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Articles related to "question"


Decision Tree Classifier from Scratch: Classifying Student’s Knowledge Level

  • In simple words, Decision Tree Classifier is a Supervised Machine learning algorithm which is used for supervised + classification problems.
  • Under the hood in decision tree, each node asks a True or False question about one of the features and moves left or right with respect to the decision.
  • We are going to use a Machine Learning algorithms to find the patterns on the historical data of the students and classify their knowledge level, and for that we are going to write our own simple Decision Tree Classifier from scratch by using Python Programming Language.
  • We have written a find_best_split function which finds the best question to as by iterating over every features and labels then calculates the information gain.
  • We have built a very simple Decision Tree Classifier from scratch without using any abstract libraries to predict the student's knowledge level.

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After 184 years, Cherokees seek House delegate seat promised in treaty

  • It was a treaty, ratified by the Senate and signed by President Andrew Jackson in 1835, granting the Cherokee Nation a delegate to Congress.
  • Teehee was named to that post in September by the tribe’s chief, Chuck Hoskin Jr. The move set off a series of technical and moral questions for leaders in Congress, who are now tasked with determining whether — and how — to allow her to take her seat.
  • A generation ago, congressional leaders might have ignored or flat out rejected claims from the Cherokee Nation to a delegate, adding to the federal government’s long history of breaking agreements with Native Americans.
  • Teehee and political leaders from other tribes say the response to the Cherokee Nation will be an important indication of how serious tribal rights are to elected officials.

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Decision Tree Classifier from Scratch: Classifying Student’s Knowledge Level

  • In simple words, Decision Tree Classifier is a Supervised Machine learning algorithm which is used for supervised + classification problems.
  • Under the hood in decision tree, each node asks a True or False question about one of the features and moves left or right with respect to the decision.
  • We are going to use a Machine Learning algorithms to find the patterns on the historical data of the students and classify their knowledge level, and for that we are going to write our own simple Decision Tree Classifier from scratch by using Python Programming Language.
  • We have written a find_best_split function which finds the best question to as by iterating over every features and labels then calculates the information gain.
  • We have built a very simple Decision Tree Classifier from scratch without using any abstract libraries to predict the student's knowledge level.

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The simple 4-word sentence that'll make you the master of small talk

  • I've dug up tricks for more interesting small talk, tips to be a better conversationalist, and out-of-the box icebreaker questions (so many questions) to get good conversations going.
  • Recently on the blog Cup of Jo, I came across a great small talk-busting question that is effective, versatile, and all of four words long.
  • While it's hard to think of a simpler question, according to my personal experience at least, it's still not much used.
  • Unlike more common conversation starters like "So what do you do for work?" it makes no assumptions about a person, so it's guaranteed not to force anyone to make any uncomfortable or potentially embarrassing admissions.
  • But to my mind Gross's suggestion for the best ever conversation starter is hard to beat.

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Decision Tree Classifier from Scratch: Classifying Student’s Knowledge Level

  • In simple words, Decision Tree Classifier is a Supervised Machine learning algorithm which is used for supervised + classification problems.
  • Under the hood in decision tree, each node asks a True or False question about one of the features and moves left or right with respect to the decision.
  • We are going to use a Machine Learning algorithms to find the patterns on the historical data of the students and classify their knowledge level, and for that we are going to write our own simple Decision Tree Classifier from scratch by using Python Programming Language.
  • We have written a find_best_split function which finds the best question to as by iterating over every features and labels then calculates the information gain.
  • We have built a very simple Decision Tree Classifier from scratch without using any abstract libraries to predict the student's knowledge level.

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Bestselling author Shea Serrano’s writing reads like a conversation. That’s not an accident.

  • Serrano, a bestselling author whose newest book Movies (And Other Things) is out this week, writes about basketball, movies, race, and a grab bag of topics in a casual, just-thought-of-this style that looks easy to do but isn’t.
  • And the approachable prose, along with the fact that he’s often writing about seemingly innocuous stuff, gives him the ability to do something extra-difficult: Serrano often slips in perceptive and provocative ideas about race and class, right alongside topics like The Best Gangster Movie Moments.
  • And when you’re doing it the other way, when you’re just sort of following where your nose is taking you, you get into the interesting stuff and then it makes sense for me to be like, “I’m going to talk about this movie.” And then there’s some other stuff going on because you can see how we got there and how we’re going to get out and get back to the movie.

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Decision Tree Classifier from Scratch: Classifying Student’s Knowledge Level

  • In simple words, Decision Tree Classifier is a Supervised Machine learning algorithm which is used for supervised + classification problems.
  • Under the hood in decision tree, each node asks a True or False question about one of the features and moves left or right with respect to the decision.
  • We are going to use a Machine Learning algorithms to find the patterns on the previous data of the students and classify their level.
  • For that we are going to write our own simple Decision Tree Classifier from scratch by using Python Programming Language.
  • Now it’s time to write our Decision Tree Classifier.
  • We have written a find_best_split function which finds the best question to as by iterating over every features and labels then calculates the information gain.
  • We have built a very simple Decision Tree Classifier from scratch without using any abstract libraries to predict the student's knowledge level.

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#help#help has had a makeover

  • The #help tag has real potential to become an area where developers can come to ask questions and have access to the growing amount of experienced developers that frequent this site.
  • Unfortunately, it has become a bit of a free-for-all for anything from helpful articles to extremely broad "I want to build x, how do I do it?" type questions.
  • If you generally can't find a tag for your question, and you think it should sit in #help then please reach out.
  • If a post is made, that doesn't follow the recommended format for the title/body we'll leave a comment and ask you to update it, or provide a reason why that's not possible.
  • If a post is made that doesn't fit in with this section, we'll remove the tag and provide the reason why.

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Decision Tree Classifier from Scratch: Classifying Student’s Knowledge Level

  • In simple words, Decision Tree Classifier is a Supervised Machine learning algorithm which is used for supervised + classification problems.
  • Under the hood in decision tree, each node asks a True or False question about one of the features and moves left or right with respect to the decision.
  • We are going to use a Machine Learning algorithms to find the patterns on the previous data of the students and classify their level.
  • We are going to write our own simple Decision Tree Classifier from scratch by using Python Programming Language.
  • Now it’s time to write our Decision Tree Classifier.
  • We have written a find_best_split function which finds the best question to as by iterating over every features and labels then calculates the information gain.
  • We have built a very simple Decision Tree Classifier from scratch without using any abstract libraries to predict the student's knowledge level.

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Better Technical Interviews: Part 5 – My Common Interview Questions

  • Please recall that throughout preceding articles, I mentioned that the interview process needs to be heavily tailored to the position you’re seeking to fill, and to the research you’ve done on an interviewee.
  • I mention this again here because it’s really important.
  • If you treat the questions below as a one-size-fits-all play book, you will be doing your team and your interviewees a disservice.
  • There is no overall interview play book in my opinion.
  • These questions rarely exist on their own, but I usually try to turn them into mini conversations.
  • With that said, here are some common questions I tend to ask and my reasoning behind them.
  • A little background on this question: I tend to phrase this along the lines of: “You’re working on an assignment with a really important deadline for your client.

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