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# # 09 Strain Gage
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# This is one of the most commonl... | Lectures/09_StrainGage.ipynb |
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# <table class="ee-notebook-buttons" align="left">
# ... | Algorithms/landsat_radiance.ipynb |
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# Copyright 2020 NVIDIA Corporation. All Rights Re... | notebooks/ssd-object-detection-demo.ipynb |
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# **Run the following two cells before you begin.**
#... | Mini-Project-2/Project 4/Fitting_a_Logistic_Regression_Model.ipynb |
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# + [markdown] colab_type="text" id="1Pi_B2cvdBiW"
# ##### Copyright 2019 The... | tf_agents/colabs/8_networks_tutorial.ipynb |
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# # Custom Types
#
# Often, the behavior for a field n... | docs/api/custom-types.ipynb |
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# # Part 1: Data Ingestion
#
#... | docs/feature-store/end-to-end-demo/01-ingest-datasources.ipynb |
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# ![Callysto.ca Banner](https://github.com/callysto/cu... | _build/html/_sources/curriculum-notebooks/Mathematics/Percentage/percentage.ipynb |
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# <p align="center">
# <img src="https://github.co... | PythonDataBasics_ParametricDistributions.ipynb |
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# %matplotlib inline
# %config InlineBackend.figur... | Lesson 5: Introduction to PyTorch/07 - Loading Image Data.ipynb |
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# Probabilistic Programming and Bayesian M... | Chapter1_Introduction/Ch1_Introduction_PyMC2.ipynb |
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#Author: <NAME>
#Purpose: This is a program tailo... | BiNew_RF.ipynb |
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# ### This is Example 4.3. Gambler’s Problem from Sutt... | DP/Gamblers Problem Solution.ipynb |
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# ## PyTorch Tutorial
#
# IFT6135 – Representation Lea... | pytorch/1. The Torch Tensor Library and Basic Operations.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# <im... | notebooks/hsip442/hsip442_algorithms_lecture-Copy1.ipynb |
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# # Deep Q-Network implementation.
#
# This homework shamelessly demands you to implement a DQN - an approximate q-learning algorithm with exp... | week04_approx_rl/homework_pytorch_debug.ipynb |
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# ![Callysto.ca Banner](https://github.com/callysto/cu... | _sources/curriculum-notebooks/Science/ProjectileMotion/projectile-motion.ipynb |
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# load and summarize the dataset
from sklearn.datasets... | Select Features for Numerical Output.ipynb |
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# Dated: 30-3-18
#
# CNN Tutorial with adam and using ... | CNN_MNIST-Part-1.ipynb |
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# # Underactuated cartpole control with iLQR, MPPI
# T... | examples/cartpole/cartpole.ipynb |
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include("lin_int2.jl")
println(readstring(`cmd /c... | A Simple Optimal Growth Model Interpolation2.ipynb |
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# + [markdown] id="R3En9MVqilRY"
# # Train on multiple GPUs
#
# In this noteb... | guide/train_on_multiple_gpus.ipynb |
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# # Simple KubeFlow Pipeline
#
# Lightweight python co... | kubeflow/notebooks/08_Simple_KubeFlow_ML_Pipeline.ipynb |
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# # Hospital Readmissions Data Analysis and Recommenda... | Statistics_Exercises/sliderule_dsi_inferential_statistics_exercise_3.ipynb |
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# title: "Feedforward Neural Networks For Regression"
# author: "<NAME>"
# date: 2017-12-20T11:53:49-07:00
# description: "How to train a feed-forward neural network for regression in Python."
# type: technical_note
# draft: false
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# ... | docs/deep_learning/keras/feedforward_neural_network_for_regression.ipynb |
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# # Indexes
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# Today we're going to be talking about ... | modern_3_indexes.ipynb |
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bres_trend_micro,bres_trend_agg = [make_trend(bres_proc,sector_var=v) for v in ['sector','sector_aggregated']]
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fig,ax = plt.subplots()
... | notebooks/dev/scraps.ipynb |
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# + [markdown] pycharm={}
# # Classification with Deli... | notebooks/classification_examples/sklearn.ipynb |
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# # Creating a Filter, Edge Detection
# ### Import re... | convolutional-neural-networks/conv-visualization/custom_filters.ipynb |
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# # Chapter 2: Multi-armed Bandits Solutions
# ## 1. ... | chap2-solutions.ipynb |
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# + [markdown] id="ElXOa7R7g37i" colab_type="text"
# # Tutorial Part 5: Putti... | examples/tutorials/05_Putting_Multitask_Learning_to_Work.ipynb |
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# # Assignment 5
# - toc: true
# - badges: true
# - co... | _notebooks/2021-11-13-Assignment5-Yili Lin.ipynb |
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import numpy as np
import pandas as pd
import matp... | 2020 Осенний семестр/Практическое задание 5/Маргарян - практика 5.ipynb |
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# # Building Simple Neural Networks
#
# In this sectio... | 01-intro-to-deep-learning/02-building-simple-neural-networks.ipynb |
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# # Creating datetimes by hand
# Often you create date... | working-with-dates-and-times-in-python/2. Combining Dates and Times/notebook_section_2.ipynb |
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#Here we will Improve model performance
# # Importin... | 7 Model Selection Boosting/Model Selection/ Grid Search .ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
#... | Tensorflow_fundamentals/callbacks.ipynb |
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# <img src="images/MCG.png" style="width: 100px">
#
#
... | Gaussian Bayesian Networks (GBNs).ipynb |
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import keras
keras.__version__
# # 5.1 - Intr... | Keras/deep-learning-Keras/.ipynb_checkpoints/5.1-introduction-to-convnets-checkpoint.ipynb |
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# # FishboneMoncriefID: An Einstein Toolkit Initial Da... | Tutorial-ETK_thorn-FishboneMoncriefID.ipynb |
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# # Noteb... | main.ipynb |
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# # Decoupling Logic and Execution
#
# In the last sec... | tutorials/beginner/decoupling_logic_and_execution.ipynb |
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# + [markdown] deletable=true editable=true
# # Solvin... | search.ipynb |
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# # Programming Exercise 4: Neural Networks Learning
... | jupyter-notebooks/ml-coursera-python-assignments/Exercise4/exercise4.ipynb |
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# <center>
# <img src="../../img/ods_stickers.jpg">
# ... | jupyter_russian/topic07_unsupervised/topic7_bonus_PCA_toy_example.ipynb |
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# # NLP 2 : Neural Embeddings, Text Classi... | S2/RITAL/TAL/TME/TME2/Dan.ipynb |
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# # Content personalization
# ## Without context
# This... | docs/examples/content-personalization.ipynb |
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# # Convolutional Neural Network (CNN)
# loading libr... | apps/handwritten-digits-recognizer/notebooks/cnn.ipynb |
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# [FProfile.jl](https://github... | Manual.ipynb |
# # In this notebook....
#
# Using HypnosPy, we first classified sleep using the most common heuristic algorithms, such as Cole-Kripke, Oakley, Sadeh, Sazonov and the Scripps Clinic algorithm.
#
# Once sleep was classified, we derived the well-established sleep metrics, such as arousal, awakening, sleep efficiency, tot... | mdpi_sensors/hypnospy_sleepmetrics_by_sleepwakealgs.ipynb |
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# ## Forecasting, updating datasets, and the "news"
#
... | examples/notebooks/statespace_news.ipynb |
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# # Introduzione a Tensorflow
#
# TensorFl... | tensorflow.ipynb |
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# # Notebook to try to get the CPI (Consumer Price Index) for... | notebooks/002-mt-getting-the-cpi-from-the-world-bank.ipynb |
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import random
import numpy as np
from math import erfc... | brwnn-raise_res.ipynb |
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# # Assignment 2 - Bacterial Bomb
# +
# Packages
# %... | A2.ipynb |
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# # Convolutional N... | demo.ipynb |
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# <img src="../../images/qiskit-heading.gif" alt="Note... | community/games/quantum_counterfeit_coin_problem.ipynb |
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# # Practical Session 2: Classification algorithms
#
#... | DSPNP_practical2/DSPNP_notebook2.ipynb |
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# # Streamlines tutorial
# In this tutorial you will l... | Examples/notebooks/Streamlines.ipynb |
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# ### Installation
# - `pip install eleanor` ([eleanor... | notebooks/online_tess_science_eleanor.ipynb |
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from IPython.display import HTML
HTML('''... | hackathons/hackathon2/index.ipynb |
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# # jupyter notebook生成PDF文件采用LaTeX编译方式，须先行安装Tex软件。（Lin... | docs/IMPOART_NOTICE_FOR_CHINESE_PDF_DOCUMENT.ipynb |
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# <a href="https://colab.research.google.co... | t81_558_class_03_5_weights.ipynb |
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import numpy as np
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fro... | matlab/udemy/Vectors/linalg_vectors.ipynb |
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# ## The Battle of the Neighborhoods - Week 1
# ###... | The Battle of Neighborhoods-Week1/The Battle of Neighborhoods-Week1-Part-1.ipynb |
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# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... | CNN.ipynb |
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# %matplotlib i... | echostatenetwork/ReservoirNetwork.ipynb |
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# # Implementation
# This section shows how the linea... | content/c2/code.ipynb |
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### ESOL predictor: GCNN, random train/validate/te... | models/GroundTruthEsolModel.ipynb |
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# # An example notebook
# A [Jupyter notebooks](http:... | example.ipynb |
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from scipy.spatial.distance import cdist
from sklearn.cluster import KMeans
from sklearn.decomposition import PCA
import pandas as pd
impo... | notebooks/Day03_EDA.ipynb |
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# + [markdown] slideshow={"slide_type": "slide"}
# # B... | Inference2.ipynb |
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# # SciPy Optimize Module
#
#
# ## Module Contents
#
#... | Optimize_Module.ipynb |
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# + [markdown] deletable=true editable=true
# # Predic... | Airline Delay with a GLM in Keras.ipynb |
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# # Optimización media-varianza
#
# <img style="float:... | Modulo3/Clase12_OptimizacionMediaVarianza.ipynb |
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# All content can be freely used and adapted under the... | notebooks/gravmetria/GRAV_somigliana_ar-livre_bouguer-v02.ipynb |
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# # Language Translation
# In this project, you’re goi... | language-translation/dlnd_language_translation.ipynb |
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import matplotlib.pyplot as plt
from matplotlib im... | model_order.ipynb |
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# # Simple dynamic seq2seq with TensorFlow
# ... | 1-seq2seq.ipynb |
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# # 01 - Data Analysis and Preparation
#
# This notebo... | 01-dataset-management.ipynb |
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# # Data Scientist Nanodegree
# ## Supervised Learning... | finding_donors.ipynb |
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# We'll dig in to the following topics:
# * Bias-Var... | Lectures/Levon/ModelTuning_Validation&Cross-Validation/main.ipynb |
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# # Simulation of data relating to weather at Dublin A... | Weather data simulation.ipynb |
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# + [markdown] id="AOpGoE2T-YXS" colab_type="text"
# ##### Copyright 2018 The... | tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb |
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# <a href="https:... | examples/notebooks/cartoee_projections.ipynb |
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# # Neural networks with PyTorch
#
# Deep learn... | intro-to-pytorch/Part 2 - Neural Networks in PyTorch (Exercises).ipynb |
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# # Name
# Data preparation using Apache Pig on YARN w... | components/gcp/dataproc/submit_pig_job/sample.ipynb |
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# ## Read data with a time index
#
# Pandas DataFrame ... | introduction_to_data_visualization_with_matplotlib/2_plotting_time_series.ipynb |
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# ### Outlier Detection with `bqplot`
# ---
# In this... | examples/Applications/Outlier Detection.ipynb |
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# ## Facial Filters
#
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# + [markdown] id="0wPixjHS38aO"
# # **Beginner's Pyth... | session-two/subject_questions/PhysEng_two_answers.ipynb |
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# # Introduction to Data Science
# --... | intro/intro-module-final.ipynb |
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# ## Continuous Futures
# Continuous Futures are an a... | Notebooks/quantopian_research_public/notebooks/tutorials/4_futures_getting_started_lesson4/notebook.ipynb |
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... | _useless/notebooks/Backprop.ipynb |
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# # Seismic Data Analysis
# ### What is Seismic Haza... | Seismic Data Analysis Notebook.ipynb |
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# ## Reproduce In-situ Sequencing results with Starfis... | notebooks/ISS_Pipeline_-_Breast_-_1_FOV.ipynb |
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# + [markdown] iooxa={"id": {"block": "ljl07JNYSrIXE70... | notebooks/.ipynb_checkpoints/Tutorial_pyhton_transform21_UtahForge_58-32_well-checkpoint.ipynb |
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# # Project 2: Digit Recognition
#
# ## Statistical Ma... | COMP90051 Statistical Machine Learning/project-2.ipynb |