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# hash: bdff06bd94e17c36ce62... | Task-1_Linear_Regression.ipynb |
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import matplotlib.pyplot as plt
import matplotlib
impo... | plots/paper_runtime2.ipynb |
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# # Learning from BEL
#
# This notebook is about learn... | notebooks/learn_from_bel/Learning from BEL.ipynb |
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# ## Import PyMongo
import pymongo
pymongo.version
... | bigdata-with-python/pyMongo/oper-update-aggre.ipynb |
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# # Predicting Car Prices Based on Features
#
# The go... | car_prices.ipynb |
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# ## PyTorch Tutorial
#
# IFT6135 – Representation Lea... | pytorch/3. Introduction to the Torch Neural Network Library.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | section_4/02_deep_reinforcement_learning.ipynb |
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... | Pattern_Recognition_and_ML_Folder/Chapter_7_Sparse_Kernel_Machines/proj7_SVM_2Classes_SMO.ipynb |
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import numpy as np
import matplotlib.pyplot as plt
imp... | 170520AIworkshop05 COVID19 IND json.ipynb |
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# ## Setup
# load the packages
import requests
from b... | Web scraping/Scraping wikepedia Tables.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | MIT_6_036_HW11_Recurrent_Neural_Networks.ipynb |
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import psycopg2
import os
from datetime import dat... | notification.ipynb |
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# %matplotlib inline
#
# # Analyze data and then plot... | docs/auto_examples/analyze.ipynb |
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from utils.epg import *
import icecream as ic
import n... | APSApril/simComparison.ipynb |
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# + executionInfo={"elapsed": 891, "status": "ok", "ti... | code/NN_HW3.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | proje_02.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Vectors.ipynb |
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import tensorflow as tf
import numpy as np
import pick... | extractive-summarization/1.rnn-lstm.ipynb |
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# +
# Logging setup
import logging
logging.basicConfi... | notebooks/OrionDBExplorer Tutorial.ipynb |
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# # Plotting a Torus
#
# To plot a surface in 3D d... | problem_candidates/Plotting surfacees.ipynb |
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# pytorch의 경사하강법(gradient descent) 코드를 보고 있으면
# ```
# ... | 1.Study/2. with computer/3.Deep_Learning_code/4. Pytorch/0.basic/4. Auto_grad.ipynb |
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# # Download and store data
# This notebook conta... | data/my_create_datasets.ipynb |
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# # Assignment 4
#
# Welcome to Assignment 4. This wil... | Course-01-Fundamentals-of-Scalable-Data-Science/assignment4.1_spark2.3_python3.6.ipynb |
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using Plots; pyplot();
using DelimitedFiles, Distr... | examples/Regression - Laplace.ipynb |
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from eulerian_cities.eulerian import euler... | examples/examples.ipynb |
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# + hide_input=true inputHidden=true language="html"
#... | docs/case_studies/test4.ipynb |
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# # A look at solution data and processed variables
#... | examples/notebooks/solution-data-and-processed-variables.ipynb |
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# # Barplots
# +
# MIT License
#
# Copyright (c) 202... | tests/test_analysis_plots.ipynb |
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# + [markdown] nbgrader={}
# # Interact Exercise 6
# ... | assignments/midterm/InteractEx06.ipynb |
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# # Climate classification with neural networks
#
# Th... | 2018-06-11-climate-classification-with-neural-nets.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # ベ... | linalg/linear-algebra.ipynb |
# ##### Copyright 2021 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/steel_lns.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Audio_to__text.ipynb |
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# Require the packages
require(ggplot2)
require(reshape2)
library(re... | graphics/semeval_verbs_boxplots_semisupervised_R.ipynb |
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import shapeworks as sw
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# # Geographic data in Python {#spatial-cl... | ipynb/tmp.ipynb |
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'''
Sistemas de ecuaciones para resolver con el mé... | ProyectoMetodos_actualizacion2.ipynb |
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# %mat... | tracking.ipynb |
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# # Insurance and Incentives
#
# *By <NAME> and <NAME>... | insurance_incentives.ipynb |
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# # Topic Modeling
#
# For more details on how topic m... | Primative Text Analysis/topic modeling.ipynb |
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# # pyjanitor Usage Walkthrough
# `pyjanitor` is a Py... | examples/notebooks/pyjanitor_intro.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | module2/assignment_kaggle_challenge_2.ipynb |
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# Separating data into training, validation and test d... | Veera/load_dataset.ipynb |
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# # CORD-19 AuthorRank
#
# An example o... | notebooks/CORD-19.ipynb |
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# # Query a pandas DataFrame
#
# Returnin... | even-more-python-for-beginners-data-tools/05 - Query a pandas Dataframe/05 - Querying DataFrames.ipynb |
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# %%writefile README.md
# CarND-Path-Planning-Proj... | Untitled.ipynb |
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# # Problem 3.3 Learning From Data
from matplotlib im... | Problem_3_3.ipynb |
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# name: python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:ap-sout... | demo-workspace/DataScientist-01-FeatureEng.ipynb |
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# + init_cell=true nbsphinx="hidden" pycharm={"is_exec... | docs/source/guide/ipynb/hilbertspace_legacy.ipynb |
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import pandas as pd
# Load the data (python dict).
fro... | assignment5.ipynb |
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import matplotlib.pyplot as ... | case_studies/general/code/get_gas_prices.ipynb |
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# %matplotlib inline
#
# # SVM-Kernels
#
#
# Three di... | sklearn/sklearn learning/demonstration/auto_examples_jupyter/svm/plot_svm_kernels.ipynb |
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# ## Task2: Bengali Transfer Learning Binary Classifie... | src/task2/2_bengali_lstm_pret/Bengali_Transfer_Learning_Binary_Classifier.ipynb |
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# # Modeling with PyTor... | 5-sax-detector/code/11-pytorch-tuning.ipynb |
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# <h1>Table of Contents<span class="tocSki... | nbs/models.common.ipynb |
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# + [markdown] id="ecYnWlyCm7NO"
# # **Regular Expressions**
#
# - A sequence... | Miscellaneous/02. Regular Expressions.ipynb |
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# %run imports.py
import pandas as pd
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dateparse... | Air-Pollution-Levels-Exploratory-Data-Analysis-master/data_2014.ipynb |
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import pandas as pd
import numpy as np
import matplotl... | Orders.ipynb |
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# Dimensionality Reduction & Visualization
#
#
# +
im... | Homeworks/example 2 _ML_Dimensionality reduction_12_Mummadi.ipynb |
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# # Data Exploration
#
# The idea of this ... | notebooks/2021-08/2021-08-20/data_exploration.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/rostering_with_travel.ipynb |
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# The following exercise is from <u> Computational Phy... | Assignment2.ipynb |
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# # "Reproducing Refo... | _notebooks/2021-02-19-reformer-reproducibility-challenge.ipynb |
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# # Translating RNA into Protein
# ## Prob... | Bioinformatics Stronghold/LEVEL 1/PROT.ipynb |
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# ## Demo 1~3
# You can find a simple version in `eleg... | eRL_demos.ipynb |
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# + [markdown] _cell_guid="cb19f71d-51c8-417f-829e-317... | assets/source/titanic-logistic-regression-homework.ipynb |
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# # Bag of Colors
# This is my personal attempt at ma... | Bag of Colors.ipynb |
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# + language="javascript"
# IPython.OutputArea.prototy... | Research_logs_and_notebooks/Stable_logs/total_loss_per_round.ipynb |
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# # 2. Quickstart: Running a single Schwar... | docs/tutorial_notebooks/2_quickstart.ipynb |
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# # Homework 3 Problem 1
# In this homework, you'll l... | AI502-TA/hw3-1(TA).ipynb |
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import numpy as np
import wisps
import splat
impor... | notebooks/lsstdsfp_supervised_learning.ipynb |
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# # Peruvian Fiscal Numbers
# ## Introduction
# The ... | docs/source/user_guide/clean/clean_pe_ruc.ipynb |
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# # Contoh penggunaan `morph_analyzer.py`
#
# Pakej ya... | contoh_penggunaan.ipynb |
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# # Backpropagation Tutorial
# (C) 2019 by [<NAME>](h... | notebooks/Backpropagation_Tutorial.ipynb |
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# import os modules to create path across operating sy... | .ipynb_checkpoints/Untitled1-checkpoint.ipynb |
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# # Action Conditional Deep Markov Model using cartpol... | tutorial/English/04-DeepMarkovModel.ipynb |
# -*- coding: utf-8 -*-
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# # Протоколы аутентифи... | Lab 1/Lab 1.ipynb |
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# # Time Series Chains
#
# ## Forecasting Web Query Da... | docs/Tutorial_Time_Series_Chains.ipynb |
# -*- coding: utf-8 -*-
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# # Exercise 10. Introduction to the hypothesis ... | Exercise 10/T12_hypothesis_testing1.ipynb |
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# # Grouping by Time
#
# In previous notebooks, we lea... | jupyter_notebooks/pandas/mastering_data_analysis/07. Time Series/03. Grouping by Time.ipynb |
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# imports
import numpy as np
import pandas as pd
# lo... | .ipynb_checkpoints/RIA-data-checkpoint.ipynb |
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# # Calculate cosmological distances with CCL
# In thi... | Distance Calculations Example.ipynb |
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# cd
# !pip install --user jupyterplot #currently disp... | CategoryRoad_Jetracer_2_Jetbot/trt_jetracer_categoryModel_for_jetbot_with_stop.ipynb |
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# ### Reading data from a social network survey
# Let... | Lecture 3/.ipynb_checkpoints/Exercise_SocialNetworkSoln-checkpoint.ipynb |
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# This notebook was prepared by [<NAME>](https://githu... | graphs_trees/bst_validate/bst_validate_challenge.ipynb |
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# # Inverse problems
from IPython.core.display import... | 05-inverse-problems.ipynb |
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# # IPython notebook for data analysis diss
# ## Impo... | main_analysis.ipynb |
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# ## This project has two parts.
#
# In the first par... | 8_Outliers_Mini-Project.ipynb |
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import os
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import matplotlib.py... | result_analysis/synthetic_analysis.ipynb |
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# # Setting Up the Sample Specific Environment
#
# In ... | utilities/video-analysis/notebooks/customvision/setup_specific_environment.ipynb |
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import tensorflow as tf
from cnn_train import cnn_... | AI/exp/04_Captcha/draft/cnn_test.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Requirements.ipynb |
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# # The Basics
# NumPy’s main object is the homogeneou... | Week04/Numpy.ipynb |
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# # Get country icons
import requests
from bs4 import... | notebooks/archive/SCRIPTS/countries/country_metadata.ipynb |