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# # Homework: Data visualization and explo... | 01_pandas/02-data_exploration_visualization.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="EffQTx-23t36" execution... | Untitled0.ipynb |
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# # Evaluate all embeddings generated with parameter_s... | notebooks/.ipynb_checkpoints/old_Evaluate_UMAP_parameter_search-checkpoint.ipynb |
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import matplotlib.image as mpimg
import matplotlib... | UKF_Visualizer.ipynb |
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# + raw_mimetype="text/restructuredtext" active=""
# .... | doc/source/visualization/scatter.ipynb |
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# # Now You Code 2: Multiply By
#
# Write a program to... | content/lessons/05/Now-You-Code/NYC2-Multiply-By.ipynb |
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from astropy.io import ascii
d = ascii.read('d... | notebooks/ProfEvalsIR.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | 3D_Photo_Inpainting_args.ipynb |
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# [UMAP](https://umap-learn.readthedocs.io/en/latest/)... | community_tutorials_and_guides/umap_demo_full.ipynb |
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# <h2 align="center"> Multivariable Regression </h2>
... | Multivariable Regression/Multivariable Regression.ipynb |
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l=1.0
n=100
h=l/(n-1)
τ... | simplify.ipynb |
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# + id="F1DhLvlWdmC9" colab_type="code" outputId="ed62c0f6-537c-48c5-b031-ff9... | day5.ipynb |
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# %run ../Python_files/util_data_storage_a... | 01_INRIX_data_preprocessing_journal18/INRIX_data_preprocessing_09_ref_speed_adjust_to_free_speed_journal.ipynb |
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# # Korteweg–De Vries equation
#
# * Physi... | demos/constant_vs_adaptive.ipynb |
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from bp.section1_video5_data import get_data
from sk... | Section 5/source/s5_v3_classification_using_xgboost.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # M... | Machine Learning Practical Application.ipynb |
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import numpy as np
import torch
use_c... | image_augmentation.ipynb |
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# # RCS Tuples
#
# ## Tuples
#
# * ordered
# * immut... | core/Python Tuples.ipynb |
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# + [markdown] latex_metadata={"author": "<NAME>", "ti... | examples/lion_lizard_toucan.ipynb |
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# # Support Vector Machines (SVM)
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# As we read e... | Notebooks/easy_track/algorithms/SVM.ipynb |
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# # Assignment 2: Parts-of-Speech Tagging (POS)
#
# We... | week 2/.ipynb_checkpoints/utf-8''C2_W2_Assignment-Copy1-checkpoint.ipynb |
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# # Project 1: Driving Licenses, Traffic Accidents and... | code/personal_practice_space/starter-code-practice_Copy1-Copy1-scaterplot .ipynb |
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# # Exporting data to NetCDF files <img align="right" ... | Frequently_used_code/Exporting_NetCDFs.ipynb |
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"""
WARNING: This tutorial and MegatronBER... | tutorials/nlp/Token_Classification-BioMegatron.ipynb |
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import numpy as np
from sklearn.datasets import make_b... | Logistic_Regression/Logistic_Regression - Vectorization.ipynb |
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# %matplotlib notebook
#dependencies
import matplotli... | Pymaceuticals/matplotlib hm .ipynb |
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# # NIR photography for snowpit (Finse)
#
# Assess usab... | SSA_retrieval.ipynb |
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# +
# 워드 파일에 뉴스 내용을 복사
# 파일을 html.htm 으로 저장
# safelink... | ebadak_news.ipynb |
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# # Normalização com percentil
#
# ## Definição da fun... | deliver/Normalizacao_com_percentil.ipynb |
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# ![Callysto.ca Banner](https://github.com/callysto/cu... | _build/jupyter_execute/curriculum-notebooks/Mathematics/OrderOfOperations/order-of-operations.ipynb |
# -*- coding: utf-8 -*-
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# # IMEC2201 Herramientas ... | content/week2/C4_ajustedatos.ipynb |
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import itertools
import logging
import numpy as n... | examples/src/dbnd_examples/pipelines/wine_quality/predict_wine_quality_tutorial.ipynb |
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# # Widgets
# + hide_input=true
from fastai import *
... | docs_src/widgets.ipynb |
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import pandas as pd
# # !pip install gensim
import... | exploration/word2vec_analysis_claudia.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | OnedriveAssignment.ipynb |
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import os, sys
# import mcvine modules
from instrument.ge... | notebooks/collimator_geometry_creation.ipynb |
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print('Simple neural network sprint 1')
fr... | Nueral_network.ipynb |
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# + deletable=false run_control={"frozen": true} dc={"... | DataCamp/Do Left-handed People Really Die Young?/notebook.ipynb |
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import torch
import random
import numpy as np
ran... | notebooks/pytorch_trainin_wine.ipynb |
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import matplotlib.pyplot as plt
import numpy as np
#... | record/car-following/.ipynb_checkpoints/car-following-visualization-checkpoint.ipynb |
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# Write a program that uses the input function to ask ... | 1.2_codeHS.ipynb |
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# # RF model with max_depth=12 (limited, unlike before... | analyses/time_lags_explain_pdp_ale_lower_max_depth.ipynb |
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# <table style="float:left; border:none">
# <tr sty... | bokeh/tutorial/11 - Running Bokeh Applictions.ipynb |
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# +
# Imports
import numpy as np
import pandas as pd
# +
# Reading in csv f... | notebooks/gas_data.ipynb |
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# + [markdown] nbgrader={"grade": false, "grade_id": "... | master/01-lecture.ipynb |
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# # Understanding Fishing Vessel's Authorization and P... | eda/eda_mmsi.ipynb |
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import requests
import json
import pandas as pd
# +
#... | .ipynb_checkpoints/airbnb_sample_test-checkpoint.ipynb |
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# # Constraint Sati... | 04-csp_lsg.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Notebooks/algorithms/IsolationForest.ipynb |
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import pandas as pd
import numpy as np
from tenso... | test2.ipynb |
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# # Вероятность в Python
# > Вероятность — степень (о... | ds/probability.ipynb |
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import os
import pandas as pd
import numpy as np
i... | performance_test_standard_kernel_cooling_rpi_4B.ipynb |
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# # Pricing a life insurance product
# Statistics Prob... | interviewq_exercises/q125_stats_insurance_policy_price_expectation.ipynb |
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# # Testing with apply, foreach and for loops in R
#
# Similar to progra... | loops.ipynb |
# ##### Copyright 2020 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/send_more_money_any_base.ipynb |
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# # GPU Simulator
#
# ## GPU Qiskit Aer Simulator Bac... | tutorials/simulators/8_gpu_simulator.ipynb |
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// # Introduction to XGBoost Spa... | examples/notebooks/scala/mortgage-gpu.ipynb |
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# # Writing Functions
#
# If you're running the exact ... | python prep/3. Writing Functions - Complete.ipynb |
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# ## 0. Utility
import random
from timeit import defa... | divide-and-conquer/sort.ipynb |
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import matplotlib.pyplot as plt
import pandas as pd
im... | Health Insurance Coverage by State.ipynb |
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# ## Explore the titanic training set
# +
import pand... | exploration.ipynb |
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# # Load Data
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import sys
import os
import numpy a... | notebooks/Load Data.ipynb |
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import numpy as np
import pandas as pd
# Calculate s... | DeepLearning - Udacity/code/Backpropagation/.ipynb_checkpoints/BP For NN-checkpoint.ipynb |
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import numpy as np
def test_exercise_27_2(x) -> b... | Chapter03/unit_tests/.ipynb_checkpoints/Exercise 27-checkpoint.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | C620.ipynb |
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envname = 'variables/loop_stim10e-16.0et6.0phvaryp1.0t... | jupyter_notebooks/plotallnotebook_phi-Copy1.ipynb |
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from flask import Flask, jsonify
from flask_sqlalchemy... | resources/line/flask-sqlalchemy.ipynb |
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# + _cell_guid="b1076dfc-b9ad-4769-8c92-a6c4dae69d19" ... | Titanic/titanic-survival-prediction.ipynb |
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# # Conical Spirals - Arc Length
#
# In th... | notebooks/1 - spiral arc length.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | notebooks/Time_Series_EDA.ipynb |
# +
# Copyright 2010-2018 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 wri... | examples/notebook/examples/sudoku_sat.ipynb |
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# <font size="+5">#03 | Transforming Basic... | 03_Transforming Basic Objects into the Powerful DataFrame/03session_transforming-to-powerful-dataframe.ipynb |
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# + id="DomJn9DynNif" colab_type="code" colab={"base_uri": "https://localhost... | proposed_method.ipynb |
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# # Ludwig Time Series Forecasting
#
# https://github.... | Ludwig/hourly-weather-wind_speed-reduced.ipynb |
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# # Hands-on!
#
# Nessa prá... | 2019/12-spark/13-spark-mllib/Hands-on.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="up3a84fcx1QX" outputId="29b5ce1e-4ef... | R/Day10/day10ofmathandstats_R.ipynb |
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import matplotlib.pyplot as plt
import numpy as np
imp... | Code/1_PK/2_intracellular/estimate_vmax.ipynb |
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import numpy as np
import pandas as pd
from pandas imp... | dataframe (1).ipynb |
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# # Calculate Shapley values (Solution)
# Shapley val... | TradingAI/AI Algorithms in Trading/Lesson 19 - Feature Engineering/calculate_shap_solution.ipynb |
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# + [markdown] deletable=false editable=fa... | 06_soil_column_FEM.ipynb |
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# # Module 10 Application
#
# ## Challenge: Crypto Investments
... | Starter_Code/crypto_investment_final_draft.ipynb |
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# # Линейная регрессия и стохастический градиентный сп... | LearningOnMarkedData/week1/c02_w01_02.ipynb |
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# # 7.4 Venturi Type Valves
# A 150 by 100 mm class 6... | docs/Examples/Crane TP 410 Solved Problems/7.4 Venturi Type Valves.ipynb |
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# + [markdown] id="JS6jP7tpCrLr" colab_type="text"
# ## Digit Recognizer
# Le... | 4_Clasification_DigitRecognizer/2_DL_Multi_Layer_NN_for_DigitRecognizer.ipynb |
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# # Apply transformer to Coarse Discourse Dataset
# +... | datasets/reddit_coarse_discourse-corpus/apply_complexity_transformer.ipynb |
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# + [markdown] id="AF24jDF8d_Po"
# # **Data Visualization**
#
# ### **Agenda*... | 03_Data_Visualization/03_DataVisualization.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Ch10-OnPolicyControlwithApproximation/MountainCar.ipynb |
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import pandas as pd
df = pd.read_csv('../Dataset/Doma... | jupyter-notebooks/.ipynb_checkpoints/[01] [02] Gerador de Atributos-checkpoint.ipynb |
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# + id="kXQR7ZpCsYBP" outputId="02f33c4e-76d4-4d28-982... | COVID_19-DATA-ANALYSIS/Covid_19_Data_Analysis(SUYASH).ipynb |
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# + title: Does Jameda discriminate against non-paying... | jameda_part2.ipynb |
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import cv2
import numpy as np
# ### Create our body c... | 14_Pedestrian_Detection.ipynb |
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import numpy as np
from sklearn i... | Q3 - XGBoost.ipynb |
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# # LIBRERIAS
#
# Podemos importar operaciones u otra... | 6_Librerias.ipynb |
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import time
# Importing Inventory dat... | 4. Inventory Management System with JSON/9. Conclusion/Inventory Management System - Conclusion.ipynb |
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# # Copy Number segments (Broad)
#
# The goal of this ... | notebooks/Copy Number segments.ipynb |
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# Code for recording calls
import sys
import math... | src/Record calls.ipynb |
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# # Bosons in optical tweezers
# This Note... | examples/Example_Hopping_Bosons.ipynb |
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# + [markdown] colab_type="text" id="view-in-github"
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# # Non-Iterative Optimizers
#
# AKA Level 2 optimizers, are unifi... | docs/notebooks/noniterative_optimizers.ipynb |