FMA: A Dataset For Music Analysis

Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson, EPFL LTS2. Free Music Archive web API All the data in the raw_*.csv tables was collected from the Free Music Archive public API. With this notebook, you can: reconstruct the original data, update some fields, e.g. the track listens (play count), augment the data with newer fields… Continue reading FMA: A Dataset For Music Analysis

word2vec visualization

using ipython notebook version: original In [1]: import visword2vec # 単語で作ったモデル vis = visword2vec.visWord2Vec(“recipe_steps.bin”) # フレーズで作ったモデル vis_phrase = visword2vec.visWord2Vec(“recipe_steps-phrase.bin”) loading loaded loading loaded In [2]: def plot_both(word): vis.plot(word) vis_phrase.plot(word) In [3]: plot_both(‘チョコ’) [ 0.21099427 0.11427726] [ 0.19734898 0.13841781] In [4]: vis_phrase.plot(‘義理_チョコ’) [ 0.16700684 0.1221358 ] In [5]: plot_both(‘義理’) [ 0.17986007 0.14094272] [ 0.248188 0.16636363] In [6]: plot_both(‘あつあつ’)… Continue reading word2vec visualization

Probabilistic Programming and

Probabilistic Programming & Bayesian Methods for Hackers Using Python and PyMC The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chapters of slow, mathematical analysis. The typical text on Bayesian inference involves two to three chapters on probability theory, then enters what Bayesian inference is. Unfortunately, due to… Continue reading Probabilistic Programming and

HTTP and Requests

Data too large for file format source Similar Notebooks py 1 1en 5 3 requests http py 1 1en 5 3 requests http checkpoint advanced scraping form submission 15 4 http postrequest multipleparameters 15 9 http responseformats 15 11 http redirectsandtimeout 15 1 http getbasics 6 derived outputs Copyright © Code Fetcher 2022    

Django Allauth Social Login For Pre Approved Users Only

Snippet 1  from allauth.account.adapter import DefaultAccountAdapterfrom allauth.socialaccount.adapter import DefaultSocialAccountAdapterfrom django.conf import settingsfrom django.http import HttpRequestfrom django.contrib.auth import get_user_modelfrom django.http import HttpResponsefrom allauth.exceptions import ImmediateHttpResponseclass AccountAdapter(DefaultAccountAdapter):  def is_open_for_signup(self, request: HttpRequest):      return getattr(settings, “ACCOUNT_ALLOW_REGISTRATION”, False)class SocialAccountAdapter(DefaultSocialAccountAdapter):  def pre_social_login(self, request, sociallogin):      try:          get_user_model().objects.get(      except get_user_model().DoesNotExist:       … Continue reading Django Allauth Social Login For Pre Approved Users Only

How To Change User Password Using Django Admin

Snippet 1 ‘’’We can change the password using admin or superuser. Assuming you have super useralready created. Please add following urls in your‘’’from django.contrib import adminfrom django.urls import path, includeurlpatterns = [   path(‘admin/’,,   path(”, include (‘main.urls’)),   path(‘accounts/’, include(‘django.contrib.auth.urls’)),]‘’’In your browser go to url your your superuser name and password.Then click on users.Click… Continue reading How To Change User Password Using Django Admin

Multithreading With Queue In Python 3

Snippet 1 import pandas as pdimport threadingimport timefrom multiprocessing import Queuemy_queue = Queue(maxsize=0)#Let us define our workerdef worker(my_queue): #Add some time to fill up the queue time.sleep(5) while(my_queue.qsize() > 0):      entry = my_queue.get() #Let us define our threads herenum_threads = 10threads = []try:  for i in range(num_threads):      t = threading.Thread(target=worker,args=(my_queue)      t.start()     … Continue reading Multithreading With Queue In Python 3

Sqlalchemy Create Engine

from sqlalchemy import create_engine source engine = create_engine(“sqlite:///hawaii.sqlite”) source engine = create_engine(f’sqlite:///../../../ih_final_project_DB/ih_final_project’) con = engine.connect() nombre_tabla = engine.table_names() source def db_connection(path): engine = create_engine(path) connection = engine.connect() return connection source #endpoint = ‘sqlite:///insiders_db.sqlite’ #local endpoint = ‘sqlite:////Users/Alysson/Documents/Projects/Hotel-Booking-Cancelation/data/hotels.sqlite’ #local db = create_engine(endpoint, poolclass=NullPool) connection = db.connect() source protocol = ‘postgresql’ password=ETL_config.password username=ETL_config.username host = ‘localhost’ port… Continue reading Sqlalchemy Create Engine

Regression Trees

Estimated time needed: 20 minutes In this lab you will learn how to implement regression trees using ScikitLearn. We will show what parameters are important, how to train a regression tree, and finally how to determine our regression trees accuracy. Objectives After completing this lab you will be able to: Train a Regression Tree Evaluate… Continue reading Regression Trees

This is an IPython notebook, backed by a ruby kernel.

I wrote a kernel in Ruby that adheres to the IPython messaging protocol. Then I modified IPython, with the help of minrk from #ipython, to instantiate my Ruby Kernel instead of its own Python kernel. The IPython KernelManager start the RubyKernel as a subprocess, and from that point communication occurs over ZeroMQ, exactly as if… Continue reading This is an IPython notebook, backed by a ruby kernel.

Data Profiling

In [1]: import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns from sklearn.linear_model import LinearRegression from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.preprocessing import MinMaxScaler from sklearn.metrics import mean_absolute_error from sklearn.metrics import mean_absolute_percentage_error import warnings warnings.filterwarnings(‘ignore’) In [2]: df = pd.read_csv(‘Salary_Data.csv’) In [3]: df.head() Out[3]: YearsExperience Salary 0 1.1… Continue reading Data Profiling