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/assignments/01_Intro2images-stVer.ipynb | 4c19b92543a0a199321351440743bd0c5a184586 | [] | no_license | iknyazeva/ML2020 | https://github.com/iknyazeva/ML2020 | 0 | 13 | null | 2020-09-21T09:56:38 | 2020-09-21T09:53:56 | Jupyter Notebook | Jupyter Notebook | false | false | .py | 10,090,911 | # ---
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# + Collapsed="false"
import numpy as np
from skimage ... | 7,627 |
/Featureselection1.ipynb | 6436b45c27083bb89cf6a9ae3aa1bd3bcc1ff9f1 | [] | no_license | gabibu/unsupervisedLearning | https://github.com/gabibu/unsupervisedLearning | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 247,907 | # ---
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# # Secret-key or symmetric cryptography
#
# ## 1 DES ... | 12,425 |
/code_back_up/backuped_on_sharefolder_2021-01-06_000/00227_Performance_measurement_updated_1221.ipynb | 8335f10935d9168b511306fb2b27f3a6bd5534ca | [] | no_license | TrellixVulnTeam/jian_projects_AAPL | https://github.com/TrellixVulnTeam/jian_projects_AAPL | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 82,546 | # ---
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# # Coursework 2: Data Processing
#
# ## Task 1
# This... | 15,859 |
/Jupyter/02. Python para ciencia de datos intermedio/Python para ciencia de datos intermedio.ipynb | d86c329ce86a16fff6ee4355e0d700457fd55cb7 | [] | no_license | juanesoc/Curso-python | https://github.com/juanesoc/Curso-python | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 291,183 | # ---
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# ## 控制迷宫寻宝机器人
#
# 在这个项目中，你将使用刚刚学到的知识，尝试根据要求，编写代码，来控制一... | 6,789 |
/hw2/Alexander_Telepov_hw2_p2.ipynb | 05bf7d0796fb7a35670f223717f0f8d1a4c0d287 | [] | no_license | alexander-telepov/ml-course-skoltech | https://github.com/alexander-telepov/ml-course-skoltech | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 431,082 | # ---
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# + [markdown] id="bWEEBnVC-Irv"
# # Home Assignment N... | 44,017 |
/data-structures/recursion/Staircase.ipynb | 2974220531bba573f441680fa2bd29175e5ba5e5 | [] | no_license | annahra/dsa-nanodegree | https://github.com/annahra/dsa-nanodegree | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 4,151 | # ---
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# + [markdown] graffitiCellId="id_v5swjqy"
# ### Probl... | 2,403 |
/Visual Genome - Regions.ipynb | aaca619c4e7f2a2edbc64ced4d5207349578bf36 | [
"MIT"
] | permissive | MeMAD-project/statistical-tools | https://github.com/MeMAD-project/statistical-tools | 1 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 2,475,773 | # ---
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# # Introducción a Python: Listas, Iteraciones y Strin... | 18,911 |
/Data_Structures/arrays/Duplicate-Number.ipynb | b14d3fc53738515f2f5384dd6594c4a844eec897 | [] | no_license | Data-Semi/DataStructure-LessonNotes | https://github.com/Data-Semi/DataStructure-LessonNotes | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 3,810 | # ---
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# ### Probl... | 1,881 |
/6_function.ipynb | f0f001ee2af6ead7a3055d9b4b0236603c7d6f9c | [] | no_license | wssunn/Python-Language | https://github.com/wssunn/Python-Language | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 7,201 | # ---
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# ### 迭代器
#
# ```python
# x = [1, 2, 3]; it = iter(x)
# print(it.__next__()) ... | 3,684 |
/2. SKKU/2.DeepLearningBasic/Practice2_Softmax_Classifier/.ipynb_checkpoints/Samsung_SDS_Practice2_Softmax_Classifier-checkpoint.ipynb | 759b6d3e793c77c17de695744cc5f6cc470097c4 | [] | no_license | LeeKeon/AI | https://github.com/LeeKeon/AI | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 125,936 | # ---
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# # Practice2. Softmax classifier
# +
import numpy as... | 16,856 |
/13_sql.ipynb | 72fd7d34098246695262ad7fb85aa4ad1c4d829b | [] | no_license | kisslitsyn/ya.practicum | https://github.com/kisslitsyn/ya.practicum | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 43,457 | # ---
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# # Lab 2: Inference in Graphical Models
#
# ### Machi... | 17,297 |
/reproductions/Example/Example_05_04.ipynb | c4c2b66bffc7496da634cfb7e89f9f33acaf7ac2 | [] | no_license | Sikhu-Ntaka/Skogestad-Python | https://github.com/Sikhu-Ntaka/Skogestad-Python | 0 | 0 | null | 2020-01-29T13:15:55 | 2020-01-29T13:05:41 | null | Jupyter Notebook | false | false | .py | 1,731 | # ---
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# # Linear Regression [35pts (+5 bonus)]
#
# ## Introd... | 24,644 |
/experimentation/jiaxin_experiment/.ipynb_checkpoints/OOP_format-checkpoint.ipynb | eafe04a384f0c3bdb07deb7ef176ea052e9ceea3 | [] | no_license | mtaziz/STB_social_media | https://github.com/mtaziz/STB_social_media | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 21,460 | # ---
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# Amend to set wd to STB_social_media_analytics.
# %cd... | 16,636 |
/Python_advanced/multiprocessing.ipynb | b5a17c2a95cc436dfc73680b386204cd5a1e373b | [] | no_license | Artia-Inspirenet/education | https://github.com/Artia-Inspirenet/education | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 1,923 | # ---
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# # 建立明确网络和损失的输出输出流以及损失的计算定义
# - by 刘道会
# - 2020-08 于重... | 25,235 |
/2018/AD/Task/Hometask2.ipynb | e31ac0d5ae8445aa3a3b68004af1afd77312ec7a | [] | no_license | andriygav/School | https://github.com/andriygav/School | 1 | 2 | null | null | null | null | Jupyter Notebook | false | false | .py | 17,804 | # ---
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import numpy as np
import matplotlib.pyplot as plt
f... | 2,973 |
/Practica Functioneel Programmeren.ipynb | 3cbf7336ee9defe800a36dfa6bf354bce972f53c | [] | no_license | wvanbreukelen/practicum-atp | https://github.com/wvanbreukelen/practicum-atp | 0 | 0 | null | 2019-04-17T12:47:39 | 2018-03-14T11:39:22 | null | Jupyter Notebook | false | false | .py | 41,879 | # ---
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# # Practica Functioneel Programmeren
# Dit bestand be... | 29,883 |
/Semi_Project 4 Find Waldo/train.ipynb | d43f3c7b195a3c5b0f53d787660063c50a4bc32b | [] | no_license | jaytoone/A.I_Image | https://github.com/jaytoone/A.I_Image | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 4,339,026 | # ---
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# + id="qJGqC_vHyHVi" colab_type="code" colab={"base_uri": "https://localhost... | 115,806 |
/Cours-TD/B-exos-corrigés-1.ipynb | de981e30d53ca6d5649f6e5475a1251c06ac072e | [] | no_license | FranckCHAMBON/L1-Math-Info---Arith | https://github.com/FranckCHAMBON/L1-Math-Info---Arith | 1 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 9,890 | # ---
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# ## Florian BARRAL
# florian.barral@essec.edu
# **Yo... | 34,038 |
/labs/06-resampling_and_the_bootstrap/lab.ipynb | 8e06b454fbbe9ca05dcb8c0911efd6b3bc28c416 | [] | no_license | IceSelkie/dsc10-2020-fa-public | https://github.com/IceSelkie/dsc10-2020-fa-public | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 27,558 | # ---
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# ## Lab 6: Resampling and the Bootstrap
#
# Welcome t... | 18,245 |
/DeterministicPCA.ipynb | 67fc4b503afe1d9c23e1119c6fb7ad2798b1cb31 | [
"MIT"
] | permissive | MarcelloVendruscolo/ProbabilisticMachineLearning | https://github.com/MarcelloVendruscolo/ProbabilisticMachineLearning | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 443,588 | # ---
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# + id="iRjddwOiWzr5" tags=["keep"]
# %mat... | 25,482 |
/.ipynb_checkpoints/NBA_GET_TEAMS-checkpoint.ipynb | 8d0048be0cfc6d51b22ba94e4716fea5126ac2ff | [] | no_license | Peilin-D/NBA_Stats | https://github.com/Peilin-D/NBA_Stats | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 3,297 | # ---
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# <small><i>This notebook was prepared by [Rishi Rajas... | 1,920 |
/newbridge/particlebox.ipynb | d6701ed7348b884ecebe7a5730ad33d4414ca499 | [] | no_license | hbhat4000/pathsamp | https://github.com/hbhat4000/pathsamp | 1 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 7,564 | # ---
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import spacy
from spacy.tokens import Span
from sp... | 22,194 |
/Task - 5 (Python Programming)/Task - 5 (Python Programming).ipynb | fb91f466cdd9a3eef808e2b423afa7decb02579a | [] | no_license | Soyel-Shaikh/Innomatics_Internship_APR_21 | https://github.com/Soyel-Shaikh/Innomatics_Internship_APR_21 | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 16,460 | # ---
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# Question 1 Detect Floating Point Number
import ... | 6,329 |
/content/00_prerequisites/00_introduction_to_python/colab.ipynb | 3d727fa5a8e3601a250497a0dc1bc86db76a2ccb | [] | no_license | sultanalnahian/Coursera_MachineLearning-Regression | https://github.com/sultanalnahian/Coursera_MachineLearning-Regression | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 95,470 | # ---
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | 51,099 |
/Ex2_4_Thompson_Beta.ipynb | 2e737608f4ff127432d655d938d4af2bcd9565a9 | [] | no_license | skywalker0803r/Microsoft-DAT257x-Reinforcement-Learning-Explained | https://github.com/skywalker0803r/Microsoft-DAT257x-Reinforcement-Learning-Explained | 1 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 79,663 | # ---
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# ## TensorFlow
#
#
# #### What is it?
# * System for ... | 29,957 |
/lectures/05-design.ipynb | 3eb28195787be8c2d05110529d4ee55a6ca446db | [
"MIT"
] | permissive | MelLain/mipt-python | https://github.com/MelLain/mipt-python | 94 | 80 | MIT | 2022-05-07T10:51:15 | 2022-04-16T11:04:20 | Jupyter Notebook | Jupyter Notebook | false | false | .py | 46,549 | # ---
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# + [markdown] slideshow={"slide_type": "slide"}
# # `... | 29,779 |
/tp2/TP2_bandits_sinRespuestas.ipynb | 89745e0f98f388933bbfb064a7ac03c4e228f8e5 | [] | no_license | LecJackS/Procesos-Markovianos-Para-el-Aprendizaje-Automatico-2019-1C | https://github.com/LecJackS/Procesos-Markovianos-Para-el-Aprendizaje-Automatico-2019-1C | 1 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 6,853 | # ---
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import numpy as np
import matplotlib.pyplot as plt
# %... | 4,978 |
/user-churn-prediction-EMR.ipynb | 11e7a6b4b652b88de467493ff8bd9baa7dd79675 | [] | no_license | LanmingMa/user-churn-prediction | https://github.com/LanmingMa/user-churn-prediction | 0 | 0 | null | null | null | null | Jupyter Notebook | false | false | .py | 88,489 | # ---
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# # MAP and MPE Inference
#
# **COMP9418-19T3, W09 Tut... | 46,011 |
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