAME>
#
# Student ID: 22... | cplane_np.ipynb |
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# <a href="https://colab... | HW9.ipynb |
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App_data = pd.... | Untitled1.ipynb |
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imp... | app/.ipynb_checkpoints/Untitled-checkpoint.ipynb |
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# # APPLE APP STORE - Transforming Raw to Clean Data
#... | .ipynb_checkpoints/Final_Apple_Code-checkpoint.ipynb |
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# + hide_input=true
import numpy as np
import matplotl... | src/Chapitre3/figure/dphinorm.ipynb |
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#install.packages("readr")
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#install.packag... | R/nyc_crime.ipynb |
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from sklearn.preprocessing import Stan... | tabular-playground-series-feb-2022/test.ipynb |
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# ## Analyze A/B Test Results
#
# ## Table of Contents... | Analyse_AB_Test_Results/Analyze_ab_test_results_notebook.ipynb |
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# + [markdown] tags=["papermill-error-cell... | reports/c9.0-fsp-deploy-cloud-2022-01-03T03:06:18.ipynb |
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import numpy as np
import cv2
import matplotlib.py... | Notebooks/Watermark on Image or Video/Watermark on Image or Video.ipynb |
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# + [markdown] colab_type="text" id="YJYDHq1TAOdQ"
# ... | Lab4/hw/hw-047Clustering_Exercises.ipynb |
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# ## Plant Seedlings Competition
# https://www.kaggle... | plant-seedlings.ipynb |
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# ### 1 - Greg was 14, Marcia was 12,... | Exercises/Basic_Stats_and_Probability/1 - Summary Statistics.ipynb |
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#
# ## How to use Error Generator ?
#
#
# ### Clone t... | Help.ipynb |
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# # バイナリデータの読み込み
import struct
import numpy as np
imp... | _programs/python/logistic/read_binary.ipynb |
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# Hypothesis Testing
# ==================
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# + [markdown] id="J_o2L3Io9t4c"
# #Deep Computer Vision
#
# In this guide we... | AI-ML/Tensorflow fcc/Instructor notebooks/Computer Vision.ipynb |
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# # ExternalSource operator
#
# In this example, we wi... | docs/examples/frameworks/paddle/paddle-external_input.ipynb |
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# # Self-Driving Car Engineer Nanodegree
#
# ## Deep L... | Traffic_Sign_Classifier.ipynb |
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# ## Introduction to the Interstellar Medium
# ### <NA... | extragalactic/R136.ipynb |
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# + id="TcQnpE9WWLpP" colab_type="code" colab={}
import pandas as pd
import m... | Matrix_3_road_sign/M3_day2.ipynb |
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import warnings
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import pandas as pd... | back/api/distribuicao.ipynb |
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# + [markdown] id="U7sjmwi3rlk0"
# # Scatter Plots
# ... | matplotlib/scatter/scatter.ipynb |
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... | Regression Problem.ipynb |
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# + [markdown] id="-GesvmV0L6jX"
# # Python List
#
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#
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# + id="E6DddC8... | Coding_Hour2.ipynb |
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# # Robust Kalman Filtering for Path Retrieval
#
# ###... | Robust Kalman Filtering for Path Retrieval.ipynb |
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import json
# +
"""
get_category_... | Data_Extraction_From_Wikipedia.ipynb |
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import numpy as np
im... | Tests/pyroomtest1fin.ipynb |
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# <a href="https://colab.research.google.co... | assignments/assignment_yourname_class10.ipynb |
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# + id="JKI-xvgOd_7P" outputId="d8b01659-a40f-4955-a3f... | additional_features/baseline/BKT-experiment.ipynb |
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# + [markdown] school_cell_uuid="84865712f2da41a9a6cf4... | 13. Scikit-Learn, Statsmodel/01. Scikit-Learn 패키지의 소개.ipynb |
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# # Overview
#
# This notebook introduces the ... | examples/overviews/Overview.ipynb |
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from ..Template import Template
from ..Library.Dai... | TradingSystem/Algorithm/Demo/.ipynb_checkpoints/Demo-checkpoint.ipynb |
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# ## Taxi Cab Classification (prior to TF2)
# This no... | 03-pipelines/kale/taxi-cab-classification_[TF]/taxicab_pipeline.ipynb |