Tag: Recommended New Netflix  Movies 2022

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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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Recommended New Netflix  Movies 2022

  • FMovies Shutdown? Discover the Best Alternatives: 345Movies, 456Movie, and More
    by Johnwho (Netflix on Medium) on September 14, 2024 at 7:50 am

    The shutdown of FMovies might leave a gap in your streaming routine, but don’t worry — there are fantastic alternatives available. Whether…Continue reading on Medium »

  • Officer Black Belt: Kim Woo-Bin shines as a Martial Arts Officer
    by Rupashi Chhabra (Netflix on Medium) on September 14, 2024 at 6:00 am

    This film is the most recent watch on my Netflix playlist. Since, the trailer aired I have been anticipating its release and rightfully so…Continue reading on Medium »

  • What Is Video Bitrate? Unveiling the Secret to Video Quality
    by AVCLabs Official (Netflix on Medium) on September 14, 2024 at 5:52 am

    This article explains what video bitrate is and how it affects video quality, revealing the secret to achieving better video performance.Continue reading on Medium »

  • 2024 : 15 Meilleurs Films à Regarder en Famille sur Netflix !
    by Joannetu (Netflix on Medium) on September 14, 2024 at 4:28 am

    Voici 15 des meilleurs films sur Netflix à regarder en famille, parfaits pour les familles de tous âges !Continue reading on Medium »

  • Help me find this….
    by /u/Plantlovr22 (Netflix) on September 14, 2024 at 2:36 am

    I watched this documentary or short form docuseries episode I can’t remember… and in it they discuss the Stanford prison experiment and how messed up that was, BUT then they recreate the experiment like with the assistance of professionals in the most ethical way possible and it doesn’t involve prison anymore. They are like trying to solve a puzzle against another team and they know about each other but can’t see each other and they have a buzzer that “sends a small non-harmful” shock to the other team (it didn’t actually) so they wanted to see if they’d initiate the shock. WHAT WAS THIS??? I CANNOT FIND IT ANYWHERE!! There is literally no way I could’ve made this up I have such detailed memories of this…. submitted by /u/Plantlovr22 [link] [comments]

  • Is "Into the Fire" the true story "Three Billboards Outside of Ebbing, Missouri" is based off?
    by /u/Atomicman4 (Netflix) on September 14, 2024 at 2:26 am

    I have done some research but can’t seem to find any connection. When Cathy mentions getting a billboard in the first episode it reminded me of this movie. The movie plays out a little differently though. She’s not adopted in the movie, the mother is a single mom, it all takes place in the same town and a few other differences. That being said I thought the use of billboards to force police action is pretty unique, and the character Frances McDormand plays is nearly identical to the real Cathy Terkanian. submitted by /u/Atomicman4 [link] [comments]

  • We need a sequel to Uglies!
    by /u/tajudson (Netflix) on September 14, 2024 at 2:21 am

    I just watched the movie, Joey King kills it. We need a sequel. Talk to as many people as you know, spread the word, make as many people as you can watch this movie! submitted by /u/tajudson [link] [comments]

  • What could be good for future "Monster" seasons?
    by /u/Downtown-Minute-8154 (Netflix) on September 14, 2024 at 2:20 am

    So with the Lyle and Erik Menendez series coming out soon (which I am excited about, it looks insane and it is probably going to ruin me since I saw some of their trial footage and I can never fully watch the Barbara Walters interview without wanting to jump through the computer or phone and yell at her), I heard allegedly season 3 of the show is going to be John Wayne Gacy, so I was thinking of some other true crime incidents that could happen out of this series. I'll say the case in the form of the title of the show and you let me know in the comments if you like the idea: "Monsters: The Tim Piazza and Beta Theta Chi Story" "Monster: The Sherri Papini Story" "Monster: The Bryan Kohberger Story" "Monsters: The Danny Santulli and Phi Gamma Delta Story" "Monsters: The Heaven's Gate Story" "Monster: The Chris Watts Story" "Monster: The Casey Anthony Story" Let me know what you think of some of these down below! submitted by /u/Downtown-Minute-8154 [link] [comments]

  • How to stop quality drops ?
    by /u/Zeroshiki-0 (Netflix) on September 14, 2024 at 2:01 am

    Does anyone know how to stop the quality from dropping to 240p ? I can't find anything online for this issue. I pay for the 4K plan, I have gigabit internet, and my TV (LG C1) is hardwired. I know this isn't on my end because this only happens with Netflix; the shows will sometimes play in 4K, but every time a camera angle changes the quality drops so much that I can't see anything. Usually lasts until the camera angle changes again, the scene ends, lighting changes, or when the show black screens, like where commercials/ads used to go. submitted by /u/Zeroshiki-0 [link] [comments]

  • Any binge-worthy series recommendations?
    by /u/GoldeeWrld (Netflix) on September 14, 2024 at 1:54 am

    Looking for a new series to get into this weekend! Had a rough week, so I kind of just want to be a coach potato for the next two days. Any recommendations would be appreciated. It might help if I mention what I've been watching as of late/my watch history: Grey's Anatomy. The Upshaws. Disjointed. The Lincoln Lawyer. You. Insecure. Martin. S.W.A.T. Blacklist. OITNB. The Family Business. Act Your Age. Good Girls. Wentworth. Girlfriends. submitted by /u/GoldeeWrld [link] [comments]

  • Ban profiles on devices?
    by /u/No_Philosophy_1363 (Netflix) on September 14, 2024 at 1:49 am

    Lately I’ve noticed my child watches their shows on my profile on their cellphone. Can I ban every profile but the “kids” profile specifically to their device? They have a 1 hour limit so it’s not like they’re watching movies all day. It’s usually just on the school bus. Please help me solve this issue. There are things on my profile i don’t want them seeing or being tempted to click on. submitted by /u/No_Philosophy_1363 [link] [comments]

  • Two separate Shaw internet accounts in the same household.
    by /u/Friendly_Goose6023 (Netflix) on September 14, 2024 at 1:46 am

    I'm moving back in my parents into the basement. The wifi doesn't work down here. Too expensive to hire an electrician to run the cables. Long story. I'm just going to buy my own internet. I'll call Rogers and they'll install my internet. So can I share Netflix with my family still? We are the same family living in the same house. But I'll be getting my own internet so does that show up to Netflix as a different household? I'm not tech savvy enough to even what what words to use here. Is IP address the right word? Will Netflix see a different IP if it's a separate Shaw internet account? Is there a way around it? I'm willing to show them all of our IDs and both of our internet bills showing it's the same house. Not trying to cheat the system here. It's legit easier to just buy my own internet than worry about cables or buying repeaters to get the signal to work. Plus being a gamer I don't want to rely on wifi. I need a cable and Shaw will install the cables if I buy my own internet. submitted by /u/Friendly_Goose6023 [link] [comments]

  • Live Streaming
    by /u/WillG316 (Netflix) on September 14, 2024 at 1:29 am

    Which Netflix plans include live streaming? WWE is moving to Netflix in January, & I can’t find any information on this. Does the Standard with ads plan for $6.99 include it?? submitted by /u/WillG316 [link] [comments]

  • Is CLOY dubbed in English? Weird experience with Netflix...
    by /u/kangaruurunner (Netflix) on September 14, 2024 at 1:17 am

    submitted by /u/kangaruurunner [link] [comments]

  • I can’t find a good show!!!!!
    by /u/Spiritual_Advance_59 (Netflix) on September 14, 2024 at 1:14 am

    I been struggling to find a good show, after I have finally gotten tired of The Office/brklyn 99. Long time coming. But I thought I finally found my show, the show to finally past the time with, Dexter. But I find myself in the middle of season 6 struggling to watch 5 min of an episode. Why? Any good show suggestions? I recently got the og SpongeBob, so I blame that. Maybe I just cannot comprehend a deeper show, I get bored. 10 min episodes that shut off my brain, I think ruined me. I think I ruined it for myself. Also Spongebob( first 4 seasons) don't last forever. Thanks submitted by /u/Spiritual_Advance_59 [link] [comments]

  • Netflix's 'Uglies': What the film & its characters represent, according to Keith Powers, Laverne Cox and more
    by /u/Icy-Obligation-3657 (Netflix) on September 14, 2024 at 1:10 am

    submitted by /u/Icy-Obligation-3657 [link] [comments]

  • What’s your “ONE?”
    by /u/jolietfake (Netflix) on September 14, 2024 at 12:42 am

    My Netflix subscription is ending Sunday and I’m pretty sick and gonna be in bed for the weekend it seems. Got me thinking… If you only had 2ish days to watch ONE series on Netflix, what would it be?? (For the sake of this game this is Netflix only, maybe it doesn’t matter if watching the actual series will take you more than 2 days but most importantly ONLY ANSWER WITH ONE TITLE. Restraint is hard.) Mine: AFTER LIFE submitted by /u/jolietfake [link] [comments]

  • Loved Uglies, Hoping for Pretties!
    by /u/Capzielios (Netflix) on September 14, 2024 at 12:42 am

    My partner and I both read the Uglies series as kids and are attached to the books. The movie that came out was a genuinely good adaptation of the book and we're both hoping to see the sequel at some point! If anyone hasn't read the books, nowadays it's not the most revolutionary tale. But it was really good for the time. And the movie followed the book closely and came all the characters true to how the book interprets them. It's the best that I think most fans could ask for. Anyways, I'd love to hear ya'lls opinions on it too! submitted by /u/Capzielios [link] [comments]

  • Gölgelerin gücü adına : Caravaggio & Ripley
    by sulekain (Netflix on Medium) on September 13, 2024 at 10:28 pm

    Sanatın çeşitli formları arasında, sinema ve resim en etkileyici görsel ifade araçlarındandır. Her ikisi de izleyicilerine derin duygusal…Continue reading on Medium »

  • Top 10 English Titles 1st Week of Sep 2024
    by /u/iPhone13pm (Netflix) on September 13, 2024 at 9:58 pm

    submitted by /u/iPhone13pm [link] [comments]

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