Artificial Intelligence

Follow along: https://colab.research.google.com/drive/1-v9cw18wTDjaCUlECKHsQnHeisLKyG8U We need to save Jabril and John Green Bot’s movie nights. Jabril generally likes action movies and John Green Bot likes romantic movies, but they need to find something that they can both watch and enjoy together. Today, we’re going to build a movie recommender systems to find that perfect movie. With the help of the LensKit library, our AI will use existing movie ratings from the MovieLens dataset and personalized ratings from Jabril and John Green Bot to perform user-user collaborative filtering. We’ll then create a Jabril Green Bot hybrid that will average these ratings to try and find something that they both want to watch. Lenskit documentation: https://java.lenskit.org/documentation/ Our GitHub for this lab: https://github.com/crash-course-ai/lab4-recommender-systems Crash Course is produced in association with PBS Digital Studios: https://www.youtube.com/pbsdigitalstudios Crash Course

Follow along: https://colab.research.google.com/drive/1-v9cw18wTDjaCUlECKHsQnHeisLKyG8U We need to save Jabril and John Green Bot’s movie nights. Jabril generally likes action movies and John Green Bot likes romantic movies, but they need to find something that they can both watch and enjoy together. Today, we’re going to build a movie recommender systems to find that perfect movie. With the help of the LensKit library, our AI will use existing movie ratings from the MovieLens dataset and personalized ratings from Jabril and John Green Bot to perform user-user collaborative filtering. We’ll then create a Jabril Green Bot hybrid that will average these ratings to try and find something that they both want to watch. Lenskit documentation: https://java.lenskit.org/documentation/ Our GitHub for this lab: https://github.com/crash-course-ai/lab4-recommender-systems Crash Course is produced in association with PBS Digital Studios: https://www.youtube.com/pbsdigitalstudios Crash Course

Follow along: https://colab.research.google.com/drive/1-v9cw18wTDjaCUlECKHsQnHeisLKyG8U We need to save Jabril and John Green Bot’s movie nights. Jabril generally likes action movies and John Green Bot likes romantic movies, but they need to find something that they can both watch and enjoy together. Today, we’re going to build a movie recommender systems to find that perfect movie. With the help of the LensKit library, our AI will use existing movie ratings from the MovieLens dataset and personalized ratings from Jabril and John Green Bot to perform user-user collaborative filtering. We’ll then create a Jabril Green Bot hybrid that will average these ratings to try and find something that they both want to watch. Lenskit documentation: https://java.lenskit.org/documentation/ Our GitHub for this lab: https://github.com/crash-course-ai/lab4-recommender-systems Crash Course is produced in association with PBS Digital Studios: https://www.youtube.com/pbsdigitalstudios Crash Course

Today, in our final episode of Crash Course AI, we're going to look towards the future. We've spent much of this series explaining how and why we don't have the Artificial General Intelligence (or AGI) that we see in the movies like Bladerunner, Her, or Ex Machina. Siri frequently doesn't understand us, we probably shouldn't sleep in our self-driving cars, and those recommended videos on YouTube and Netflix often aren't what we really want to watch next. So let's talk about what we do know, how we got here, and where we think it's all headed. Thanks so much everyone for watching! Don't forget to subscribe to Jabril’s channel here! http://youtube.com/c/jabrils And you can find some more free recourses to learn about AI below! https://course.fast.ai/ https://www.coursera.org/learn/ai-for-everyone  https://www.coursera.org/learn/machine-learning https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html https://www.kaggle.com/learn/overview https://www.kaggle.com/competitions?

Today, in our final episode of Crash Course AI, we're going to look towards the future. We've spent much of this series explaining how and why we don't have the Artificial General Intelligence (or AGI) that we see in the movies like Bladerunner, Her, or Ex Machina. Siri frequently doesn't understand us, we probably shouldn't sleep in our self-driving cars, and those recommended videos on YouTube and Netflix often aren't what we really want to watch next. So let's talk about what we do know, how we got here, and where we think it's all headed. Thanks so much everyone for watching! Don't forget to subscribe to Jabril’s channel here! http://youtube.com/c/jabrils And you can find some more free recourses to learn about AI below! https://course.fast.ai/ https://www.coursera.org/learn/ai-for-everyone  https://www.coursera.org/learn/machine-learning https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html https://www.kaggle.com/learn/overview https://www.kaggle.com/competitions?

Today, in our final episode of Crash Course AI, we're going to look towards the future. We've spent much of this series explaining how and why we don't have the Artificial General Intelligence (or AGI) that we see in the movies like Bladerunner, Her, or Ex Machina. Siri frequently doesn't understand us, we probably shouldn't sleep in our self-driving cars, and those recommended videos on YouTube and Netflix often aren't what we really want to watch next. So let's talk about what we do know, how we got here, and where we think it's all headed. Thanks so much everyone for watching! Don't forget to subscribe to Jabril’s channel here! http://youtube.com/c/jabrils And you can find some more free recourses to learn about AI below! https://course.fast.ai/ https://www.coursera.org/learn/ai-for-everyone  https://www.coursera.org/learn/machine-learning https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html https://www.kaggle.com/learn/overview https://www.kaggle.com/competitions?

Today, in our final episode of Crash Course AI, we're going to look towards the future. We've spent much of this series explaining how and why we don't have the Artificial General Intelligence (or AGI) that we see in the movies like Bladerunner, Her, or Ex Machina. Siri frequently doesn't understand us, we probably shouldn't sleep in our self-driving cars, and those recommended videos on YouTube and Netflix often aren't what we really want to watch next. So let's talk about what we do know, how we got here, and where we think it's all headed. Thanks so much everyone for watching! Don't forget to subscribe to Jabril’s channel here! http://youtube.com/c/jabrils And you can find some more free recourses to learn about AI below! https://course.fast.ai/ https://www.coursera.org/learn/ai-for-everyone  https://www.coursera.org/learn/machine-learning https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html https://www.kaggle.com/learn/overview https://www.kaggle.com/competitions?

Follow along: https://colab.research.google.com/drive/1N5IdMTmiNbwEOD8dqammN8GAfpk41arw Today, in our final lab, Jabril tries to make an AI settle the question once and for all, "Will a cat or a dog make us happier?" But in building this AI, Jabril will accidentally incorporate the very bias he was trying to avoid. So today we'll talk about how bias creeps into our algorithms and what we can do to try to account for these problems. Crash Course is produced in association with PBS Digital Studios: https://www.youtube.com/pbsdigitalstudios Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse Thanks to the following patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Eric Prestemon, Sam Buck, Mark Brouwer, Efrain R. Pedroza, Matthew Curls, Indika Siriwardena, Avi Yashchin, Timothy J Kwist, Brian Thomas Gossett, Haixiang N/A Liu, Jonathan Zbikowski, Siobhan Sabino, Jennifer Kill

Follow along: https://colab.research.google.com/drive/1N5IdMTmiNbwEOD8dqammN8GAfpk41arw Today, in our final lab, Jabril tries to make an AI settle the question once and for all, "Will a cat or a dog make us happier?" But in building this AI, Jabril will accidentally incorporate the very bias he was trying to avoid. So today we'll talk about how bias creeps into our algorithms and what we can do to try to account for these problems. Crash Course is produced in association with PBS Digital Studios: https://www.youtube.com/pbsdigitalstudios Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse Thanks to the following patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Eric Prestemon, Sam Buck, Mark Brouwer, Efrain R. Pedroza, Matthew Curls, Indika Siriwardena, Avi Yashchin, Timothy J Kwist, Brian Thomas Gossett, Haixiang N/A Liu, Jonathan Zbikowski, Siobhan Sabino, Jennifer Kill

Follow along: https://colab.research.google.com/drive/1N5IdMTmiNbwEOD8dqammN8GAfpk41arw Today, in our final lab, Jabril tries to make an AI settle the question once and for all, "Will a cat or a dog make us happier?" But in building this AI, Jabril will accidentally incorporate the very bias he was trying to avoid. So today we'll talk about how bias creeps into our algorithms and what we can do to try to account for these problems. Crash Course is produced in association with PBS Digital Studios: https://www.youtube.com/pbsdigitalstudios Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse Thanks to the following patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Eric Prestemon, Sam Buck, Mark Brouwer, Efrain R. Pedroza, Matthew Curls, Indika Siriwardena, Avi Yashchin, Timothy J Kwist, Brian Thomas Gossett, Haixiang N/A Liu, Jonathan Zbikowski, Siobhan Sabino, Jennifer Kill