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# **Introduction to markdown**
# # intro
# ## intro
... | Basics/file 1.ipynb |
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# <h2 style="color:green" align="center"> Machine Lear... | Week02/Day02/Linear Regression Multivariate/2_linear_regression_multivariate.ipynb |
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import pandas as pd
import numpy as np
data = pd.read... | Python/statistics_with_Python/03_Python_Enviroment/Markdown_notebook/05_reshapingData.ipynb |
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from sqlalchemy import create_engine
import spotipy
fr... | data_collection/concatenate_SQL_files.ipynb |
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import numpy as np
import sys
sys.path.append('../')
i... | refactoring/demo_notebook/StraightnessAnalysis.ipynb |
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# + [markdown] colab_type="text" id="view-in-github"
#... | tutorials/W3D4_ReinforcementLearning/student/W3D4_Tutorial3.ipynb |
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# + [markdown] colab_type="text" id="pUq0PvsJ16LM"
# #... | blog_notebooks/intro_to_cudf/getting_started_with_cuDF.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | CIFAR10_Image_Classification_using_CNN.ipynb |
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import turicreate as tc
import mxnet as mx
import nump... | data/output/style_transfer_demo.ipynb |
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# <p align="center">
# <img src="https://github.... | Interactive_Simulation.ipynb |
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print("Hello World!")
print("1,2,3,4,5")
print("This ... | files/Intro to jupyter notebook.ipynb |
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import os
import pandas as pd
import numpy as np
from ... | Homeworks/Extra credit Algorithms/K_Means.ipynb |
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# <h1>Training on Cloud AI Platform</h1>
#
# This note... | courses/machine_learning/deepdive/06_structured/labs/5_train.ipynb |
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# + id="dlsBDOweUJyP" colab_type="code" colab={}
import os
import sys
import... | tensorflow/estimator/Linear.ipynb |
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# ## Activity 01: Use NumPy to compute the Mean, Media... | Lesson01/Activity01/activity01_solution.ipynb |
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# ## 8-2. グローバーのアルゴリズム
#
# グローバーのアルゴリズムは、整列化されていないデータベ... | notebooks/8.2_Grovers_algorithm.ipynb |
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import torch
import torchvision
import torch.nn as nn
... | PyTorch_autograd.ipynb |
# # Traces
# +
import model.utils as utils
from model.HodgkinHuxley import HodgkinHuxley
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
# %matplotlib inline
# + inputHidden=false outputHidden=false
# !mkdir svg/
# +
I, t_on, t_off, dt = utils.syn_current()
I = I*0.75
true_params, _ =... | 1_goal/01_make_traces.ipynb |
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# Lambda School Data Science
#
# *Unit 2, Sprint 1, Mo... | module3-ridge-regression/LS_DS_213_assignment.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | 28septiembre.ipynb |
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# # Random Forests Multi-node, Multi-GPU demo
#
# The ... | cuml/random_forest_mnmg_demo.ipynb |
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# Центр непрерывного образования
#
# # Программа «Pyth... | class_7-8/classes/Classes_lecture.ipynb |
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# <!--BOOK_INFORMATION-->
# <a href="https://www.packt... | notebooks/03.02-Understanding-the-k-NN-Algorithm.ipynb |
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# ### Introduction
#
# Text classification algorithms ... | Machine Learning Interview Task/Text classification For Enron Email Classification.ipynb |
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import pickle
import numpy as np
import tensorflow... | Traffic Sign Classifier/KERAS_DNN.ipynb |
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# # Source: Rivals
#hide
import core_cons... | j_notebooks/Rivals.ipynb |
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# # Monte Carlo Simulation
#
# Working with Lennard-Jo... | day3_hw.ipynb |
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# <h1> EDA & Data Visualization </h1>
# <hr>
# <h3>In ... | Data-Visualization/1-Visualization-and-Reports.ipynb |
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# + pycharm={"name": "#%%\n"}
'''
3.2.3 create_regress... | notebooks/3.2.3 create_regression_prediction_c2.ipynb |
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from oda_api.api import DispatcherAPI
from oda_api.plo... | examples/spectrum_longterm.ipynb |
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# # 02 - Multilayer perceptrons in gluon
import mxnet... | In Progress - Deep Learning - The Straight Dope/03 - Deep Neural Networks/02 - Multilayer perceptrons in gluon.ipynb |
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from matplotlib import pyplot as plt
plt.style.use('classic')
fro... | 1.Simple Linear Regression/3.Model Accurcay/predictHousePrice.ipynb |
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# %matplotlib inline
import numpy as np
import cv2
fro... | SR MAM PROJECT.ipynb |
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# # How Jupyter is used
#
# Rule, Adam, <NAME>, and <N... | Intro to Jupyter.ipynb |
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# %pylab inline
# %matplotlib inline
from... | demo.ipynb |
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# # Decision Trees ::
#
# **Class is implemented only... | Trees/Example-Classification_and_Regression.ipynb |
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# # Process Results
# ## Imports
# +
import pandas a... | results/get_results-3-clases.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | classified.ipynb |
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import random
import math
class Point:
def __init__(self... | 2021_Math/m17.ipynb |
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# # Keypoint regression
# Single keypoint regress... | notebooks/keypointregression.ipynb |
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# # Fig 15. Scatter plot of research centres by number... | notebooks/15. Scatter plot of research centres by number of projects and total funding.ipynb |
# # 10 Taking Advantage of First Class Objects
# ### 10.1 First Class Objects
#
# Python exposes many language features and places
# almost no constraints on what types data
# structures can hold.
#
# Here's an example of using a dictionary of functions to create a
# simple calculator. In some languages the only re... | speakers/Stuart Williams/PyCon-2016-Python-Epiphanies/Python-Epiphanies-07-10-Taking-Advantage-of-First-Class-Objects.ipynb |
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# # Econophysics I
# ## Exercise 03 - H07
#
# ### <NAM... | week_3/Exercise03_H07_05.ipynb |
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import pprint
from keras.utils.data_utils import g... | Embedding/.ipynb_checkpoints/word2vec_example-checkpoint.ipynb |
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# **Important: This notebook will only work with fasta... | courses/dl2/carvana-unet-lrg.ipynb |
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# 1- Importar librerías
import pandas as pd # data... | 12_ Deep-Learning/CNN_Keras_cats_dogs.ipynb |
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# # Exercise 2 - Shor's algorithm
# ## Historical back... | solutions by participants/ex2/ex2-GiacomoDiStasio-24cnot.ipynb |
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# import packages
import pandas as pd
import matplotl... | WK1_EDA.ipynb |
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# # Install ship_mapper
# ----------------------------... | tutorials/Install_ship_mapper.ipynb |
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from Sapphire.Utilities.Bui... | main/Sapphire/Tutorials/CNA/Tutorial.ipynb |
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# + id="uAVuwjwIvgAH" executionInfo={"status": "ok", "... | week3/avneesh/Q3 - 2/Attempt1_filesubmission_Avneesh Mishra - Smooth Planning Spirals.ipynb |
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import warn... | 3-2. VGG16 Triplet Network (margin 0.5).ipynb |
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# # Ex2 - Filtering and Sorting Data
# This t... | 02_Filtering_&_Sorting/Euro12/Exercises.ipynb |
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'''
Written by rizawa
Written on 2018-06-08
'''
i... | groups/nx_simple_paths-Copy1.groups.v9.ipynb |
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# ## 特征提取
# +
from keras.applications import Xception... | with_ImageDataGenerator.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Eigenvalue_and_Eigenvector.ipynb |
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# # Ray Tune - Understanding Hyperparameter Tuning
#
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def _pad_sequence(
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from Trajectory impo... | src/Notebook/Point Lander with Drag.ipynb |
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from dbcm2.DBcm import *
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# # 경사 하강법을 이용한 얕은 신경망 학습
#
import tensorflow as tf
import n... | RNN_TF20/03. Shallow Neural Network Training with Gradient Descent-Antonio.ipynb |
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# # Inductive Miner
# ## Step 1: Handling and import ... | src/BPIC 2012/InductiveMiner_after.ipynb |
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# + [markdown] id="AruwmQxE5Xm_"
# In this assignment ... | Visualization_Assignments/Copy of A_06_VisualizationWithSeaborn_en.ipynb |
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# # Adatstruktúrák
# Pythonban több összetett adattíp... | teljes/05-Adatstrukturak.ipynb |
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# default_exp data.text2text.core
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# %re... | nbs/01za_data-text2text-core.ipynb |
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# + id="izDHCRIt8gqQ" colab_type="code" colab={"base_uri": "https://localhost... | mobile_net_ssd.ipynb |
# -*- coding: utf-8 -*-
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# # Graph Coloring Kata Workbook
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#... | GraphColoring/Workbook_GraphColoring.ipynb |
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# %matplotlib inline
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# ============================... | stable/_downloads/c252c7618c44ac318ad1e9e85d5b7059/plot_decoding_csp_timefreq.ipynb |
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# # data for the distance-size ratio ... | Experiments/D&N&Time/.ipynb_checkpoints/D&N&Time-checkpoint.ipynb |
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# + [markdown] id="bOChJSNXtC9g" colab_type="text"
# # Advanced RNNs
# + [ma... | notebooks/14_Advanced_RNNs.ipynb |
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# # 국공립 어린이집 최적 입지 선정 | [서울시 빅데이터 캠퍼스 공모전](https://big... | Project_md_kernel_2.ipynb |
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# %autosave 2
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import numpy as np
... | misc/jupyter_notebooks/17.10.13/numpy_table.ipynb |
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# Copyright (c) Microsoft Corporation. All rights r... | how-to-use-azureml/work-with-data/datasets-tutorial/labeled-datasets/labeled-datasets.ipynb |
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import torchvision
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import torch.optim as... | AI Painting.ipynb |
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# + [markdown] colab_type="text" id="view-in-github"
# <a href="https://colab... | tutorials/Benchmark_Linear_Image_Classification_on_ImageNet_1K_V0_1_6.ipynb |
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import RPi.GPIO as GPIO # Import Raspberry Pi GPIO... | bottle_recognition/tries/test_GPIO.ipynb |
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# ### What's New in Python 3.6
# Here ... | dd_1/Part 1/Section 10 - Extras/01 - Python 3.6 Highlights.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="w35zPOcMyNwJ" outputId=... | Bark 101/Bark_101_impl_1_1_Original_RGB_Dense201_Custom_withImageNet_DataFlow.ipynb |
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# # Bayesian Network
from IPython.display import Imag... | notebooks/2. Bayesian Networks.ipynb |
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# + [markdown] colab_type="text" id="pBQsZEJmubLs"
# <... | curriculum/unit-4-machine-learning/sprint-2-intro-nn/module3-Intro-to-Keras/LS_DS_423_Keras_Assignment.ipynb |
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# Credits: Forked from [deep-learning-keras-tensorflow... | deep-learning/keras-tutorial/2.2.1 Supervised Learning - ConvNet HandsOn Part I.ipynb |
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fr... | pyspark/example/spark_core/4.5_shared_variable.ipynb |
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# File contains a number of useful pandas code snippet... | learning/pandas.ipynb |
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# # Using PyTorch DALI plugin: using various readers
#... | docs/examples/pytorch/pytorch-various-readers.ipynb |
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# # Análisis de Patrones en Texto
# Muchas veces nos ... | Modulo2/3. Funciones Strings.ipynb |
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raw_... | notebooks/1_Complaint_Status_Tracking.ipynb |
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# The ``Select`` widget allows selecting a ``value`` from a list or dictionary of ``options`` by selecting ... | examples/reference/widgets/Select.ipynb |
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# ## This notebook can be used as a quick check for va... | model_var_overview.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
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# <h1 align = 'center'> Neural Networks Demystified </... | Python/ML_DL/DL/Neural-Networks-Demystified-master/Part 2 Forward Propagation.ipynb |
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class Ball:
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import os, sys
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from pathlib import Pa... | notebooks/LFNA/synthetic-visualize-env.ipynb |
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# # Classification modeling
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# Working with int... | notebooks/.ipynb_checkpoints/09_interpolated_modeling-checkpoint.ipynb |
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# + [markdown] colab_type="text" id="-eFju4_DDKeX"
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# hash: 31f2aee4e71d21fbe5cf8b01ff0e069b9275f589... | ETL/cleanUp answer_photos.ipynb |
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! [ -e /content ] && pip install -Uqq self... | nbs/12 - byol.ipynb |
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# # Reinforcement Learning
# Here we'll look into wha... | _archived/tensorflow/tensorflow_5.ipynb |