netflix 數(shù)據(jù)科學(xué)家

數(shù)據(jù)科學(xué) ， 機(jī)器學(xué)習(xí) ， 技術(shù) (Data Science, Machine Learning, Technology)

Using data science, Netflix has surpassed its competition and now has over 100 million users globally. Data science helps Netflix keep track of all your likes and dislikes to make sure you’re satisfied.

借助數(shù)據(jù)科學(xué)，Netflix超越了競(jìng)爭(zhēng)對(duì)手，目前在全球擁有超過1億用戶。 數(shù)據(jù)科學(xué)可幫助Netflix跟蹤您的所有好惡，以確保您滿意。

, Photo by ， fauxels from Pexels的Pexelsfauxels攝影

這個(gè)概念 (The Concept)

Data science is a combination of tools, algorithms, and machine learning principles that help users gain functional and beneficial patterns from raw data. A data scientist can identify future occurrences of an event by using advanced machine learning algorithms. The Internet of Things (IoT) has given rise to the fundamentals of data science, making it the most valuable resource for all companies today.

數(shù)據(jù)科學(xué)是工具，算法和機(jī)器學(xué)習(xí)原理的組合 ，可幫助用戶從原始數(shù)據(jù)中獲得功能性和有益的模式。 數(shù)據(jù)科學(xué)家可以使用高級(jí)機(jī)器學(xué)習(xí)算法來確定事件的未來發(fā)生。 物聯(lián)網(wǎng)(IoT)引起了數(shù)據(jù)科學(xué)的基礎(chǔ)知識(shí)，使其成為當(dāng)今所有公司最有價(jià)值的資源 。

目的 (The Aim)

Netflix has always strived to improve User Interface at all levels. Their primary goal is to add Contextual Awareness to their recommendations. It means that the proposals should have high logical reasoning behind them. As per DataFlair, two types of contextual classes are relevant to Netflix.

Netflix一直在努力改善所有級(jí)別的用戶界面 。 他們的主要目標(biāo)是在他們的建議中增加上下文意識(shí) 。 這意味著這些建議應(yīng)在其背后具有較高的邏輯推理性。 根據(jù)DataFlair ，兩種類型的上下文類與Netflix有關(guān)。

1.明確 (1. Explicit)

● Location

●位置

● Language

●語(yǔ)言

● Time of the Day

●一天中的時(shí)間

● Device

●設(shè)備

2.推斷 (2. Inferred)

● Binging Patterns

●結(jié)合方式

● Companion

●同伴

User Interface at all levels, Photo by 用戶界面 ， energepic.com from Pexels的Pexelsenergepic.com攝

應(yīng)用程序 (The Application)

Netflix has used data science to ensure that users enjoy value for money. With the help of various Analytical Tools, the Streaming Giant identifies the liking and proclivity of users and directs them towards similar options. A study suggests that recommendations influence more than 80% of all streamed content on Netflix.

Netflix利用數(shù)據(jù)科學(xué)來確保用戶享受金錢的價(jià)值 。 在各種分析工具的幫助下，Streaming Giant可以識(shí)別用戶的喜好和傾向并將其引導(dǎo)至相似的選項(xiàng)。 一項(xiàng)研究表明，推薦影響Netflix上所有流媒體內(nèi)容的80％以上。

Netflix does not use the conventional Hadoop warehouse. It instead uses an upgraded Data Storage System, Amazon’s S3. It allows it to spin more Hadoop clusters for work bases accessing the same Data. It uses Hive for Ad hoc queries and Analytics/PIG for ETL (Extract, transform, load)

Netflix不使用傳統(tǒng)的Hadoop倉(cāng)庫(kù)。 相反，它使用升級(jí)的數(shù)據(jù)存儲(chǔ)系統(tǒng)Amazon的S3 。 它允許它為訪問相同數(shù)據(jù)的工作基地旋轉(zhuǎn)更多的Hadoop集群。 它使用Hive進(jìn)行臨時(shí)查詢，并使用Analytics / PIG進(jìn)行ETL(提取，轉(zhuǎn)換，加載)

數(shù)據(jù) (The Data)

To begin their Analysis, Netflix gathers Raw Fata, from which it plans to extract resourceful information using Data Science Algorithms. A combination of these algorithms transforms plain numbers to a detailed Recommendation Plan. For every 5 minutes a user spends on scrolling, Netflix can predict more than 40% of their relative selection patterns. There are several fields on Netflix, where Data is collected, captured, and stored.

為了開始進(jìn)行分析，Netflix收集了Raw Fata，并計(jì)劃使用Data Science算法從中提取資源豐富的信息。 這些算法的組合將素?cái)?shù)轉(zhuǎn)換為詳細(xì)的推薦計(jì)劃。 用戶每花5分鐘滾動(dòng)一次，Netflix就可以預(yù)測(cè)其相對(duì)選擇模式的40％以上。 Netflix上有幾個(gè)字段，用于收集，捕獲和存儲(chǔ)數(shù)據(jù)。

● Time: The primary step is to understand and store the Time and Date when users stream content. It helps them identify your Sunday night-horror movie plans or your Afternoon-thriller preferences.

●時(shí)間：第一步是了解和存儲(chǔ)用戶流式傳輸內(nèi)容時(shí)的時(shí)間和日期。 它可以幫助他們確定您的周日夜間恐怖電影計(jì)劃或您的下午驚悚片偏好。

● Searches: All Search Titles are automatically stored to re-direct further recommendations towards these searches. Let’s say you search “John Wick,” watch the movie and close Netflix. The next time you switch the application back on, you will undoubtedly find more Action movies or more Keanu Reeves starters.

●搜索：將自動(dòng)存儲(chǔ)所有搜索標(biāo)題，以將更多建議重定向到這些搜索。 假設(shè)您搜索“ John Wick ”，觀看電影并關(guān)閉Netflix。 下次您重新打開該應(yīng)用程序時(shí)，無疑會(huì)找到更多的動(dòng)作電影或更多的Keanu Reeves起動(dòng)器。

● Browsing and scrolling behavior: Netflix also uses Advanced Analytical programs to identify which Movie/TV show you decided to stop and read about. It helps them showcase more similar content to catch your eye and get you interested again.

●瀏覽和滾動(dòng)行為：Netflix還使用Advanced Analytical程序來確定您決定停止并閱讀的電影/電視節(jié)目。 它可以幫助他們展示更多類似的內(nèi)容，以引起您的注意并再次引起您的興趣。

● Pause/Fast-forward: Using Data Science, Netflix catches the exact durations where a user starts Pausing or Fast-forwarding while streaming content. It helps it identify what kind of scenes are preferred over others. If you skip an action movie’s emotional scene, it develops the algorithm to avoid passionate movies in future recommendations. But if you re-watch an emotional scene, it will adapt accordingly.

●暫停/快進(jìn)：使用數(shù)據(jù)科學(xué)，Netflix可以捕獲用戶在流式傳輸內(nèi)容時(shí)開始暫停或快進(jìn)的確切時(shí)長(zhǎng)。 它有助于確定哪種場(chǎng)景比其他場(chǎng)景更受青睞。 如果您跳過動(dòng)作片的情感場(chǎng)景，它會(huì)開發(fā)出避免在以后的推薦中出現(xiàn)激情片的算法。 但是，如果您重新觀看一個(gè)情感場(chǎng)景，它將相應(yīng)地進(jìn)行調(diào)整。

● A device used: If you use separate mechanisms to stream different content, this differentiation is stored permanently. For example, Children watching cartoons on the home-TV will not be recommended movies watched by their parents on the iPad, despite using the same account.

●使用的設(shè)備：如果使用單獨(dú)的機(jī)制來流傳輸不同的內(nèi)容，則此差異將被永久存儲(chǔ)。 例如，即使使用相同的帳戶，也不會(huì)推薦父母在iPad上觀看家庭電視上觀看動(dòng)畫片的兒童觀看的電影。

To begin their Analysis, Netflix gathers Raw Fata, from which it plans to extract resourceful information using Data Science Algorithms, Photo by Lukas from Pexels為了開始進(jìn)行分析，Netflix收集了Raw Fata，并計(jì)劃使用Data Science算法從中提取資源豐富的信息， Pexels的Lukas 攝

該項(xiàng)目 (The Project)

Netflix uses Data at all levels possible. From the time it a user logs in to log out, it stores all possible information it needs. It then channels these Data to bring out actionable information. The most famous story of Netflix’s marketing is how they purchased the “House of Cards” series. The series, starred by Kevin Spaced and directed by David Fincher, was one of the biggest blockbuster hits. More than a hundred million dollars was incurred to purchase this TV series, for several reasons.

Netflix盡可能使用數(shù)據(jù)。 從用戶登錄到注銷開始，它就存儲(chǔ)了所需的所有可能的信息。 然后，它會(huì)引導(dǎo)這些數(shù)據(jù)以帶出可操作的信息 。 Netflix營(yíng)銷最著名的故事是他們?nèi)绾钨?gòu)買“ 紙牌屋 ”系列。 該系列由凱文·斯派西德(Kevin Spaced)主演，由大衛(wèi)·芬奇(David Fincher)執(zhí)導(dǎo)，是最熱門的大片之一。 購(gòu)買該電視連續(xù)劇的費(fèi)用超過一億美元 ，原因有幾個(gè)。

● Netflix identified a vast fan base for Actor Kevin Spacey, who has acted in movies such as 21 and American Beauty.

●Netflix為演員凱文·斯派西(Kevin Spacey)確定了龐大的粉絲群，他曾出演過21電影和《美國(guó)美女》等電影。

● It also did a background check about Trending and Popular movies on their platform. Movies like Fight Club and The Social Network were highly rated and viewed by their audience, all directed by the renowned David Fincher.

●它還對(duì)平臺(tái)上的熱門電影和熱門電影進(jìn)行了背景檢查。 像《 搏擊俱樂部》和《社交網(wǎng)絡(luò)》這樣的電影獲得了觀眾的高度評(píng)價(jià)和觀看，全部由著名的大衛(wèi)·芬徹執(zhí)導(dǎo)。

● Netflix also viewed the statistics of the British version of the series, that was earlier released. The UK version received due appreciation by its target audience, which boosted its stance.

●Netflix還查看了早先發(fā)行的該系列英國(guó)版本的統(tǒng)計(jì)信息。 英國(guó)版受到其目標(biāo)受眾的應(yīng)有贊賞，這增強(qiáng)了其立場(chǎng)。

● The Political Drama Genre was one of their most active genres, with movies like Elizabeth I: The Virgin Queen and Winnie Mandela, doing rounds on their website.

●政治戲劇類型是他們最活躍的類型之一，像伊麗莎白一世(Elizabeth I：The Virgin Queen)和溫妮·曼德拉(Winnie Mandela)等電影在其網(wǎng)站上進(jìn)行巡回演出。

Using programmable algorithms, all factors were linked to a pattern, making Netflix spend the big bucks on House of Cards. The series then became a massive hit and climbed to the #1 position on their trending charts, making it a successive and profitable Analysis.

使用可編程算法 ，所有因素都與一種模式相關(guān)聯(lián)，從而使Netflix在“紙牌屋”上花了大錢。 該系列隨后大受歡迎，并在其趨勢(shì)圖上攀升至第一位，使其成為連續(xù)且盈利的分析。

Netflix identified a vast fan base for Actor Kevin Spacey, who has acted in movies such as 21 and American Beauty, Photo by Bich Tran from PexelsNetflix公司確定了演員凱文斯派西，誰(shuí)在電影中，如21行動(dòng)和美國(guó)麗人，照片龐大粉絲群的碧陳德良從Pexels

好處 (The Benefits)

Why would a company like Netflix, having a Market Monopoly, spend their time on Data Science? The answer is Consumer Retention. It is crucial to attracting new customers while retaining the current batch. Using Data Analysis tools, users of Netflix have preferred its platform over other service providers such as Hotstar and Amazon Prime. Netflix has beautifully driven millions of users towards its platform, achieving 20 Billion Dollars in revenue in 2019.

為什么像Netflix這樣擁有市場(chǎng)壟斷地位的公司花時(shí)間在數(shù)據(jù)科學(xué)上 ？ 答案是消費(fèi)者保留。 在保留當(dāng)前批次的同時(shí)吸引新客戶至關(guān)重要。 使用數(shù)據(jù)分析工具，Netflix的用戶比其他服務(wù)提供商(例如Hotstar和Amazon Prime)更喜歡其平臺(tái)。 Netflix吸引了數(shù)百萬用戶使用其平臺(tái)，在2019年實(shí)現(xiàn)了200億美元的收入。

結(jié)果 (The Outcome)

Netflix gained more than 3.1 Million followers on its platform after the release of House of Cards; this addition was majorly gained from the US streamers. It helped Netflix in plenty of ways.

在紙牌屋發(fā)布之后，Netflix在其平臺(tái)上吸引了310萬追隨者; 這種增加主要來自美國(guó)的彩帶。 它以多種方式幫助了Netflix。

● Revenue: Newly subscribed users added more than 72.5 Million Dollars in Revenue for Netflix. It was more than 75% of the combined investment Netflix made to air both seasons of the show.

●收入：新訂閱用戶為Netflix增加了超過7250萬美元的收入。 這是該節(jié)目?jī)蓚€(gè)季度Netflix播出的總投資的75％以上。

● Word of Mouth: Adding high users and tending to their needs using Data Science helped Netflix gain even more popularity globally. It also led to the sequential addition of users through referrals, expanding, and creating further growth opportunities.

●口口相傳：使用數(shù)據(jù)科學(xué)增加高用戶群并滿足他們的需求有助于Netflix在全球范圍內(nèi)獲得更大的普及。 它還通過推薦 ，擴(kuò)展和創(chuàng)造進(jìn)一步的增長(zhǎng)機(jī)會(huì)而導(dǎo)致用戶的順序添加。

顯示器 (The Display)

Every section on Netflix’s home page is unique to its user’s account. Each chapter is displayed based on a vast set of Data collected, combined to produce the most relevant recommendations.

Netflix主頁(yè)上的每個(gè)部分對(duì)于其用戶帳戶都是唯一的。 每章都是根據(jù)收集的大量數(shù)據(jù)進(jìn)行顯示的，并結(jié)合起來產(chǎn)生最相關(guān)的建議。

1.趨勢(shì)： (1. Trending:)

The Trending section is formatted according to the Location and preferences of the user. Chris Hemsworth’s Extraction was on the top of the Trending list in India, just after its release. Every user in India who had viewed action-based content or Chris Hemsworth’s movies was recommended Extraction.

根據(jù)用戶的位置和偏好設(shè)置“趨勢(shì)”部分的格式。 克里斯赫姆斯沃思的提取是在印度的趨勢(shì)列表的頂部，只是其發(fā)布后。 在印度每個(gè)用戶誰(shuí)曾看到基于行動(dòng)的內(nèi)容或克里斯赫姆斯沃思的電影推薦提取 。

Netflix gained more than 3.1 Million followers on its platform after the release of House of Cards, Image by Jorge Gryntysz from PixabayNetflix公司獲得了其平臺(tái)上超過310萬周的追隨者卡，圖像的眾議院版本由后豪爾赫Gryntysz從Pixabay

2.繼續(xù)觀看 (2. Continue Watching)

This section is a set of collective content that a User has begun streaming, but has left unfinished. Pause durations are stored to start streaming the content on the exact scene on which it has been paused/terminated before.

此部分是用戶已開始流式傳輸?shù)赐瓿傻囊唤M集體內(nèi)容。 暫停持續(xù)時(shí)間將被存儲(chǔ)，以開始在之前已被暫停/終止的確切場(chǎng)景上流式傳輸內(nèi)容。

3.類型內(nèi)容 (3. Genre Content)

If the user frequently indulges in viewing Action movies, A section will be separately created named “Violent Movies.” This section will contain all popular Action Movies that have plenty of Violent scenes. If a user watches shows like Money Heist (A top-rated show dealing with thieves in Spain), they will find an additional section named “Risk-Taker and Rule-Breaker TV” on their Home Page.

如果用戶經(jīng)常沉迷于觀看動(dòng)作電影，則將單獨(dú)創(chuàng)建一個(gè)名為“暴力電影”的部分。 本部分將包含所有具有暴力場(chǎng)景的流行動(dòng)作片。 如果用戶觀看了諸如Money Heist之類的節(jié)目(這是西班牙處理盜賊的最佳節(jié)目)，他們將在其主頁(yè)上找到一個(gè)名為“ Risk-Taker and Rule-Breaker TV”的附加欄目。

4.因?yàn)槟憧戳?(4. Because You Watched)

There is also a combination section, where all other Data is factored in. Suppose a User watched the Movie Polar, a new part called “Because you watched Polar” will be created, containing other movies of the Same genre, Actors, Directors, and Producers.

還有一個(gè)組合部分，其中包含所有其他數(shù)據(jù)。假設(shè)用戶觀看了電影Polar，將創(chuàng)建一個(gè)名為“因?yàn)槟^看了Polar”的新部分，其中包含相同類型，演員，導(dǎo)演和其他電影的其他電影生產(chǎn)者。

Netflix aims at making people wonder how it always has a ready-made list that will entertain them. Every Pause, Scroll, and Log-in time is used to enhance User Interface in the best way possible.

Netflix的目的是讓人們懷疑它總是有一個(gè)現(xiàn)成的列表來娛樂他們。 每次暫停，滾動(dòng)和登錄時(shí)間都用于以最佳方式增強(qiáng)用戶界面 。

Netflix aims at making people wonder how it always has a ready-made list that will entertain them, Photo by Stas Knop from PexelsNetflix的目標(biāo)是讓人們懷疑它總是有一個(gè)現(xiàn)成的列表來娛樂他們， Pexels的Stas Knop 攝

測(cè)試 (The Testing)

Netflix always conducts Background Testing at scale to understand the functionality of their Data analysis-driven recommendations. The Results and Statistics from these Tests determine whether a set of algorithms should be widely introduced in their platforms globally.

Netflix始終進(jìn)行大規(guī)模的背景測(cè)試 ，以了解其以數(shù)據(jù)分析為依據(jù)的建議的功能。 這些測(cè)試的結(jié)果和統(tǒng)計(jì)數(shù)據(jù)決定了是否應(yīng)在其全球平臺(tái)上廣泛引入一組算法。

基于交錯(cuò)的個(gè)性化 (Personalization Based on Interleaving)

Netflix conventionally followed the A/B testing policy, where two sets of reduced algorithms were tested on two different sets of samples. The results of these tests were based on how accurately the recommendation section appealed to the target samples. This method was subsequently scrapped because of its implausibility.

Netflix一直遵循A / B測(cè)試政策 ，即在兩組不同的樣本上測(cè)試兩組簡(jiǎn)化算法。 這些測(cè)試的結(jié)果基礎(chǔ)上，建議部分如何準(zhǔn)確地上訴到目標(biāo)樣本。 此方法由于其難以置信而隨后被廢棄。

Netflix adopted a new method of Testing. In this testing method, Netflix decided to infuse Interleaving of Algorithms to decide on the best Page Ranking Algorithm for improving User Interface. This method benefited the American Media Service Provider in many ways.

Netflix采用了一種新的測(cè)試方法。 在這種測(cè)試方法中，Netflix決定注入算法交織來確定最佳的頁(yè)面排名算法，以改善用戶界面。 這種方法使美國(guó)媒體服務(wù)提供商從許多方面受益。

Interleaving of Algorithms to decide on the best Page Ranking Algorithm for improving User Interface, Image by 交織 ，以決定用于改善用戶界面的最佳頁(yè)面排名算法。作者： Michal Jarmoluk from Michal PixabayJarmoluk

● Cost-friendly: Interleaving involves blending, which means Netflix carried out two tests for the price of one. Background testing involves a significant amount of Cost, which was saved using this method.

●成本低廉：交織涉及融合，這意味著Netflix以一項(xiàng)價(jià)格進(jìn)行了兩項(xiàng)測(cè)試。 后臺(tái)測(cè)試涉及大量Cost ，使用此方法可以節(jié)省這些費(fèi)用 。

● Time-saving: Combining two testing methods into one saves time to work on other matters and quickly gives out the results. We all know that Time is Money; hence, this is considered as a more suitable and profitable choice of Testing.

●節(jié)省時(shí)間：將兩種測(cè)試方法合而為一，可以節(jié)省處理其他問題的時(shí)間并快速給出結(jié)果。 我們都知道時(shí)間是金錢 ; 因此，這被認(rèn)為是一種更合適，更有利可圖的測(cè)試選擇。

重要性 (The Importance)

As the world moves into the future, digitization has been normalized by all. The inflow of Users on the Internet is continually growing in large numbers. It has created a heated environment filled with intense competition among Media Service Providers like Netflix and Amazon Prime.

隨著世界走向未來，數(shù)字化已被所有人規(guī)范化。 Internet上的用戶流入量持續(xù)大量增長(zhǎng)。 它創(chuàng)造了一個(gè)激烈的環(huán)境，充滿了像Netflix和Amazon Prime這樣的媒體服務(wù)提供商之間的激烈競(jìng)爭(zhēng) 。

1.參與度： (1. Engagement:)

Data Science helps Netflix to increase the participation of users powerfully and creatively. Using Analytics, a virtual rapport between the user and the Service provider is created. Netflix aims at exploiting this rapport with their Market Share advantage.

數(shù)據(jù)科學(xué)幫助Netflix強(qiáng)大而有創(chuàng)意地增加了用戶的參與度。 使用Analytics(分析)，可以在用戶和服務(wù)提供商之間建立虛擬的融洽關(guān)系 。 Netflix旨在利用其市場(chǎng)份額優(yōu)勢(shì)來發(fā)展這種融洽關(guān)系。

2.解決方案： (2. Solution:)

Netflix aims at using Data Science as a go-to for problem-solving. There are plenty of problems that Data Science can help with.

Netflix旨在將數(shù)據(jù)科學(xué)作為解決問題的捷徑 。 數(shù)據(jù)科學(xué)可以解決很多問題。

● Low reach: Recommendations on Netflix can improve the view count on overlooked content. It helps Netflix to keep its audience engaged on its platform.

●觸及率低：Netflix上的建議可以提高被忽略內(nèi)容的觀看次數(shù)。 它可以幫助Netflix保持觀眾對(duì)平臺(tái)的關(guān)注。

● Feedback and Ratings: Analytical programs and Probability models help Netflix average a cluster of User Ratings to categorize content, based on its ability to impress.

●反饋和評(píng)分：分析程序和概率模型可幫助Netflix根據(jù)其印象深刻的能力對(duì)一組用戶評(píng)分進(jìn)行平均，以對(duì)內(nèi)容進(jìn)行分類。

● Policy Control: Netflix has a strict policy that discourages the sharing of a single account by multiple people. Netflix allows up-to five Individual Profiles to access the website using one account. Using Data Science governs the Devices used for log-ins from the same accounts to avoid a breach.

●策略控制：Netflix具有嚴(yán)格的策略，不鼓勵(lì)多人共享一個(gè)帳戶。 Netflix允許多達(dá)五個(gè)個(gè)人檔案使用一個(gè)帳戶訪問該網(wǎng)站。 使用Data Science可以控制用于從同一帳戶登錄的設(shè)備，以避免違規(guī)。

rapport between the user and the Service provider is created. 融洽關(guān)系 。 Netflix aims at exploiting this rapport with their Netflix的目標(biāo)是利用這種關(guān)系有其Market Share advantage, Video by 市場(chǎng)份額的優(yōu)勢(shì)，視頻由BUMIPUTRA from 土著從PixabayPixabay

● Innovation and Efficiency: The critical quality of Data Science is that it never runs out of fashion. Machine learning continually adapts to the present, uses previously-stored Data available at present to predict future outcomes. Efficiency for Netflix would mean to deliver the right content to the right user.

●創(chuàng)新和效率：數(shù)據(jù)科學(xué)的關(guān)鍵素質(zhì)是它永遠(yuǎn)不會(huì)過時(shí)。 機(jī)器學(xué)習(xí)不斷適應(yīng)當(dāng)前情況，使用當(dāng)前可用的先前存儲(chǔ)的數(shù)據(jù)來預(yù)測(cè)未來的結(jié)果。 Netflix的效率意味著向正確的用戶提供正確的內(nèi)容。

● Decision making: Gathering Data to make decisions is not the mantra to success. The mantra lies in mastering Analytics to use the Data and channel it in the right direction. Netflix has used Data Science to identify the appropriate opportunities and paths available.

●決策：收集數(shù)據(jù)來制定決策不是成功的咒語(yǔ)。 口頭禪在于掌握Analytics(分析)以使用數(shù)據(jù)并按正確的方向進(jìn)行引導(dǎo)。 Netflix已使用數(shù)據(jù)科學(xué)來確定適當(dāng)?shù)臋C(jī)會(huì)和可用路徑。

● Personalization: In a commercial market where the physical sale is conducted, a consumer can ask for personalized products, test it, and purchase it. Data Science has helped Netflix stretch its range to meet all the customized demands of the public.

●個(gè)性化：在進(jìn)行實(shí)物銷售的商業(yè)市場(chǎng)中，消費(fèi)者可以要求個(gè)性化產(chǎn)品，進(jìn)行測(cè)試并購(gòu)買。 數(shù)據(jù)科學(xué)幫助Netflix擴(kuò)展了其范圍，以滿足公眾的所有定制需求。

For a consumer, a sense of satisfaction is met when the correct product is available at the right time and place, for the right price. Netflix has made its users’ lives more convenient by providing high-quality, relevant content at their fingertips.

對(duì)于消費(fèi)者而言，當(dāng)在正確的時(shí)間和地點(diǎn)以正確的價(jià)格獲得正確的產(chǎn)品時(shí)，就會(huì)感到滿足感。 Netflix通過提供觸手可及的高質(zhì)量相關(guān)內(nèi)容，使用戶的生活更加便捷 。

結(jié)論 (The Conclusion)

It all comes down to one question:

歸結(jié)為一個(gè)問題：

Based on the historical actions taken by a user and the data available, what is the most probable video a user will play right now?

根據(jù)用戶的歷史操作和可用數(shù)據(jù)，用戶現(xiàn)在最可能播放的視頻是什么？

Netflix aims at using Data Science as a go-to for problem-solving. There are plenty of problems that Data Science can help with., Photo by Dominika Roseclay from PexelsNetflix旨在將數(shù)據(jù)科學(xué)作為解決問題的捷徑 。 數(shù)據(jù)科學(xué)可以解決很多問題。，來自Pexels的Dominika Roseclay 攝

The list of recommendations can be prepared within seconds using Probability Models and Analytical Programs. Data science has become an integral part of the growing world. It has built the foundation on which companies like Netflix and more will develop their future. Netflix has minimized its scope for errors, enhanced User Interface, and boosted User Engagement.

可以使用概率模型和分析程序在幾秒鐘內(nèi)準(zhǔn)備好建議列表。 數(shù)據(jù)科學(xué)已成為成長(zhǎng)中世界不可或缺的一部分。 它為Netflix等公司和更多公司發(fā)展未來奠定了基礎(chǔ)。 Netflix 最大限度地減少了出錯(cuò)的范圍 ， 增強(qiáng)了用戶界面 ，并增強(qiáng)了用戶參與度 。

I`ve always taken life as a journey from one experience to another. So far it has been a road full of interesting events and people. Join me on my Journey through LinkedIn, Instagram & Youtube

我一直把生活視為從一種經(jīng)歷到另一種經(jīng)歷的旅程。 到目前為止，這條路充滿了有趣的事件和人們。 通過 LinkedIn ， Instagram 和 Youtube 加入我的旅程

Once in action, decision-making seems like an easy task. But it requires creative workers, using high-end tools to create solutions adaptable across all verticals. Netflix holds a dominating market share and is crowned as “HBO of Internet Tv.” The success of any platform on the World Wide Web can’t come without a strong foundation. Without Data Science, companies would be stuck with unfiltered clusters of Databases, with no clue how they will proceed further.

一旦采取行動(dòng)，決策似乎是一件容易的事。 但是，這需要?jiǎng)?chuàng)意工作者使用高端工具來創(chuàng)建適用于所有行業(yè)的解決方案。 Netflix擁有主要的市場(chǎng)份額，并被冠以“ 互聯(lián)網(wǎng)電視的HBO”之稱 。 互聯(lián)網(wǎng)上任何平臺(tái)的成功都離不開堅(jiān)實(shí)的基礎(chǔ) 。 沒有數(shù)據(jù)科學(xué)，公司將被困在未經(jīng)過濾的數(shù)據(jù)庫(kù)集群中 ，而沒有任何線索進(jìn)一步發(fā)展。

Every person must ask themselves whether Data Analytics will improve their business or not? Netflix did it, so should you.

每個(gè)人都必須問自己，Data Analytics是否會(huì)改善他們的業(yè)務(wù)？ Netflix做到了，您也應(yīng)該這樣做。

With all the information at hand, you are hopefully prepared to become a successful Data Scientist in the future. Hope this helps and all the best for your future endeavors! Thanks for reading this article! Leave a comment below if you have any questions.

掌握了所有信息，您有望將來成為一名成功的數(shù)據(jù)科學(xué)家。 希望這對(duì)您的未來有所幫助，并祝一切順利！ 感謝您閱讀本文！ 如有任何疑問，請(qǐng)?jiān)谙旅姘l(fā)表評(píng)論。

翻譯自: https://medium.com/towards-artificial-intelligence/applications-of-data-science-and-machine-learning-in-netflix-dcdf6abbb194

netflix 數(shù)據(jù)科學(xué)家

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