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# ## Introduction
#
# This notebook creates a correlat... | ai-columbiax-ml-w6-k-class-bayes-classifier.ipynb |
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# # Tutorial on Logic gates
#
# In quantum computi... | examples/5. Logic Gates (Tutorial).ipynb |
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import ipywidgets as widgets
recipe_ingredients = dic... | widget_example.ipynb |
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# # Exporting and Importing MLRun Functions
# nuclio:... | examples/mlrun_export_import.ipynb |
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# # Optimizing the hyperparam... | BlogPosts/Hyperparameter_tuning_comparison/Hyperparameter_tuning_comparison_post.ipynb |
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# + [markdown] nbsphinx="hidden"
# # The Discrete-Time... | discrete_time_fourier_transform/definition.ipynb |
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credit_card_train = pd.read_csv("./raw/credit_card_bal... | hj/02_preprocessing__credit_card_v2.ipynb |
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import numpy as np
# # Problem 1
#
# Create a... | Ex 8/ex08.ipynb |
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# # Microsoft Face Api Integration through Python
# ... | Microsoft Face Api - Python.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | PredictSeasons_SVM.ipynb |
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# # Calibrating Pastas models
# *<NAME>, University of... | examples/notebooks/09_calibration_options.ipynb |
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from IPython.display import HTML
HTML('''... | InteriorPoint.ipynb |
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# # ECG-Pytorch-Ver2.0
#
# @create 2021-09... | .ipynb_checkpoints/ECG-Pytorch-Ver2.0-Q-checkpoint.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | KNN_Classification_Demo.ipynb |
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# + [markdown] id="37puETfgRzzg" colab_type="text"
# # Data Preprocessing Too... | Dataset/Udemy_Machine_Learning_A_Z/Part 1 - Data Preprocessing/Section 2 -------------------- Part 1 - Data Preprocessing --------------------/Python/data_preprocessing_tools.ipynb |
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# # Load Data
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# %load_ext autoreload
# %autoreloa... | Network Analysis/La Liga Centrality.ipynb |
# -*- coding: utf-8 -*-
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# # **Comandos básicos**
# Para realiza... | Sesion2_Comandos_Basicos/Comandosbasicos.ipynb |
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# # Graph concepts and state machine
# A graph is... | docs/serving/realtime-pipelines.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Model_Performance_Evaluations0.ipynb |
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import numpy as np
import laser_hockey_env as lh
impor... | Game_Start.ipynb |
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# # merge_sim© Tutorial
# * This tutorial shows h... | code/tutorial.ipynb |
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i... | test.ipynb |
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imp... | Assignments/DataClean.ipynb |
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# ## Plotting very large datasets meaningfully, using ... | examples/topics/nyc_taxi.ipynb |
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# + [markdown] id="6jySCx7r-D68"
# # Installs
#
# If n... | dream_net.ipynb |
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import torch
import torch.n... | source/gan/main.ipynb |
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# ### Cab-Driver Agent
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# Importing libraries
impo... | DQN_Agent_Arch1.ipynb |
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# # Functions for retrieving data, making basic calcul... | portfolio_analysis.ipynb |
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# https://github.com/tensorflow/docs/blob/master/site/... | models_deep_learning/tf1/2.4 automatic differentiation.ipynb |
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# # Inference plots - Pairwise scatterplots
#
# This e... | examples/plot-mcmc-pairwise-scatterplots.ipynb |
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#      
#    &... | ai/DeepStream/English/python/jupyter_notebook/Introduction_to_Multi-DNN_pipeline.ipynb |
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import dask.dataframe as dd
import... | EDA.ipynb |
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# # Exceptions
# An [exception](https://docs.python.or... | 10-exceptions.ipynb |
# -*- coding: utf-8 -*-
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# + dc={"key": "4"} deletable=false editable=fal... | R Projects/R Importing and Cleaning Data/notebook.ipynb |
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# # 76 Cereal Brands, a Head-to-Head Comparison
#
# ... | Cereals.ipynb |
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# # 0.0 - Retrieve Dataset
#
# **Actions**... | notebooks/0.0-rimij405-retrieve-dataset.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="5M7DQ-kO90os" outputId=... | notebooks/text_generator_v2.ipynb |
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# # Набор заданий №1
# ## Выполнил студент группы БВТ1... | .ipynb_checkpoints/Tasks1_BVT1904_Skorodumov-checkpoint.ipynb |
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#import cv2
import os
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# + [markdown] pycharm={"name": "#%% md\n"}
# # Advent... | src/day03/day03.ipynb |
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import json
# #### JSON String to Dict
values = """
... | preprocessing/JSON.ipynb |
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# Copyright (c) Microsoft... | examples/interpretation/notebooks/F3_block_training_and_evaluation_local.ipynb |
(* -*- coding: utf-8 -*-
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(* na... | Dictionnaires - Tables de hachage.ipynb |
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import math
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from it... | 6_GaussianBeta_Dropout_01.ipynb |
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# # Parts of Speech Assessment - Solutions
# For this... | 004-POS-Assessment-CGIL.ipynb |
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# # Sampling DataFrames
import numpy as np
import pan... | Section 4/4.4_Sampling.ipynb |
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lst =[1,1,5,2,8,7,9,6]
sub_lst =[1,1,5]
def is_sub_l... | Day 5 Assignment.ipynb |
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# # Train an Agent usin... | examples/1_train_bc.ipynb |
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# # NMF and SVD
#
# The... | projects/00 refresher/00_nmf.ipynb |
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# Stock Price Analyzer using ML and BigData
# ==
#
# ... | StockPriceAnalyzer_Main.ipynb |
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# # AutoML pipeline preset
# ## Initia... | docs/tutorials/tutor_2.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | models/XGBoost3__AirTemp_target.ipynb |
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import pandas as pd
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import matplotl... | Data analysis Internship/Data Quality assessment(Step-1)/Customer address/customeradd.ipynb |
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movies_metadata = pd.read_csv('da... | Movielens Extract.ipynb |
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# COMP 21... | labs/lab2.ipynb |
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import torch
import torch.nn as nn
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# # Initialization
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from datetime import datetime
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import os
import pandas as pd
import scholarly
os.chdi... | notebooks/json_file_processing_population_density.ipynb |
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import datetime
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import pandas as pd... | Kaggle/Sberbank Russian Housing Market/naive_modeling_xgb_clean_data.ipynb |
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# ## Configurations for Colab
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import sys
IN_COLAB... | 08.rainbow.ipynb |
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# Зависимости
import pandas as pd
import numpy as ... | 2021 Весенний семестр/Практическое задание 3/Червинский - задание 10.ipynb |
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import random
class Pet():
def __init__(self,... | 01_Workshop-master/Chapter05/Exercise78/Exercise78.ipynb |
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# # Importing Libraries
import numpy as np
import pan... | Police shootings-Kaggle.ipynb |
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# CWPK \#42: Other Structural Considerations
# =======... | cwpk-42-other-structural-considerations.ipynb |
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# # Exercise 1 b
# ## 3 Nearest Neighbor Classificatio... | ex01b/nearest-neighbor.ipynb |
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import pickle
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i... | model_for_MSFT_dataset.ipynb |
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# # ERDDAP Frequent Tools c... | EcoFOCI_Moorings/ERRDAP_DailyAverages.ipynb |
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# # Train a model with SUN Rgb Data
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import os
i... | samples/sun/train_model_d.ipynb |
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# name: python374jvsc74a57bd0b080221bbfcc22139d6f403b5aa156ef25a7f222... | Projects/Flotation/float.ipynb |
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import numpy as np
import pandas as pd
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# let's create a ... | Chapter07/Recipe3-Creating-representations-of-week-day.ipynb |
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# %matplotlib notebook
import matplotlib
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... | scripts/remote/.ipynb_checkpoints/RunER-checkpoint.ipynb |
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# %run ../notebook_preamble.ipy
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import pyproj
import geopandas as gpd
import shapely
import os
from datetime import datetime
from zipfile... | ds/notebooks/dev/11_gr_defra_air_pollution.ipynb |
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# Retrieve a random joke about programming from the _O... | lesson02/exercises/api_exercise.ipynb |
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... | notebooks/HMC_mixture.ipynb |
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# # Beginning Analysis of NHTSA Data
import numpy as ... | DataDiscovery_1.ipynb |
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# + [markdown] colab_type="text" id="q9aaxiSJg60h"
# #... | Kata Intro to AI/intro-to-ml-tensorflow-master/lessons/intro-to-tensorflow/Part_1_Introduction_to_Neural_Networks_with_TensorFlow_(Solution).ipynb |
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# %matplotlib inline
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# # Problem 2: Logistic Regression and LDA
# You are ... | M5 Pridictive Modeling/M5 W4 Project/M5 Predictive Modeling W4 Logistic Regression and LDA Project - Shreyansh.ipynb |
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# # Notebook template
# - This template is inspired by... | C1M1_Assignment.ipynb |
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# + pycharm={"name": "#%%\n"}
import panda... | benchmarks/earthquake/latest/example-log/analyze.ipynb |
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# #Handwritten Digit Indentification
#
# This project ... | index.ipynb |
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# # Three Quadratic Functions
#
# Copyright (C) 2020 <... | demos/nonlinear/Three quadratic functions.ipynb |
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# + [markdown] button=false new_sheet=false run_contro... | docs/beta/notebooks/Parser.ipynb |
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### https://keras.io/ko/applications/
# # !pip un... | pretrained_model/VGG16.ipynb |
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# # Тематическая классификация длинных тек... | task1_20newsgroups.ipynb |
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# ## Whatsapp Data Processing
import datetime
import ... | Whatsapp Data Processing.ipynb |
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from keras.preprocessing import sequence
from kera... | examples/text_interpretability/cnn_sentiment_imdb.ipynb |
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# # Rich Document Vectors
#
# The vectorizers library ... | doc/document_vectorization.ipynb |
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# # Code from previous sessions.
#
# This should look... | 02-training-and-regularization-tactics/01-activations.ipynb |
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# # Calculating Feature Log-Ratios Directly using Qarc... | example_notebooks/qarcoal/qarcoal_example.ipynb |
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from torch_geomet... | Validation_Docking/Docking_CASF2016_CoreSet.ipynb |
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# %load_ext autoreload
# %autoreload 2
import date... | notebooks/Lyna/FilterSam1ByReadNamesFromSam2.ipynb |
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# Import the dependencies.
import pandas as pd
impor... | Cleanup/WeatherPy.ipynb |
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# # Exercises
#
# This notebook... | tests/no_inline_exercises/ipynb/exercises.ipynb |
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# ### Common spadefoot custom parsing
# - This dataset... | notebooks/01.0-custom-parsing/10.0-common-spadefoot-custom-parsing.ipynb |
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# ## Preprocessing
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# Import our dependencies
from... | Optimization_attempt_2.ipynb |