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# + id="vPOn1ABLheho" colab_type="code" colab={}
import plotly.graph_objects ... | visualization/Word_Frequency.ipynb |
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# No notebook anterior, nós aprendemos intuitivamente ... | Perceptron.ipynb |
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# # Introduction to Datamining
# ###... | course_overview.ipynb |
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# ## This notebook serves as a refresher with some bas... | notebooks/1_Python_101.ipynb |
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# # Feature engineering
# This notebook will teach you... | notebooks/.ipynb_checkpoints/feature_engineering-checkpoint.ipynb |
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# + id="copyright"
# Copyright 2021 Google LLC
#
# Licensed under the Apache ... | notebooks/community/ml_ops/stage2/mlops_experimentation.ipynb |
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# # Python for Youth
# We learn python through a game... | lessons/python/python-for-kids/Python-lesson.ipynb |
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# # Question 2 - Build and Apply a perceptron
#
# For ... | Single Layer Perceptron/.ipynb_checkpoints/Question2_Notebook-checkpoint.ipynb |
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# # Ungraded Lab Part 2 - Consuming a Machine Learning... | course1/week1-ungraded-lab/client.ipynb |
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from data_cleaning import clean_defender_data
from... | FantasyPL-Flask/Untitled1.ipynb |
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// # Classification on Iris dataset with sklearn... | jupyter/onnxruntime/machine_learning_with_ONNXRuntime.ipynb |
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import pandas as pd
# !head -n 1000 violations.csv >... | Homework 11 Soma.ipynb |
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import numpy as np
import matplotlib.pyplot as plt... | Deconvolution/convolution1.ipynb |
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# # Problem 250 - 250250
#
# Find the number of non-em... | Euler 250 - 250250.ipynb |
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# # ESTUDIO DE CASO: PREDICCIÓN DE ENFERMEDAD DEL CORAZÓN
# 1- Demostrar conocimiento organizacional o de contexto
# 2- Demostrar conocimien... | Caso de estudio 3/caso_de_estudio_3.ipynb |
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import pickle
import pandas as pd
impo... | notebooks/Compare_mCT_vs_SMP_SSA.ipynb |
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# # [Species Name] Records from GBIF and/o... | Query_TEMPLATE.ipynb |
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# + [markdown] graffitiCellId="id_qwukc5b"
# # Exercis... | Jupyter Tutorial/Exercise_Heterogenous_plugin_and_the_DevCloud.ipynb |
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# # 人脸关键点检测
#
# **作者... | docs/practices/landmark_detection/landmark_detection.ipynb |
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# + [markdown] id="glA3NV9MRl63" colab_type="text"
# # Kalman Filter - Lab 7.... | Lab_7_2_KalmanFilter.ipynb |
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# + [markdown] deletable=true editable=true
# ... | Notes/P3 SmartCab/smartcab/.ipynb_checkpoints/smartcabzh-checkpoint.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | AIC_Project1_Jayden_v_Surprise.ipynb |
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# # Spartan Data Science
#
# # Imports
import pandas ... | Titanic - Random Forest (0.73205).ipynb |
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# requests is a library that helps get web pages
# url... | notebook/Requests_Stub.ipynb |
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# # Rating Movies IMDB
# ## Importing the... | rating-movies-imdb.ipynb |
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# # Two stream numerical code and tests
import numpy ... | 001_Overview.ipynb |
# # Trying the Julia programming language in the Jupyter Notebook
println("Hello world!")
f(z, c) = z.*z .+ c
f(2.0 + 1.0im, 1.0)
z = [-1.0 - 1.0im 1.0 - 1.0im;
-1.0 + 1.0im 1.0 + 1.0im]
z[1,end]
f(z, 0)
function julia(z, c; maxiter=200)
for n = 1:maxiter
if abs2(z) > 4.0
return n-... | Chapter05/12_julia.ipynb |
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# <script async src="https://www.googletagmanager.com/... | Tutorial-ADM_in_terms_of_BSSN.ipynb |
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# For more information about Monte Carlo Tree Sear... | 2.ReinforcementLearning/MCTS/mcts.ipynb |
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# # Mushroom classification using catboost
# +
from I... | mushroom_classification/mushroom_classification_catboost.ipynb |
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# Import most generic modules
import i... | gamestonk_terminal/jupyter/reports/similar_analysis.ipynb |
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# !jupyter nbconvert --to html DnnMath.ipynb
# # ... | TF-Keras_CHATBOT/.ipynb_checkpoints/DnnMath-checkpoint.ipynb |
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import pandas as pd
import numpy as np
import matplotl... | regression-problems/univariate-linear-regression-with-gradient-descent/linear-regression-with-gradient-descent-impl-01.ipynb |
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# # Traduction automatique
# Attention: c... | module5/s2_machine_translation.ipynb |
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# # ... | getting-started/getting_started_biology_modeling_tools.ipynb |
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# # Day and Night Image Classifier
# ---
#
# The day/n... | 1_1_Image_Representation/6_1. Visualizing the Data.ipynb |
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# # Welcome to the SETI Institute Code Challenge!
#
# ... | tutorials/Step_1_Get_Data.ipynb |
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# + [markdown] id="3HTm3uxaAblr"
# # GC-SAN
# > Graph Contextualized Self-Att... | docs/C699874_GC_SAN.ipynb |
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# # Physics laws commonly used in mathematical modelin... | J_Mathematical_Modeling/Section 2/SuppNoteBook-PhysicsLawsInBiology.ipynb |
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# # Problem Solving Approaches
# ## Greedy Algorithms... | Python/Problem Solving Approach.ipynb |
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# + [markdown] papermill={"duration": 0.039647, "end_t... | Source/zomato-success-factors-rating-predictions.ipynb |
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# ## Beamprofile (Figure 7)
# +
# Import modules
impo... | ipynb/fig07_beamprofile.ipynb |
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# # CS207 Project Group 9
# # Bambanta: Forward and Re... | docs/Final.ipynb |
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# # QCoDeS Example with Keysight 344xxA
# `344xxA` mo... | docs/examples/driver_examples/Qcodes example with Keysight 344xxA.ipynb |
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# # Handwritten Digits recognization using Deep Learni... | Deep Learning/4. Handwritten Digits recognization.ipynb |
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# # All decoders (except KF, NB, and ensemb... | Paper_code/ManyDecoders_DataAmt.ipynb |
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# reload packages
# %load_ext autoreload
# %autoreload... | notebooks/dataset-projections/fmnist/fashion-mnist-parametric-tsne.ipynb |
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# # Manejo de Ficheros
# Python nos permite trabajar ... | Modulo4/1. Manejo de Ficheros.ipynb |
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'''Deep Dreaming in Keras.
Run the script with:
```
p... | Deep Dreaming.ipynb |
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# # T-Student regression
# ---
# In this notebook we a... | t_regression.ipynb |
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# # Homework 6: Web Applications
#
# For this homework... | homework6/Homework_6.ipynb |
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import matplotlib.pyplot as plt
import numpy as np
imp... | 1_Predicting/data_visualization.ipynb |
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from sklearn.tree import DecisionTreeClassifier
fr... | module_6/Module_suppl_notebooks/ML-5.Decision_trees + RF.ipynb |
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import unittest
class MyTestCase(unittest.Tes... | Untitled.ipynb |
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import numpy as np
import matplotlib.pyplot as plt
fro... | code/notebooks/CAD-psych-paper/SCZSAFF/psychosis-Copy4.ipynb |
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# # 1 An introduction to ... | content/08. Remote services and multi-agent systems/08.1 Introducing remote services and multi-agent systems.ipynb |
from traj_py import XPStraj
import bluesky.preprocessors as bpp
import bluesky.plan_stubs as bps
# +
class ScanningExperimentalModule2():
""" the zero for Ry must be set correctly so that Rx is pointing in the x direction
once homed, this position i1s at -6.0
"""
x = EpicsMotor('XF:16IDC-ES:Scan2... | tests/flyscaning_2018Nov14.ipynb |
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# # Anonymizing data with Faker
from pprint import pprint
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import pandas as pd
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import numpy as np # linear algebra
import pandas... | Kaggle/Playgroud/Satisfaction/0-84-score-with-36-features-only.py.ipynb |
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# # SIR Modeling in Python, based on Numberphile
#
#... | SIRModeling.ipynb |
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# ## Importing Libraries & getting Data
import numpy as np
impor... | Kaggle Datasets/ML/Real or Fake Jobs/fakejobs.ipynb |
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# # Python List Iteration
# A variety of ways to itera... | Python Programming/10. Extras/Python List Iteration.ipynb |
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import numpy as np
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# %load_ext autoreload
# %autoreload 2
import num... | overlapping_reg/pre_summer2021/overlap_shi_ex_pt.ipynb |
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# -*- coding: utf-8 -*-
from __future__ i... | machineTranlsation/machineTranslation.ipynb |
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# <h1><font size=12>
# Weather Derivatites </h1>
# <h1... | code/nnLSTMtransition.ipynb |
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# + [markdown] id="gAlLjDLPDGC4"
# # COCOデータセットダウンロード
# + id="-OUkCFdBa_4N"
... | YOLOX-Colaboratory-coco-minitrain.ipynb |
# -*- coding: utf-8 -*-
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... | Jupyter notebooks/Circuitos Eletricos I - Semana 1.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="gghLdT_L86m3" outputId=... | DeepFace.ipynb |
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# + active=""
# 说明：
# 给定一棵二叉树，确定它是否高度平衡。
# 针对这... | Tree/0827/110. Balanced Binary Tree.ipynb |
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import numpy as np
import os
from PIL import Image
imp... | 1104-linearalgebra/PCA_SVD_image.ipynb |
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import os
from sklearn.decomposition import PCA
from s... | apps/dash-tsne/notebooks/Pandas Tests.ipynb |
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# %matplotlib inline
import matplotlib.pyplot as plt
i... | before_zipline.ipynb |
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# %load_ext autoreload
# %autoreload 2
import os
import ... | notebooks/illustrative_plot.ipynb |
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# # Safety of a Buckling Plate
import grama as gr
X =... | examples/demo/buckling_plate.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | ExplainModel.ipynb |
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# # Python для анализа данных
#
# *<NAME>, НИУ ВШЭ*
#
... | lect11_Selenium_API/2021_DPO_11_3_selenium-books.ipynb |
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# # Pandas 3: Shaping data
#
# The second in a seri... | Code/IPython/bootcamp_pandas-shape.ipynb |
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# name: python374jvsc74a57bd07945e9a82d7512fbf96246d9bbc29cd2f106c1a4a9cf54c9563dadf10f22... | week4_EDA_np_pd_json_apis_regex/day1_numpy_pandas_I/theory/python/global_local.ipynb |
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# + [markdown] deletable=true editable=true
# # Using ... | notebooks/pipeline_with_two_datasets.ipynb |
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# + id="fMpWRG9LdF8r"
# I need to Install Tensorlow using command
# !pip in... | Artificial Intelligence Code.ipynb |
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# ### <center>Update TCGA Workspace Data Model with Co... | notebooks/Update_Data_Model_to_Compact_DRS_Identifier.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Activity_1_Python_Fundamentals.ipynb |
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# + [markdown] id="KK-Ovk_OL8gb"
# Assignment 5
#
#
#
#
#
#
#
#
# + [markdow... | assignmet5_Neerja.ipynb |
# + [markdown] colab_type="text" id="copyright-notice"
# #### Copyright 2017 Google LLC.
# + cellView="both" colab={"autoexec": {"startup": false, "wait_interval": 0}} colab_type="code" id="copyright-notice2"
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compli... | ml/cc/exercises/zh-CN/sparsity_and_l1_regularization.ipynb |
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# # Run fidimag inside a Docker Container
# ## Setup ... | doc/user_guide/ipynb/tutorial-docker-container.ipynb |
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import cmath
z = complex(input())
print(*cmath.po... | Python/6. Math/31. polar coordinates.ipynb |
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# # 数值稳定性和模型初始化
#
# 理解了正向传播与反向传播以后，我们来讨论一下深度学习模型的数值稳定性问题以及模型参数的初始化方法。深度模型有关数值稳定性的典型问题是衰减（vanishing）和爆炸（explosion）。
#
#
# ## 衰减和爆炸
#
# 当神经网络的层数... | chapter_deep-learning-basics/numerical-stability-and-init.ipynb |
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import pandas as pd
d = [0,1,2,3,4,5,6,7,8,9]
df = pd... | learning python/learning pandas/pandas_lec_02.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# ## ... | slides/2_28/lenet.ipynb |
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# # Cycle through each year and extract the major topi... | .ipynb_checkpoints/07_tf-idf extraction and processing for each year - 6 topics per year of 5 words-checkpoint.ipynb |
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# # CRC Make-A-Thon Crash Course - API Number Exercise... | CRC Make A Thon Crash Course API Number Exercise.ipynb |
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# # CSC413 - Tutorial 2
# ## Tutorial overview
#
# - ... | assets/tutorials/tut02_pytorch.ipynb |
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# # Load the dataset.
with open("./datasets/football_... | research/common_neighbours_football.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
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# Bin data with logarithmically spaced bins notebo... | functions/notebooks/Bin data with logarithmically spaced bins.ipynb |
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#TEST 01
#trying to write to csv file
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# # Tutorial 2. Solving a 1D diffusion equation
# +
... | docs/build/html/examples/tutorial-02-diffusion-1D-solvers-FTCS.ipynb |