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# # Train your own skip-thoughts model
#
# This notebo... | src/examples/train-skip-thoughts.ipynb |
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# # 02 - Introduction to Python for Data Analysis
#
# ... | notebooks/02-IntroPython.ipynb |
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# # Network Concatenation
#
# The results... | docs/source/notebooks/04-Network_concatenation.ipynb |
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from datascience import *
import numpy as np
# %m... | lec/lec10.ipynb |
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# # Using EKF tweaks with Sigma Point Kalman Filters
#... | doc/src/UsingEKFTricksWithSPKF.ipynb |
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# + [markdown] colab_type="text" id="Ndo4ERqnwQOU"
# ##### Copyright 2018 The... | site/en/r2/tutorials/generative/cvae.ipynb |
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# + [markdown] id="bFqstK5Hegki"
# # **Step 1: Loading modules**
# Before we ... | 1. Scraping financial data on Yahoo! Finance/1.2 Web_Scraping_with_Python_Completed_Project.ipynb |
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# from http://iamtrask.github.io/2015/07/12/basic-... | notebooks/mpc-playground/basic-python-network.ipynb |
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#Remember to load another conda environment with pyEMM... | notebook/SpectraloASIS-Parallel.ipynb |
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# Copyright (c) Microsoft Corporation. All rights r... | lab01.1_AD_Introduction/lab01.1b_AD_data_preparation_for_time_series.ipynb |
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# # Stochastic RS... | Python_Stock/Technical_Indicators/Stochastic_RSI.ipynb |
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# # Filter maximisation
#
# In this notebook we will d... | course_2.0/09_debugging_exploring_extra.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} id="... | data_mining/lpps/scripts/itti/scrapes_itti_asus.ipynb |
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# + [markdown] id="64aq4ZKbZPdW" colab_type="text"
# # Tutorial: Ground State... | Tutorials/1DTFIM/Tutorial_1DTFIM.ipynb |
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import lightgbm as lgb
import pandas as pd
import catb... | catboost/benchmarks/model_evaluation_speed/model_evaluation_benchmark.ipynb |
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import matplotlib.pyplot as plt
import matplotlib.... | mechanistic/orientation_map_kmeans.ipynb |
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import os
import tqdm
import pandas as pd
import ... | notebooks/CreateDataset.ipynb |
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# ## Import Libraries
from image_preprocessing import... | model-1.ipynb |
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from IPython.display import Image
# # Smart Reply: Au... | papers/Google_SmartReply.ipynb |
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import os
from utils import load_data_to_mem, aug... | Overview_augmented_images.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | SHL_split_and_batch.ipynb |
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# ### Objective
#
# Predict the sales price for each h... | Housing-Prices/fourth_submission-Machine-Learning-Competition-Practice-Iowa-Home-Prices.ipynb |
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# # Chapter 4. Linear Models
# +
import pandas as pd
... | notebooks/04_linear_models.ipynb |
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# ## Practice Followings<br>실습 예
#
#
# ### Opening a ... | 01.bash-practice.ipynb |
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# %matplotlib inline
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import numpy as np
import ma... | notebooks/active_learning/Understanding-GP.ipynb |
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# ## KMeans Clustering - CB4_64... | examples/clustering/KMeans_CB4_64_16D_STK_1.ipynb |
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# # Special String Again
#
# <br>
#
# ![image](https:/... | Interview Preparation Kit/5. String Manipulation/Special String Again.ipynb |
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# + colab={"base_uri": "https://localhost:8080/"} exec... | PennyLane/Data Reuploading Classifier/Q Conv + DRC Keras MNIST (best)-Copy1.ipynb |
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# # Sentiment Analysis Project with No RNNs
import os... | src/Sentiment Analysis Project With No RNNs.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | assignment_no_2_day_6.ipynb |
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# <a id='home'></a>
# # Investigation of Twitter archi... | Project 4 - Wrangle and Analyze Data/wrangle_act.ipynb |
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# # Unsupervised Anomaly Detection
#
# We continue wit... | notebooks/unsupervised_anomalies.ipynb |
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# + [markdown] slideshow={"slide_type": "skip"}
# # To... | software_engineering/5_Test/notebook.ipynb |
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# %matplotlib inline
import matplotlib.pyplot as plt
i... | notebooks/12.Case_Study-SMS_Spam_Detection.ipynb |
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# + [markdown] id="Ih7gcr9o37cL" colab_type="text"
# # variabel
# + id="4HLj... | mod_02_python_intro/mod_02_02.ipynb |
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# # Boston Housing Classifica... | exercises/boston_housing_classification_svm_evaluation.ipynb |
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# cd C:\Users\mmatousek\GIT\recsys
# %load_ext autore... | notebooks/exploration/0.1_spotlight2pytorch.ipynb |
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from tensorflow.keras.preprocessing.sequence import pa... | src/DataGenerator.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# Set... | notebooks/1 - Setting Up a Twitter Bot in 5 Easy Steps.ipynb |
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# + [markdown] colab_type="text" id="0-53Xmr3wEu2"
# L... | coderbyte/20191215_2/Letter Changes.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | Tweet_Emotion_Recognition_Learner.ipynb |
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# + [markdown] id="v4OdNCeP18-F"
# # Imports
# + id="Eo-Pfm2BApZU" colab={"b... | Competition-Solutions/Audio/GIZ NLP Agricultural Keyword Spotter/Solution 2/resnext101/inference.ipynb |
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# + [markdown] id="HO67bSDTFCrU"
# # Mask R-CNN training code for tvai2021
#
... | samples/custom/tvai-mask-rcnn-training.ipynb |
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import pandas as pd
import numpy as np
df = pd.read_c... | notebooks/use_employements_features.ipynb |
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# # Optimizer tweaks
# +
# %load_ext autoreload
# %au... | dev_course/dl2/09_optimizers.ipynb |
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import pandas as pd
import numpy as np
waitdata_raw = ... | analysis/Monica/milestone1.ipynb/analysis.monica.milestone1.ipynb |
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# + [markdown] id="VEYe67K6E6j0"
# ## **Grasp Candidat... | exercises/clutter/grasp_candidate.ipynb |
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# # UT2000 Beacon Summary
# For the MADS framework pap... | notebooks/archive/2.0.1-hef-ut2000-beacon-summary.ipynb |
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# # Feature Importance
# !pip install lightgbm
BASE_... | src/trec-dl-21-ltr/src/main/ipynb/feature-importance.ipynb |
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import numpy as np
import cv2 as cv
import matplotlib.... | opencv/Image Processing in OpenCV/Image Segmentation with Watershed Algorithm.ipynb |
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# # Getting started with the Data API
# ### **Let's s... | jupyter-notebooks/data-api-tutorials/search_and_download_quickstart.ipynb |
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# # Processing data example using **Rasterio**, **ge... | Sentinel2_processing-2.ipynb |
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# *Lot of materials in today's workshop (including tex... | workshop9/workshop9_unsupervised_learning.ipynb |
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import requests
from bs4 import BeautifulSoup
im... | scrap_processing.ipynb |
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# <img style="float: center;" src="images/CI_horizonta... | class_notebooks/2_1_Databases.ipynb |
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# # Chapter 2 - Session 1
# # Matrix (Images) in Pytho... | Chapter 2/C2S1 - Matrix (Images) in Python.ipynb |
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# # Here is my oversimplified and rather naive unde... | Converting_text_to_features/Word_Embeddings.ipynb |
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# # Homewo... | Homework3.ipynb |
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# # Mask R-CNN for DeepScore
# For our own dataset De... | deepscore/inspect_deepscore_data.ipynb |
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# # Example Notebook
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# This notebook demonstrates ho... | notebooks/example_notebook.ipynb |
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# + [markdown] id="rzmBy3Bf19vv"
# * Source : https://taeguu.tistory.com/27
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# # Machine Learning Engineer Nanodegree
# ## ... | student_intervention.ipynb |
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# # Loding a Dataset
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... | authenticating.ipynb |
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# https://www.algoexpert.io/questions/Bi... | notebooks/binary-search-array.ipynb |
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# # Image-Basic-Recognition_static
# O Sistema deve i... | lessons/7.4.2 - Camera-Basic-Recognition_scanner_Object.ipynb |
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# # Chapter 2 - Phase Plane Analysis
#
# Phase plane a... | Chapter 2 - Phase Plane Analysis.ipynb |
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# # Analysis of Fitting
import tellurium as te
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# ### Starting from scratch on Covid-19 data analysis
... | notebooks/covidz-01.2020-04-21.ipynb |
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# # Developing an AI application
#
# Going forward, AI... | Image Classifier Project.ipynb |
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# # SIF TO Julia
#
# **Goal:** Obtaining the CUTEs... | Unconstrained-NonLinear-TestSuite-Notes.ipynb |
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# + colab={} colab_type="code" id="-rZvPT6cX1eE"
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# + [markdown] deletable=false editable=false nbgrader... | Week 00/SLU00 - Jupyter Notebook/Exercise notebook.ipynb |
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# %matplotlib inline
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sys.path.append("... | examples/0. Dataset Label Review.ipynb |
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# # 演習5 - VQE(変分量子固有値ソルバー)
# ***
#
# ## 歴史的背景
#
#
# 過去... | solutions by participants/ex5/ex5-ja-SoyaSaijo-3cnot-2.339013mHa-16params.ipynb |
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# %load_ext autoreload
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# <a href="https://cognitiveclass.ai/">
# ... | Python (Expressions, Types, Variables ).ipynb |
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# ### Se pide, usando la regresión lineal de sklearn:
... | Bloque 3 - Machine Learning/01_Supervisado/1-Linear Regression/ejercicios/01_Con_altura.ipynb |
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# + [markdown] id="5sQVmss-VqC_" colab_type="text"
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# # VT Graphs in Jupyter Notebook
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# In thi... | docs/notebooks/VTLookupV3.ipynb |
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using LCIO
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# ## Class pada Python
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# !pip install pretrainedmodels
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# # Regularized Regression
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import numpy as np
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# # Ex04 - Filtragem em frequência
# Neste exercício ... | 1S2020/EA979A_Ex04_FiltragemFrequencia.ipynb |
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# # Testing
# + [markdown] tags=[]
# Think Bayes, Sec... | notebooks/chap10.ipynb |