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Articles related to "feature"


Why I *love* TMUX

  • So one sweet thing about Tmux is that it creates "sessions" which means that you can open several separate instances of tmux all with their own tabs and applications running.
  • This feature extends beyond the ability to run tmux in any terminal and get a new instance.
  • I create a specific "work" session in tmux that has VIM, servers, and other utilities initialized and I actually rarely close it - I simply detach from the session when I'm done working.
  • The session management in tmux is more of a power user utility that I started seriously using only recently but it's super useful and at this point, it's the selling feature of tmux to me.
  • If I want to take a break from my desktop, I can just pick up my laptop, open a terminal window there, and attach to the session.

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A Brief Tour of Scikit-learn (Sklearn)

  • Scikit-learn is a python library that provides methods for data reading, data preparation, regression, classification, unsupervised clustering, and much more.
  • We can see that random forest performance is much better than linear regression.
  • We can further improve performance by optimizing parameters in random forests.
  • Feel free to train and test on the full data set for a more suitable comparison of performance between models.
  • We see that support vector regression performs better than linear regression but worse than random forests.
  • Similar to the random forest example, the support vector machine parameters can be optimized such that error is minimized.
  • We see that k-nearest neighbors algorithm outperform linear regression when trained on the full data set.
  • In another post, I will outline some of the classification methods that are most common in the python machine learning library.

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A Brief Tour of Scikit-learn (Sklearn)

  • Scikit-learn is a python library that provides methods for data reading, data preparation, regression, classification, unsupervised clustering, and much more.
  • We can see that random forest performance is much better than linear regression.
  • We can further improve performance by optimizing parameters in random forests.
  • Feel free to train and test on the full data set for a more suitable comparison of performance between models.
  • We see that support vector regression performs better than linear regression but worse than random forests.
  • Similar to the random forest example, the support vector machine parameters can be optimized such that error is minimized.
  • We see that k-nearest neighbors algorithm outperform linear regression when trained on the full data set.
  • In another post, I will outline some of the classification methods that are most common in the python machine learning library.

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A Brief Tour of Scikit-learn (Sklearn)

  • Scikit-learn is a python library that provides methods for data reading, data preparation, regression, classification, unsupervised clustering, and much more.
  • We can see that random forest performance is much better than linear regression.
  • We can further improve performance by optimizing parameters in random forests.
  • Feel free to train and test on the full data set for a more suitable comparison of performance between models.
  • We see that support vector regression performs better than linear regression but worse than random forests.
  • Similar to the random forest example, the support vector machine parameters can be optimized such that error is minimized.
  • We see that k-nearest neighbors algorithm outperform linear regression when trained on the full data set.
  • In another post, I will outline some of the classification methods that are most common in the python machine learning library.

save | comments | report | share on


A Brief Tour of Scikit-learn (Sklearn)

  • Scikit-learn is a python library that provides methods for data reading, data preparation, regression, classification, unsupervised clustering, and much more.
  • We can see that random forest performance is much better than linear regression.
  • We can further improve performance by optimizing parameters in random forests.
  • Feel free to train and test on the full data set for a more suitable comparison of performance between models.
  • We see that support vector regression performs better than linear regression but worse than random forests.
  • Similar to the random forest example, the support vector machine parameters can be optimized such that error is minimized.
  • We see that k-nearest neighbors algorithm outperform linear regression when trained on the full data set.
  • In another post, I will outline some of the classification methods that are most common in the python machine learning library.

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Dyson hopes you'll throw down $650 for its lamp that mimics candlelight

  • Dyson's newest light, the Lightcycle Morph, is its most flexible lamp yet.
  • At first glance, it looks similar to the Dyson Lightcycle, introduced last year, and it has many of the same key features -- like the ability to automatically adjust based on your local daylight.
  • It also has three axes which allow it to rotate into different positions and the ability to emulate candlelight, but you'll have to shell out a minimum of $650 for this updated version.
  • You can aim the Lightcycle Morph at art for feature lighting, or use it more traditionally over your workspace.
  • The Morph also adds a light-up stem that emits a warm, orange glow and can emulate candlelight.
  • Like the original Dyson Lightcycle, the Morph adjusts based on your age -- according to Dyson a 65-year-old needs four times more light than a 20-year-old.

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Political Data Science: A tale of tweets

  • The current political situation in Scotland after the Brexit vote, and most recently, Boris Johnson’s win in the winter General Election of 2019, is very heated.
  • I then performed a systematic comparison with a Deep Learning Recurrent Neural Network (RNN) known as Long-Short-Term-Memory (LSTM) Network.
  • With Grid Search you set up a grid of hyperparameter values and for each combination, train a model and score on the validation data.
  • I passed the combined hyperparameters to the GridsearchCV object for each classifier and 10 folds for the cross validation which means that for every parameter combination, the grid ran 10 different iterations with a different test set every time (this took a while…).
  • And if we want a neural network to understand our tweets, we need one that can learn from what it reads and build on it.

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#todayilearnedCompleted JavaScript Data Structure Course, and Here is What I Learned About Hash Table.

  • In the last few articles, I wrote overviews of Linked List, Queue, Stack, Binary Search Tree, and Binary Heap that I learned while taking JavaScript Data Structures and Algorithms Course on Udemy.
  • I'd like to implement features to delete/edit each data efficiently, but in this case, both of feature takes time complexity of O(n).
  • It looks similar to arrays -- we map index to values, but for Hash Table, we use keys instead of indexes.
  • What happens behind the scene is that a Hash Table uses a hash function to compute an index from the key, and the index tells which array of buckets the value should be stored into.
  • There are so many more data structures out there to learn, and also there's more to know about JavaScript Object and Map. Always think there's room to improve, so we won't lose the chance to make our crafts better.

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How to turn on shuffle on Spotify, using either your computer or phone

  • From watching music videos on YouTube to streaming music on platforms like Spotify, it's never been easier to listen to music.
  • Aside from the standard features, Spotify also includes a shuffle feature, which allows you to switch up the order of songs in your playlists or favorite albums.
  • Here's how to turn on the shuffle feature on Spotify.
  • Insider receives a commission when you buy through our links.

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Here's the full list of Super Bowl commercials that will run this year

  • The car maker is set to make its 11th consecutive appearance in the big game in a spot produced by David & Goliath, in which a 10 year-old boy replaces a star athlete in a press conference.
  • Michelob Ultra is yet another Anheuser-Busch InBev brand in Super Bowl 2020, and is running a star-studded 60-second spot this year with Jimmy Fallon, John Cena, Usain Bolt, Brooks Koepka, and Kerri Walsh Jennings.
  • The longtime Super Bowl advertiser is returning to the big game with a 30-second commercial starring Missy Elliott and H.E.R. that will promote Pepsi Zero Sugar in a matte black can.
  • The car-mat maker is making its seventh Super Bowl appearance this year, with a 30-second commercial produced by its agency of record Pinnacle Advertising.

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