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What is machine learning and how does Netflix use it for its recommendation engine?

What is machine learning and how does Netflix use it for its recommendation engine?

What is machine learning and how does Netflix use it for its recommendation engine?

What is an online recommendation engine?

Think about examples of machine learning you may have encountered in the past such as a website like Netflix  that recommends what video you may be interested in watching next?
Are the recommendations ever wrong or unfair? We will  give an example and explain how this could be addressed.

2023 AWS Certified Machine Learning Specialty (MLS-C01) Practice Exams
2023 AWS Certified Machine Learning Specialty (MLS-C01) Practice Exams

Machine learning is a field of artificial intelligence that Netflix uses to create its recommendation algorithm. The goal of machine learning is to teach computers to learn from data and make predictions based on that data. To do this, Netflix employs Machine Learning Engineers, Data Scientists, and software developers to design and build algorithms that can automatically improve over time. The Netflix recommendations engine is just one example of how machine learning can be used to improve the user experience. By understanding what users watch and why, the recommendations engine can provide tailored suggestions that help users find new shows and movies to enjoy. Machine learning is also used for other Netflix features, such as predicting which shows a user might be interested in watching next, or detecting inappropriate content. In a world where data is becoming increasingly important, machine learning will continue to play a vital role in helping Netflix deliver a great experience to its users.

What is machine learning and how does Netflix use it for its recommendation engine?
What is machine learning and how does Netflix use it for its recommendation engine?

Netflix’s recommendation engine is one of the company’s most valuable assets. By using machine learning, Netflix is able to constantly improve its recommendations for each individual user.

Machine learning engineers, data scientists, and developers work together to build and improve the recommendation engine.

  • They start by collecting data on what users watch and how they interact with the Netflix interface.
  • This data is then used to train machine learning models.
  • The models are constantly being tweaked and improved by the team of engineers.
  • The goal is to make sure that each user sees recommendations that are highly relevant to their interests.

Thanks to the work of the team, Netflix’s recommendation engine is constantly getting better at understanding each individual user.

How Does It Work?

In short, Netflix’s recommendation algorithm looks at what you’ve watched in the past and then makes recommendations based on that data. But of course, it’s a bit more complicated than that. The algorithm also looks at data from other users with similar watching habits to yours. This allows Netflix to give you more tailored recommendations.

For example, say you’re a big fan of Friends (who isn’t?). The algorithm knows that a lot of Friends fans also like shows like Cheers, Seinfeld, and The Office. So, if you’re ever feeling nostalgic and in the mood for a sitcom marathon, Netflix will be there to help you out.

But That’s Not All…

Not only does the algorithm take into account what you’ve watched in the past, but it also looks at what you’re currently watching. For example, let’s say you’re halfway through Season 2 of Breaking Bad and you decide to take a break for a few days. When you come back and finish Season 2, the algorithm knows that you’re now interested in similar shows like Dexter and The Wire. And voila! Those shows will now be recommended to you.

Of course, the algorithm isn’t perfect. There are always going to be times when it recommends a show or movie that just doesn’t interest you. But hey, that’s why they have the “thumbs up/thumbs down” feature. Just give those shows the old thumbs down and never think about them again! Problem solved.

Another angle :

When it comes to TV and movie recommendations, there are two main types of data that are being collected and analyzed:

1) demographic data

2) viewing data.

Demographic data is information like your age, gender, location, etc. This data is generally used to group people with similar interests together so that they can be served more targeted recommendations. For example, if you’re a 25-year-old female living in Los Angeles, you might be grouped together with other 25-year-old females living in Los Angeles who have similar viewing habits as you.

Viewing data is exactly what it sounds like—it’s information on what TV shows and movies you’ve watched in the past. This data is used to identify patterns in your viewing habits so that the algorithm can make better recommendations on what you might want to watch next. For example, if you’ve watched a lot of romantic comedies in the past, the algorithm might recommend other romantic comedies that you might like based on those patterns.

Are the Recommendations Ever Wrong or Unfair?
Yes and no. The fact of the matter is that no algorithm is perfect—there will always be some error involved. However, these errors are usually minor and don’t have a major impact on our lives. In fact, we often don’t even notice them!

The bigger issue with machine learning isn’t inaccuracy; it’s bias. Because algorithms are designed by humans, they often contain human biases that can seep into the recommendations they make. For example, a recent study found that Amazon’s algorithms were biased against women authors because the majority of book purchases on the site were made by men. As a result, Amazon’s algorithms were more likely to recommend books written by men over books written by women—regardless of quality or popularity.

These sorts of biases can have major impacts on our lives because they can dictate what we see and don’t see online. If we’re only seeing content that reflects our own biases back at us, we’re not getting a well-rounded view of the world—and that can have serious implications for both our personal lives and society as a whole.

One of the benefits of machine learning is that it can help us make better decisions. For example, if you’re trying to decide what movie to watch on Netflix, the site will use your past viewing history to recommend movies that you might like. This is possible because machine learning algorithms are able to identify patterns in data.

Another benefit of machine learning is that it can help us automate tasks. For example, if you’re a cashier and have to scan the barcodes of the items someone is buying, a machine learning algorithm can be used to automatically scan the barcodes and calculate the total cost of the purchase. This can save time and increase efficiency.

The Consequences of Machine Learning

While machine learning can be beneficial, there are also some potential consequences that should be considered. One consequence is that machine learning algorithms can perpetuate bias. For example, if you’re using a machine learning algorithm to recommend movies to people on Netflix, the algorithm might only recommend movies that are similar to ones that people have already watched. This could lead to people only watching movies that confirm their existing beliefs instead of challenged them.

Another consequence of machine learning is that it can be difficult to understand how the algorithms work. This is because the algorithms are usually created by trained experts and then fine-tuned through trial and error. As a result, regular people often don’t know how or why certain decisions are being made by machines. This lack of transparency can lead to mistrust and frustration.

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  • Switched to the ad version....
    by /u/rysimpcrz (Netflix) on July 26, 2024 at 5:47 am

    And all my devices stopped working. The alerts said my devices must be outdated, need upgrades, or I should upgrade. All of my devices are brand new and current as of 5 minutes past my change in billing. Sorry Netflix, after 20+ years you've messed with this customer for the last time. Your subscribers are going to drop like flies going forward. submitted by /u/rysimpcrz [link] [comments]

  • "The 100" Thoughts
    by /u/hectorb3 (Netflix) on July 26, 2024 at 4:45 am

    A while back I subscribed to Netflix and found 'The 100'. The premise was very enticing to my sci-fi/fantasy mind, so I started watching it. I'm up to S3E12, and it just seems to be the same thing over and over. Clark or someone else screws up thinking they are doing something that's going to fix everything between the different groups, but it all backfires, and then the hive mind for either society takes over and they are all killing each other again. I do enjoy the characters and their development through the series so far. Does the show get any better? Are there better plot lines? Or am I just asking for too much from an old weekly sci-fi drama? submitted by /u/hectorb3 [link] [comments]

  • Just found out that my Netflix account was activated by someone else using my debit card after I unsubscribe years ago. Netflix support wouldn’t engage. Am I screwed?
    by /u/SR-Barlowe (Netflix) on July 26, 2024 at 4:45 am

    I know I’m the stupid one for not checking my charges for so long, but I just discovered that my account was taken over at least four years ago and the subscription has been running the whole time. There are multiple profiles on “my” account that I didn’t create (quite clearly since I don’t speak the language) but I understand that’s circumstantial. Do I have any hope of recovering anything that I’ve apparently been paying into this or am I just totally out of luck? submitted by /u/SR-Barlowe [link] [comments]

  • Netflix Tricked Me Into Buying A Plan That Is Useless
    by /u/jsfb (Netflix) on July 26, 2024 at 4:09 am

    Canada here. When my plan became outdated, I switched to the lowest plan (Standard with Ads), begrudgingly. I tried watching my show tonight and my it wouldn't stream on my TV because "Your Plan Does Not Support Streaming On This Device". Well my TV is a Smart TV, Samsung, less than 5 years old. It's not my problem that Netflixs' policies and ads are incompatible with my (completely normal) TV. I subscribed to a monthly plan under the assumption that a streaming service would work on my TV? Is that not reasonable? I called Netflix and the solution is to buy a better TV that supports ads (???) or upgrade my plan (of course). Why would Netflix offer a plan that is incompatible with normal, modern devices? It's not fair that I'm restricted from receiving what I pay for due to compatibility issues that are out of my control. FURTHERMORE, I tried chromecasting from the Netflix app onto the TV but they got rid of that option in the Netflix app. It simply won't chromecast. It won't let me cast my stream (that I am paying monthly for) onto a larger screen. I'm done. I'm out. I'll have to use other streaming services or find a different way to watch my shows but I am fed up with Netflix's scammy and deceptive marketing. submitted by /u/jsfb [link] [comments]

  • The Boyfriend
    by /u/Jatmahl (Netflix) on July 26, 2024 at 3:59 am

    I can see this being a thing where it's done in different countries. Make it happen Netflix. Would love to see a Brazil, South African, UK and France version. submitted by /u/Jatmahl [link] [comments]

  • Skywalkers: A Love Story FAKE?!
    by /u/lowclouds3 (Netflix) on July 26, 2024 at 3:50 am

    My wife and I watched this documentary last night. While being entertained, I can't help but feel like it was fake. Some questions: - the scaffolding they practiced with and then later used for the final claim was conveniently exact same size as the one they found at the bottom of the spire - the scaffold they found at the bottom of the spire fit perfectly at the top where they did the swan dive pose - the weather was always really good, isn't the wind crazy fast when your at those heights... none of the shots on the top of building showed any weather conditions Could the movie just be some green screens and some stitches together drone video of the real landmark's & buildings? submitted by /u/lowclouds3 [link] [comments]

  • has anyone watched find me falling
    by /u/HeliumRhenium (Netflix) on July 26, 2024 at 3:09 am

    am i high or was this movie really bad i didn't realize him and Melina weren't flirting until the bomb dropped that she was his daughter so many unnecessary scenes...like the scene with the grandma having her death bag packed was long for no reason lol the music is giving like they took a guy who sings on Broadway and tried to make him sound like a rock star the fence was like 2 feet long melina being born & raised in Greece but sounding american i stopped watching when he saved the pregnant girl from jumping so maybe i missed an ending that connects the dots what do you think submitted by /u/HeliumRhenium [link] [comments]

  • Can someone please explain the monsters in “Sweet Home” for me, please!
    by /u/Maison-Ikkoku (Netflix) on July 26, 2024 at 2:22 am

    Ok, I am not here to comment on the quality of the drama. I am sure many would agree that seasons 2 and 3, with their cheap production and boring storyline pale in comparison to season 1. What I am trying to understand is who and where did the monsters come from. There seems to be three types of monsters: the true monsters, those alien looking creatures, and then there are the bad human-looking monsters that can do weird things (excluding the main protagonist who is a good humanoid monster), and then in season 3 we are introduced to the neohumans who are not really monsters but not entirely human. So where did each come from and who exactly are they? submitted by /u/Maison-Ikkoku [link] [comments]

  • Netflix Skipping Over Episodes?
    by /u/Amazing_Persimmon769 (Netflix) on July 26, 2024 at 1:22 am

    I have only noticed this recently but as I’m binge watching shows it will skip an episode and automatically load up the episode after it. So for example I’ll be watching episode 7, it ends and I click the “next episode” button, and it loads up episode 9. I can still go back and watch these episodes that are being skipped if I go through the “episodes and more” tab but it is really annoying trying to catch every time netflix does this, and sometimes I only catch it after already watching a few more episodes ahead. Recently it happened while I was watching the 7th episode of Dead Boy Detectives. The thing is there are only 8 episodes of DBD so instead netflix loaded up what I would call the “you finished the series you’re watching” screen. Netflix made it seem like I had finished the series and there was nothing left to watch, it gave me the recommendation it always does when finishing a series so I assumed it was over. The only reason I realized and went back to watch the next episode was because my sister mentioned there were 8 episodes, which I had also remembered but just assumed I had recalled it wrong. I went to check the “episodes and more” tab and there was the 8th episode it had skipped over. This is super inconvenient and has spoiled certain episodes of some series for me. Is this happening to anyone else? If so is there a way to fix it? And no it’s not an issue with someone else being on my account I’ve already checked that out. If anyone has an answer that would be greatly appreciated. submitted by /u/Amazing_Persimmon769 [link] [comments]

  • US: Trash Truck
    by /u/ThisIsMyAltBrah (Netflix) on July 26, 2024 at 12:38 am

    Netflix’s ‘Trash Truck’ & ‘My Dad The Bounty Hunter’ Producer Acquired By France Télévisions’ Studio Arm submitted by /u/ThisIsMyAltBrah [link] [comments]

  • Commercials added = lagging AF
    by /u/nela_mariposa (Netflix) on July 26, 2024 at 12:36 am

    Netflix told me that I could no longer keep my super old, less than $10/mo subscription price and forced me to change to a higher price point WITH commercials now, and even higher cost without commercials. After I switched to having commercials, I can’t get the dang thing to stop buffering, freezing, or the sound/picture not be in alignment. So basically, now that I pay more money, the quality sucks and I have to restart Netflix over and over again. Anyone else experience the same thing? If I pay for no commercials, will I be able to get thru a whole show without it crapping out on me? submitted by /u/nela_mariposa [link] [comments]

  • 3 episodes into Dark and struggling to get into it.
    by /u/dustandchaos (Netflix) on July 26, 2024 at 12:36 am

    I’ve heard people rave endlessly about this show so I’m giving it a go. I’m not sure if it’s the English dubbing, or the time travel arch, or some lack of connection to the characters but I’m finding it hard to connect. Is it something that gets better as you go or if you don’t start out loving it you just won’t love it? submitted by /u/dustandchaos [link] [comments]

  • Homicide LA
    by /u/Euphoric-Kale9532 (Netflix) on July 25, 2024 at 11:54 pm

    Am I wrong?? submitted by /u/Euphoric-Kale9532 [link] [comments]

  • Tell them you love me, Anna Stubblefield disability kink?
    by /u/Remote_Promise498 (Netflix) on July 25, 2024 at 11:26 pm

    Anyone else think Anna had a kink for disabled people? I think it has a lot with her being narcissistic and basically falling inlove with herself but I found it super strange that she enjoyed "cosplaying" disabled people as kid. It threw me off so much, specifically because she said it so casually like it was a normal thing every kid did... submitted by /u/Remote_Promise498 [link] [comments]

  • Dark comedy recommendations
    by /u/insouciant_unsoul (Netflix) on July 25, 2024 at 11:26 pm

    I recently enjoyed watching Bad sisters (2022) and Fleabag (2016-2019). I'd prefer movie/series recommendations on dark comedy genre. Something more recent and contemporary. Would prefer any language. submitted by /u/insouciant_unsoul [link] [comments]

  • BBQ Showdown Kevin Bludso isn’t even that good…
    by /u/TeaHot8165 (Netflix) on July 25, 2024 at 9:28 pm

    I was looking for another bbq competition show to watch. I found an old Food Network show called BBQ Brawl. Kevin was a contestant on that show. He performed so poorly that he was almost last picked for teams. Then he was the first eliminated contestant on episode 1 season 1. Bobby Flay was not impressed with him to say the least. submitted by /u/TeaHot8165 [link] [comments]

  • Short attention span, need something to get me hooked
    by /u/EaterPeoplePurple (Netflix) on July 25, 2024 at 8:44 pm

    Finding it tricky to get more than 5 minutes out of a show. Blame it on short attention span? Who knows. The only shows that really reeled me in were baby reindeer, Mr robot, queens gambit, breaking bad and better call Saul. Ozark was OK. Not interested in bridgerton, GOT or anime. What’s left out there?? Need something intense! submitted by /u/EaterPeoplePurple [link] [comments]

  • Leave the World Behind (Wish I'd left this movie behind)
    by /u/Key-Satisfaction899 (Netflix) on July 25, 2024 at 8:21 pm

    This movie was like a freshman art of film project. Wildly melodramatic disjointed scenes, accompanied by piano and string orchestra instrumentation to guilt you into feeling it must be deeper than you think. Hyperbole everywhere, a plot so thin you can't even project meaning into it, populated by characters that are contradictory caricatures of themselves from scene to scene. It's one thing to be abstract, and/or to try to create a feeling of confusion and despair in an audience which people experiencing a scenario like this would be feeling ... It does neither. Truly a self indulgent turd of a movie. How do A-List stars get roped into thinking this is deep, reflective and thought provoking? submitted by /u/Key-Satisfaction899 [link] [comments]

  • Crooks Episode 5
    by /u/-asoparty- (Netflix) on July 25, 2024 at 8:11 pm

    Hi leute, ich versuche es nochmal mit einem eigenen beitrag. Ich suche: "I Nuovi Angeli - Troppo Bella (Schallbauer Remix for CROOKS)" Der schallbauer remix war auf youtube und soundcloud verfügbar und wurde entfernt oder auf privat gestellt. Hat ihn noch jemand sichern können und kann ihn bereitstellen oder hat irgendeine andere idee, wie ich genau diesen remix finden kann. Die übrigen remixe auf spotify, soundcloud und youtube finde ich keine ausreichend gute alternative. Vielen dank submitted by /u/-asoparty- [link] [comments]

  • Looking for a show
    by /u/sarcasticcheesecake (Netflix) on July 25, 2024 at 8:04 pm

    Looking for a show to watch with my 11 year old. She's at the stage where kids shows are boring but she's too young for adult shows.. Any suggestions on something to watch? Also have prime and Disney submitted by /u/sarcasticcheesecake [link] [comments]

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