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# + [markdown] slideshow={... | 2A/S8/UE Apprentissage Machine et optimisation/Optimisation 2/TP1/tp1_optimisation.ipynb |
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# # Integrating external data from a CSV <img align="r... | Frequently_used_code/External_data_CSVs.ipynb |
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# Names
names = ["John", "Donald"]
# colours
colours ... | Sound_constants.ipynb |
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import matplotlib.pyplot as plt
import... | .ipynb_checkpoints/colorSpace-checkpoint.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | nb/watermeter_clean.ipynb |
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# # Content Based Recommendation (CBR)
#
# When we use... | notebooks/reco-tut-asr-99-03-content-based-recommendations.ipynb |
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# My attempt at the [7-Segment Display](https://en.wik... | notebooks/2019-07-10-Seven-Segment-Display-Coding-Puzzle.ipynb |
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# + [markdown] id="vM6tkrjHlBs_" colab_type="text"
# # Mapping GIS Data in Py... | gis/gis_activity.ipynb |
# -*- coding: utf-8 -*-
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# # Chapter 5 - Fixes, Estimates and Tra... | eg/Yachts and Navigation - Chapter 5 - Fixes, Estimates and Transits.ipynb |
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# # Producing Quick and Easy Plots of Topology within ... | examples/notebooks/io/quick_plotting_networks.ipynb |
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# # Exercício 1.0 - Raciocínio Lógico
# +... | 01-Fundamentos-Programacao-DS/Scripts/Mod-01/aula_01/exercicios_resolucao.ipynb |
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# # Diving Into Bayesian Analysis
# *<NAME>*
#
# In th... | Chapter01/BayesianAnalysis.ipynb |
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# + colab={"base_uri": "https://localhost:8080/", "hei... | Top10.ipynb |
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from gumbel_sigmoid_softmax import gumbel_softmax
im... | demo_gumbel_softmax.ipynb |
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# ### Solves the 1D Advection equation with periodic b... | hyperbolic1D.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | IIIT_project1.ipynb |
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from keras.datasets import mnist
#defining traini... | DeepLearningWithPython/04_MnistClassification/MnistClassification.ipynb |
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# This notebook was prepared by [<NAME>](https://githu... | bit_manipulation/print_binary/print_binary_challenge.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | CoronaSimLessM&Recovery.ipynb |
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// %env
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ETL_CONF_... | emr-on-eks/green_taxi_load.ipynb |
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# # From Word Embeddings To Document Distances详解
# > 《... | _notebooks/2020-06-11-From-Word-Embeddings-To-Document-Distances.ipynb |
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# # 频率分析 (1):从 fchk 文件得到分子频率与简正模式
# > 创建时间:2019-10-04... | source/QC_Notes/Freq_Series/freq_1.ipynb |
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from mxnet import nd
def dropout(X, drop_probabil... | _12_dropout-scratch.ipynb |
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# Successful run of SpatialDE, results in data fol... | notebooks/SpatialDEwStabilize.ipynb |
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# ## Accessing NLCD data on Azure
#
# The [National La... | data/nlcd.ipynb |
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import sys
import cv2
from PyQt5 import QtCore, Qt... | face_indentation.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | Prelim_Exam.ipynb |
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import sys
import argparse
from yolo import YOL... | inference.ipynb |
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import pickle
import numpy as np
import collections
im... | analysis/Fitting.ipynb |
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import pandas as pd
from postgresif import PostgresIF
... | pandas/sql-pandas/sql-pandas.ipynb |
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# + [markdown] id="auzlUi26MZ8M"
# # Dataset download
# In this section the d... | 2-InceptionV3.ipynb |
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# ## mmdleaf
# Segment a leaf from the background
# #... | notebooks/dleaf.ipynb |
# -*- coding: utf-8 -*-
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Rooms = Vector{Vector{... | 23/Day 23 - Amphipod.ipynb |
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# # Self study 1
#
# In this self study you should wor... | ML_Lecture5_SelfStudy5/Self study 1 - NN from scratch-GD _without_data_support.ipynb |
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# + [markdown] id="riE4dK9DDJ7o"
# ## Gradient Descent
# + id="jlq5M8is1Lcv"... | ML_basic/Gradient Descent.ipynb |
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# + [markdown] id="view-in-github" colab_type="... | test_lesson_1.ipynb |
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import pandas as pd
import numpy as np
import seaborn ... | plots/codes/experiment3.ipynb |
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# ## Dependencies
# + _kg_hide-input=true
import json... | Model backlog/Train/55-jigsaw-1fold-xlm-roberta-large-step-radam-lower.ipynb |
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# default_exp models.lr
# -
# # LR
# > A pytorch implementation of Logis... | nbs/models/models.lr.ipynb |
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# # Kitchen Confusion Matrix
# ## A game about classif... | week-5/kitchen-confusion-matrix.ipynb |
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# Import all the required packages for our code
import itertools
... | deadline1/notebook.ipynb |
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# %matplotlib inline
from PIL import Image
import ma... | week05/prep_lecture08.ipynb |
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# ## K-Nearest Neighbors (KNN)
# > In KNN, K is the nu... | KNN/KNN.ipynb |
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import torch
# ### Inputs
x = torch.tensor([2, 3, 4.... | 01_PyTorch_Basics/03_Back_Propagation/Backward Propagation.ipynb |
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# # QUANTUM PHASE ESTIMATION
# This tutorial provides a ... | advanced_circuits_algorithms/QPE/QPE.ipynb |
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import pandas as pd
from pandas import DataFrame
i... | .ipynb_checkpoints/Stock Data Feature Engineering-checkpoint.ipynb |
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# ## week03: Логистическая регрессия и анализ изображе... | week0_03_logistic/week03_extra_image_classifier.ipynb |
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from IPython.core.display import display, HTML
display... | helper_functions.ipynb |
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# # Example usage
# In this example, we'l... | examples/example_usage.ipynb |
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# # Excercises Electric Machinery Fundamentals
# ## Ch... | Chapman/Ch3-Problem_3-10.ipynb |
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# + [markdown] id="DjGyEGkLLFxP" colab_type="text"
# ## A/B Testing with Mach... | kernels/.ipynb_checkpoints/ML_testing-checkpoint.ipynb |
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# Implement a model per day. Log:
# * 6-15 Adaboost
# ... | codes/mlmodels/practice_makes_perfect.ipynb |
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// # Introduction to F# #
//
// F# is an... | NotebookExamples/fsharp/Introduction to F#.ipynb |
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from azureml.core import ... | examples/explainability/train-deploy-explainer.ipynb |
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import numpy as np
import pandas as pd
import matplotl... | src/Target_classification/driving_1RX_only.ipynb |
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# # Multicontact Data in HiGlass
#
# This notebook use... | notebooks/mc-higlass-new.ipynb |
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# # Master Data Science for Business - Data Science Co... | Day2/Notebook 3 - TripAdvisor_sol.ipynb |
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import pandas as pd
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# 说明:
# 设计循环队列的实现。循环队列是一种线性数据结构,其中的操... | Queue/622. Design Circular Queue.ipynb |
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# # Model selection
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import tensorflow as tf
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# # Fine tuning convolutional neural networks
# Use th... | CNN_testing_practice.ipynb |
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import Ruk_Reader
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# + deletable=true editable=true
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# Import all libraries needed for the tutorial
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# # Tutorial about drift analysis and correction
# La... | docs/tutorials/notebooks/Analysis_Drift.ipynb |
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import pandas as pd
# 2 main datatypes
series = pd.Se... | introduction-to-pandas.ipynb |
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# %matplotlib inline
# # モデルの保存と読み込み
#
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# ____
# # Nanodegree Engenheiro de Machine Learning
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# # Solutions to the Julia Set Exercises
#
# 1: Write... | book/Solutions/Solutions to the Julia Set Exercises.ipynb |
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# ### 111. Minimum Depth of Binary Tree
# #### Conten... | 101-150/111.minimum-depth-of-binary-tree.ipynb |
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# # Anomaly Detection on MNIST
#
# This notebook shows... | notebooks/3-Autoencoders/8-Anomaly-Detection.ipynb |
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# # Offered Pipeline can be usefull by <NAME>
# # Gen... | .ipynb_checkpoints/practical_pipeline_by_marios_michailidis-checkpoint.ipynb |
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# Copyright 2021 Google LLC
# Use of this source code is governed by an M... | notebooks/figures/chapter22_figures.ipynb |
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# # 5-Fold Cross Validation
# import libraries
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# # Predicting wine quality using machine learning tec... | wine-ml/wine_quality.ipynb |
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# # RTT Scoring
# <div>
# <p style="fl... | notebooks/archive/__RTT_Scoring.ipynb |