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# MNIST
#
# @author becxer
# @email <EMAIL>
# @r... | Jupyter/001_MNIST.ipynb |
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# ### Heroes Of P... | HeroesOfPymoli/.ipynb_checkpoints/HeroesOfPymoli_hw-checkpoint.ipynb |
# -*- coding: utf-8 -*-
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# # MATH50003 Numerical An... | sheets/week10.ipynb |
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import os
from pathlib import Path
import math
imp... | notebooks/data_scrapping/Load_recipe_content.ipynb |
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# ML Project Template
# # Frame the Problem and Look ... | machine-learning-template.ipynb |
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# + [markdown] Collapsed="false"
# # Publication queri... | archive/2-Publications-queries.ipynb |
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# !pip install dna_features_viewer
# !pip install --u... | covid19/prelim.ipynb |
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# ## 1.2 引领浪潮的LaTeX
#
# ### 1.2.1 LaTeX的出现
#
# LaTeX是一... | chapter-1/section2.ipynb |
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import pandas as pd
iris=pd.read_csv("https://archive.... | Lecture 5 Pandas/Manipulating Data in data frame-2/Manipulating Data in DataFrame -2-checkpoint.ipynb |
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# Code for **"Inpainting"** figures $6$, $8$ and 7 (to... | 0-newbooks/deep-image-prior/inpainting.ipynb |
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# # Mathematical model of the curtain
# ## Model parameters
... | challenges/curtain/notebooks/.ipynb_checkpoints/Mathematical model-checkpoint.ipynb |
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import pandas as pd
import numpy as np
df = pd.re... | Section 2/Video 2.4/Video 2.4.ipynb |
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# # Using Pima dataset for classification
import nump... | classification/classification_pima_02.ipynb |
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# # TASK -2
# ## Exploring Supervised Machine Learning... | Task_1_Linear Regression.ipynb |
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import pandas as pd
import matplotlib.pyplot as pl... | notebooks/explore_data_original.ipynb |
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# ## pCMV-Target-AID
# QUEEN script for pCMV-Target-A... | demo/sakata_et_al_2020/pCMV_Target_AID_construction.ipynb |
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# # 2-3.4 Intro Python
# # The Power of List Iteration... | Python Fundamentals/Module_3_4_Python_Fundamentals.ipynb |
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# # Depth Map from Stereo Images
#
# _You can view [I... | calibration-reconstruction/depth-map/README.ipynb |
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# + [markdown] id="hQnUF4trhLQ4" colab_type="text"
# #... | exercises/rl_workshop_cliff_world.ipynb |
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# # Markdown
#
# Per formattare il testo, Jupyter met... | project/markdown.ipynb |
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# # Amazon Personalize Workshop Part 2 - Vi... | getting_started/notebooks/2021-06-20-amazon-personalize-workshop-part-2.ipynb |
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# # Graphs using Matplotlib
# Matplotlib is a plotting... | algorithms/ml/Graphs(Matplotlib)/Graphs(Matplotlib).ipynb |
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import pandas as pd
import numpy as np
import matp... | 6.0 Computer Vision/2.0 Tensorflow/Plant Disease2.ipynb |
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# + active=""
# 说明：
# 给出矩阵 matrix 和目标值 target，返回元素... | Dynamic Programming/1104/1074. Number of Submatrices That Sum to Target.ipynb |
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import pandas as pd
import numpy as np
import matplot... | jupyter_notebook_code/Random Forest Classifier.ipynb |
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# + [markdown] id="YwMU3rCeoB-j" colab_type="text"
# # **nnU-Net : The no-new... | nnunetmec2020.ipynb |
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import networkx as nx
G = nx.read_adjlist("data/tiny_... | testbed.ipynb |
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# !python setup.py build_ext --inplace
import os
... | cv-competition-1/pytorch_baseline/pytorch_baseline.ipynb |
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# # Record Embedding
import pandas as pd
import numpy... | Embedding-FastText_hospital_results.ipynb |
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import networkx as nx
import matplotlib.pyplot as plt
... | deprecated-tsp.ipynb |
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# **Download** (right-click, save target as ...) this ... | 8-Labs/Lab23/src-lessold/.ipynb_checkpoints/Lab23_Class-checkpoint.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Random_Forest_Project.ipynb |
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from GENIE3 import *
sizen = 200
# +
fname='/home/li... | eval/synnet_and_genie3.ipynb |
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# + [markdown] id="_55E3-GVHuGx"
# # Get the data
# +... | notebooks/ipynb/BruteForce - Gradient Boosted Trees.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | covid_19_V2_Exploratory_Data_Analysis.ipynb |
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# ## 14.1 - 14.3
# Compute using $h=2^{-1}, 2^{-2}, \... | solution_chapter14.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="waM_Vx6Ej4DW" outputId=... | notebooks/root-cause-analysis.ipynb |
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# + [markdown] id="bwCxd7ugXMCu"
# # MNIST Dataseti
#
# 0'dan 10'a kadar yazı... | Models/MNIST/MNIST - Easy.ipynb |
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# imports
import nibabel as nib
import numpy as n... | train.ipynb |
# -*- coding: utf-8 -*-
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# # SELECT from Nobel
#
# ## `nobel` Nobel Laure... | R/03 SELECT from Nobel.ipynb |
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import tensorflow as tf
from tensorflow.keras import m... | well_logs.ipynb |
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import torch
from torch import nn
from torch.utils.data impor... | modules/module_20/pytorch.ipynb |
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# # Task 2: Create Bengali word embeddings
# ## Impor... | Task_2/bengali_bengali/Task-2c.1_bengali_word_embeddings.ipynb |
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# <center>
# <h1> ILI285 - Computación Científica ... | SC1/Bonus_Finding_2_Chebyshev_Points_Graphically.ipynb |
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from requests import get
from bs4 import BeautifulSoup... | .ipynb_checkpoints/scrape+clean data-checkpoint.ipynb |
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import urllib
from bs4 import BeautifulSoup
import req... | WebScraping/FactCheckWebScraping.ipynb |
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# 
# ## Contents
#
# - [Abstract](inde... | notebooks/structure.ipynb |
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# # Detecting rooftop a... | rooftop-detection/main.ipynb |
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# # Space Flight Mice Kidney Gene Analysis
# ## networ... | notebooks/general_notebooks/all_pipelines_mice_kidneys.ipynb |
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# # Tutorial 7: Pancan data access
#
# Thi... | notebooks/tutorial07_pancan.ipynb |
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# + [markdown] colab_type="text" id="3o8Qof7Cy165"
# #... | courses/machine_learning/deepdive2/structured/labs/1b_prepare_data_babyweight.ipynb |
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import numpy as np
import matplotlib.pyplot as plt
fro... | First_experiment.ipynb |
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# + init_cell=true
# %logstop
# %logstart -rtq ~/.logs... | 9_ML_Natural_Language_Processing.ipynb |
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import can
import udsoncan
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bus = can.Bus(interfac... | notebooks/00_Bootstrap.ipynb |
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# ### XGBoosting Easy version
# +
import numpy as np ... | Big_Data_Analysis/feature_selection/12-1xgb(easy).ipynb |
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# Objectives :
# Re-itirate and understand
#
#
# ... | Machine Learning/Julia/Basics of Machine Learning with Julia.ipynb |
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# # xspec Documentation (v1.3.2)
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# ### <NAME> - Udacity / SDCND - May./2019.
#
#
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# # Datasheet for "Where it pays to go to college"
# ... | botasakhi/Datasheet.ipynb |
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# + id="RWPN3PCP-IwW" colab_type="code" colab={"autoexec": {"startup": false,... | Machine_Learning/SVM/Credit_Card_Fraud_Detection/Credit_Card_Fraud_Detection_Using_SVM.ipynb |
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# # Mass Detection training
#
# +
import os
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from collections import defaultdict, deque
# ## algo... | 100days/day 78 - horn-satifiability.ipynb |
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# ## Generate points for the cases tab
#
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# # Task 3: preprocessing
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# Imports
import re
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# + [markdown] colab_type="text" id="view-in-github"
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# **Корректность проверена на Python 3.7:**
# + pandas... | Yandex data science/4/Week 2/.ipynb_checkpoints/stat.student_tests-checkpoint.ipynb |
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# # Assignment 3
import numpy as np
from matplotlib i... | 18cse002-Assignment 3.ipynb |
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# ## 練習時間
# 資料的操作有很多，接下來的馬拉松中我們會介紹常被使用到的操作，參加者不妨先自行想像一... | HomeWork/Day_004_HW.ipynb |
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# + [markdown] id="JgBwwu4ZAHKK"
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# # Active Learning on Logistic Regression
# ## Config... | Active Learning Regression.ipynb |
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# <a href="https://colab.research.google.c... | tutorial_nbs/00c_Time_Series_data_preparation.ipynb |
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# + [markdown] id="woaQzCU4smj8"
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# # Assignment - Index splitting (take home... | advance/cv-master/Assignments/a07.ipynb |
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# Built-in libraries
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# %load_ext autoreload
# %matplotlib inline
# %autorel... | notebooks/label_refinery/output-1535206418/label_refinery-use_pre1-run_num4.nbconvert.ipynb |
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# # Divorce rates and their relationship with Marriage rate and Median A... | The Many Variables & The Spurious Waffles.ipynb |
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# # word2vec IMDB data
#
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import sys
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import pandas as pd
import plotly.express as px
import... | Untitled.ipynb |
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# + colab={"base_uri": "https://localhost:8080/", "hei... | data/drafts/seq2seq.ipynb |
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# # CarND Object Detection Lab
#
# Let's get started!
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# + [markdown] id="view-in-github" colab_type="text"
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# # Convolutional Autoencoder
#
# Sticking with the MN... | autoencoder/Convolutional_Autoencoder.ipynb |
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# # Introdução
# Este arquivo se refere aos dados obt... | volumes_2019_1.ipynb |
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# Notebook to play with WOD data using the wodpy packa... | Nancy/strat/comparisons/WOD Data-pandas.ipynb |
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# Python core
from typing import ... | notebooks/20.0_simplify_data_loading.ipynb |
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import ee
import geodatatool
Map = geodatatool.Map()
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# # Basics tutorial
import numpy as np
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# # Landsat 8 NDVI Analysis on the Cloud
#
# This note... | notebooks/0-landsat8-on-gcs.ipynb |
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// # Analysing JSON Data
//
// This example de... | examples/weather/ProcessJSON.ipynb |
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import pandas as pd # data package
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# # Modelling lithium plating in PyBaMM
#
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#自作moduleのパスを追加。
import sys
sys.path.append('../my... | CreateHtmlFile/CreateHtml.ipynb |