{"id":13418,"date":"2023-04-05T09:29:31","date_gmt":"2023-04-05T06:29:31","guid":{"rendered":"https:\/\/www.openenglish.com.tr\/blog\/?p=13418"},"modified":"2024-06-13T16:48:34","modified_gmt":"2024-06-13T13:48:34","slug":"veri-bilimcileri-icin-ingilizce-kelimeler","status":"publish","type":"post","link":"https:\/\/www.openenglish.com.tr\/blog\/veri-bilimcileri-icin-ingilizce-kelimeler\/","title":{"rendered":"Veri Bilimcileri \u0130\u00e7in \u0130ngilizce Kelimeler"},"content":{"rendered":"

Veri bilimi, verilerin analizi ve yorumlanmas\u0131 yoluyla bilgiye d\u00f6n\u00fc\u015ft\u00fcr\u00fclmesi s\u00fcrecidir. Veri biliminde, b\u00fcy\u00fck veri k\u00fcmeleri kullan\u0131larak istatistiksel y\u00f6ntemler, makine \u00f6\u011frenme algoritmalar\u0131 ve veri madencili\u011fi teknikleri gibi ara\u00e7lar kullan\u0131l\u0131r. Veri bilimi, bir\u00e7ok alanda kullan\u0131labilir, \u00f6rne\u011fin; i\u015fletme, sa\u011fl\u0131k, m\u00fchendislik ve sosyal bilimler gibi.\u00a0<\/span><\/p>\n

Veri bilimci ise, veri biliminde uzmanla\u015fm\u0131\u015f bir ki\u015fidir. Veri bilimcileri, verileri toplamak, analiz etmek, yorumlamak ve raporlamak i\u00e7in teknikler kullan\u0131rlar. Bu ki\u015filer ayn\u0131 zamanda, verileri anlaml\u0131 hale getirecek modeller ve algoritmalar olu\u015fturarak, i\u015fletmelere daha iyi kararlar vermelerine yard\u0131mc\u0131 olurlar.\u00a0<\/span><\/p>\n

Veri bilimcileri; veri tabanlar\u0131, programlama dilleri ve istatistik bilgisi gibi teknik becerilere sahiptirler. Veri bilimcileri i\u00e7in \u0130ngilizce \u00f6nemli mi diye merak ediyor olabilirsin. Yaz\u0131m\u0131z\u0131n devam\u0131nda veri bilimcileri i\u00e7in i\u015f \u0130ngilizcesi<\/a><\/strong><\/em> ve \u0130ngilizce bilmenin \u00f6nemli olup olmad\u0131\u011f\u0131n\u0131 \u00f6\u011frenece\u011fine emin olabilirsin.<\/span><\/p>\n

\u0130ngilizce Veri Bilimi Nedir?<\/strong><\/h2>\n

Veri bilimciler i\u00e7in \u0130ngilizce kelimeleri s\u0131ralamadan \u00f6nce \u0130ngilizce veri biliminin ne demek oldu\u011funu seninle payla\u015fmak istedik. Verilerin analizi i\u00e7in \u00e7al\u0131\u015fan veri biliminin \u0130ngilizce kar\u015f\u0131l\u0131\u011f\u0131 data science olarak biliniyor.\u00a0<\/span><\/p>\n

Bir\u00e7ok uygulaman\u0131n bir arada bulundu\u011fu ve birlikte \u00e7al\u0131\u015ft\u0131\u011f\u0131 veri bilimi i\u015fini yapan ki\u015filere veri\u00a0 bilimci ya da veri bilimi uzman\u0131 deniyor. Veri bilimciler i\u00e7in \u0130ngilizcede kullan\u0131lan ad ise literat\u00fcrde, data scientist olarak kar\u015f\u0131m\u0131za \u00e7\u0131k\u0131yor.<\/span><\/p>\n

\u0130ngilizcede data science ya da data scientist gibi bir\u00e7ok kavram var. Bu kavramlar\u0131 \u00f6\u011frenme iste\u011fine sahipsen, bu sayfada yer alan ileti\u015fim formunu doldurabilirsin. Formu doldurduktan sonra seni aramam\u0131z\u0131 ve sana,<\/span> online \u0130ngilizce kursu<\/a><\/strong><\/em>\u00a0hakk\u0131nda bilgiler sunmam\u0131z\u0131 bekleyebilirsin.<\/span><\/p>\n

\"veri<\/p>\n

Veri Bilimciler \u0130\u00e7in \u0130ngilizce Gerekli mi?<\/strong><\/h2>\n

Veri bilimcileri i\u00e7in \u0130ngilizce, k\u00fcresel bir disiplin olan veri bilimi alan\u0131nda \u00e7al\u0131\u015fanlar i\u00e7in olduk\u00e7a \u00f6nemlidir. Veri bilimi, farkl\u0131 \u00fclkelerden ve farkl\u0131 dillerden insanlar\u0131n kat\u0131l\u0131m\u0131yla olu\u015fan bir aland\u0131r ve genellikle \u0130ngilizce olarak yay\u0131nlanan makaleler ve kaynaklar \u00fczerinden \u00e7al\u0131\u015f\u0131l\u0131r. <\/span><\/p>\n

Ayr\u0131ca, veri bilimiyle ilgili \u00e7o\u011fu ara\u00e7 ve teknolojinin \u0130ngilizce dilinde belgelendirildi\u011fi ve \u0130ngilizce olarak kullan\u0131ld\u0131\u011f\u0131 d\u00fc\u015f\u00fcn\u00fcld\u00fc\u011f\u00fcnde, \u0130ngilizce bilmek veri bilimcileri i\u00e7in olduk\u00e7a faydal\u0131d\u0131r.\u00a0<\/span><\/p>\n

Veri bilimcileri, i\u015flerinde \u0130ngilizce bilgilerini kullanarak yeni teknolojileri ve ara\u00e7lar\u0131 takip edebilirler ve d\u00fcnya \u00e7ap\u0131nda i\u015fbirlikleri kurabilirler. Sonu\u00e7 olarak, veri bilimcileri i\u00e7in \u0130ngilizce bilmek, kariyerlerindeki ba\u015far\u0131lar\u0131n\u0131 ve k\u00fcresel alanda rekabet avantajlar\u0131n\u0131 art\u0131racak bir fakt\u00f6rd\u00fcr.<\/span><\/p>\n

Veri Bilimciler \u0130\u00e7in \u0130ngilizce Kelime Listesi<\/strong><\/h2>\n

Veri bilimcileri i\u00e7in gerekli olan birtak\u0131m \u0130ngilizce kelime bulunuyor. Veri bilimcileri i\u00e7in gerekli \u0130ngilizce kelimelerden en \u00f6nemli 50 tanesini, T\u00fcrk\u00e7e kar\u015f\u0131l\u0131klar\u0131n\u0131 ve okunu\u015flar\u0131n\u0131 hemen a\u015fa\u011f\u0131da bulabilirsin.<\/span><\/p>\n

    \n
  1. Data – Veri<\/span><\/li>\n
  2. Analytics – Analiz<\/span><\/li>\n
  3. Machine Learning – Makine \u00d6\u011frenimi<\/span><\/li>\n
  4. Artificial Intelligence – Yapay Zeka<\/span><\/li>\n
  5. Algorithm – Algoritma<\/span><\/li>\n
  6. Big Data – B\u00fcy\u00fck Veri<\/span><\/li>\n
  7. Visualization – G\u00f6rselle\u015ftirme<\/span><\/li>\n
  8. Statistics – \u0130statistik<\/span><\/li>\n
  9. Predictive Modeling – Tahminsel Modelleme<\/span><\/li>\n
  10. Regression – Regresyon<\/span><\/li>\n
  11. Clustering – K\u00fcmeleme<\/span><\/li>\n
  12. Data Mining – Veri Madencili\u011fi<\/span><\/li>\n
  13. Feature Engineering – \u00d6zellik M\u00fchendisli\u011fi<\/span><\/li>\n
  14. Dimensionality Reduction – Boyut Azaltma<\/span><\/li>\n
  15. Neural Networks – Sinir A\u011flar\u0131<\/span><\/li>\n
  16. Deep Learning – Derin \u00d6\u011frenme<\/span><\/li>\n
  17. Natural Language Processing – Do\u011fal Dil \u0130\u015fleme<\/span><\/li>\n
  18. Decision Tree – Karar A\u011fac\u0131<\/span><\/li>\n
  19. Random Forest – Rastgele Orman<\/span><\/li>\n
  20. Support Vector Machines – Destek Vekt\u00f6r Makineleri<\/span><\/li>\n
  21. Neural Network Architecture – Sinir A\u011f\u0131 Mimarisi<\/span><\/li>\n
  22. Artificial Neural Networks – Yapay Sinir A\u011flar\u0131<\/span><\/li>\n
  23. Gradient Descent – Gradyan \u0130ni\u015f<\/span><\/li>\n
  24. Stochastic Gradient Descent – Stokastik Gradyan \u0130ni\u015f<\/span><\/li>\n
  25. Batch Normalization – Toplu Normalle\u015ftirme<\/span><\/li>\n
  26. Convolutional Neural Networks – Evri\u015fimli Sinir A\u011flar\u0131<\/span><\/li>\n
  27. Recurrent Neural Networks – Tekrarlayan Sinir A\u011flar\u0131<\/span><\/li>\n
  28. Long Short-Term Memory – Uzun K\u0131sa D\u00f6nem Bellek<\/span><\/li>\n
  29. Overfitting – A\u015f\u0131r\u0131 \u00d6\u011frenme<\/span><\/li>\n
  30. Underfitting – Yetersiz \u00d6\u011frenme<\/span><\/li>\n
  31. Cross-Validation – \u00c7apraz Do\u011frulama<\/span><\/li>\n
  32. Regularization – D\u00fczenlile\u015ftirme<\/span><\/li>\n
  33. Ensemble Learning – Ansamb\u0131l \u00d6\u011frenme<\/span><\/li>\n
  34. Hyperparameter Tuning – Hiperparametre Ayarlama<\/span><\/li>\n
  35. Gradient Boosting – Gradyan Artt\u0131rma<\/span><\/li>\n
  36. AdaBoost – AdaBoost<\/span><\/li>\n
  37. XGBoost – XGBoost<\/span><\/li>\n
  38. LightGBM – LightGBM<\/span><\/li>\n
  39. K-Nearest Neighbors – K-En Yak\u0131n Kom\u015fular<\/span><\/li>\n
  40. Principal Component Analysis – Temel Bile\u015fen Analizi<\/span><\/li>\n
  41. Singular Value Decomposition – Tekil De\u011fer Ayr\u0131\u015f\u0131m\u0131<\/span><\/li>\n
  42. Association Rule Mining – \u0130li\u015fki Kurallar\u0131 Madencili\u011fi<\/span><\/li>\n
  43. Time Series Analysis – Zaman Serisi Analizi<\/span><\/li>\n
  44. Anomaly Detection – Anomali Tespiti<\/span><\/li>\n
  45. Bayesian Networks – Bayes A\u011flar\u0131<\/span><\/li>\n
  46. Markov Chain – Markov Zinciri<\/span><\/li>\n
  47. Monte Carlo Simulation – Monte Carlo Sim\u00fclasyonu<\/span><\/li>\n
  48. Non-parametric Statistics – Parametrik Olmayan \u0130statistik<\/span><\/li>\n
  49. Outlier Detection – Ayk\u0131r\u0131 Veri Tespiti<\/span><\/li>\n
  50. Support Vector Regression – Destek Vekt\u00f6r Regresyonu<\/span><\/li>\n<\/ol>\n

    \u00d6\u011frenmek istedi\u011fin, yaln\u0131zca, veri bilimcileri i\u00e7in \u0130ngilizce kelimeler de\u011fil ise;<\/span> \u0130ngilizcede En \u00c7ok Kullan\u0131lan 1000 Kelime<\/i><\/b><\/a> ba\u015fl\u0131kl\u0131 yaz\u0131m\u0131z\u0131 mutlaka okumal\u0131s\u0131n.<\/span><\/p>\n

    \"veri<\/p>\n

    Veri Bilimciler \u0130\u00e7in \u0130ngilizce Kelimelerin C\u00fcmle \u0130\u00e7inde Kullan\u0131m\u0131<\/strong><\/h3>\n

    Veri bilimcileri i\u00e7in \u0130ngilizcede \u00f6\u011frenilecek \u00e7ok kelime var. \u015eimdi, veri bilimcileri i\u00e7in \u0130ngilizce kelimeleri c\u00fcmle i\u00e7erisinde kullanmaya yard\u0131mc\u0131 olacak 10 \u00f6rnek c\u00fcmleyi seninle payla\u015faca\u011f\u0131z.<\/span><\/p>\n

      \n
    1. Data science is a highly interdisciplinary field that combines computer science, statistics, and domain expertise. –<\/span> Veri bilimi, bilgisayar bilimleri, istatistik ve alan uzmanl\u0131\u011f\u0131n\u0131 birle\u015ftiren \u00e7ok disiplinli bir aland\u0131r.<\/span><\/i><\/li>\n
    2. Machine learning is a type of artificial intelligence that allows machines to learn from data and improve their performance over time. – <\/span>Makine \u00f6\u011frenimi, makinelerin verilerden \u00f6\u011frenmesine ve zamanla performans\u0131n\u0131 geli\u015ftirmesine olanak tan\u0131yan bir yapay zeka t\u00fcr\u00fcd\u00fcr.<\/span><\/i><\/li>\n
    3. The use of big data and analytics is transforming industries across the board, from healthcare to finance. – <\/span>B\u00fcy\u00fck veri ve analitik kullan\u0131m\u0131, sa\u011fl\u0131ktan finansa kadar her alanda end\u00fcstrileri d\u00f6n\u00fc\u015ft\u00fcr\u00fcyor.<\/span><\/i><\/li>\n
    4. Data visualization is a powerful tool for communicating complex information in a clear and concise manner. – <\/span>Veri g\u00f6rselle\u015ftirme, karma\u015f\u0131k bilgileri net ve \u00f6zl\u00fc bir \u015fekilde iletmek i\u00e7in g\u00fc\u00e7l\u00fc bir ara\u00e7t\u0131r.<\/span><\/i><\/li>\n
    5. Predictive modeling uses historical data to make predictions about future events or trends. – <\/span>Tahminsel modelleme, ge\u00e7mi\u015f verileri kullanarak gelecekteki olaylar veya trendler hakk\u0131nda tahminler yapmak i\u00e7in kullan\u0131l\u0131r.<\/span><\/i><\/li>\n
    6. Natural language processing is a field of study that focuses on the interaction between computers and human languages. – <\/span>Do\u011fal dil i\u015fleme, bilgisayarlar ile insan dilleri aras\u0131ndaki etkile\u015fime odaklanan bir \u00e7al\u0131\u015fma alan\u0131d\u0131r.<\/span><\/i><\/li>\n
    7. Neural networks are a type of machine learning algorithm that are inspired by the structure and function of the human brain. – <\/span>Sinir a\u011flar\u0131, insan beyninin yap\u0131s\u0131 ve i\u015flevinden esinlenen bir makine \u00f6\u011frenimi algoritmas\u0131 t\u00fcr\u00fcd\u00fcr.<\/span><\/i><\/li>\n
    8. Random forest is a popular machine learning technique for classification and regression problems. – <\/span>Rastgele orman, s\u0131n\u0131fland\u0131rma ve regresyon problemleri i\u00e7in pop\u00fcler bir makine \u00f6\u011frenimi tekniktir.<\/span><\/i><\/li>\n
    9. Ensemble learning is a technique that combines multiple machine learning models to improve predictive accuracy. – <\/span>Ansamb\u0131l \u00f6\u011frenme, tahmin do\u011frulu\u011funu art\u0131rmak i\u00e7in birden fazla makine \u00f6\u011frenimi modelini birle\u015ftiren bir tekniktir.<\/span><\/i><\/li>\n
    10. Cross-validation is a method for evaluating the performance of machine learning models by training and testing on different subsets of the data. – <\/span>\u00c7apraz do\u011frulama, makine \u00f6\u011frenimi modellerinin performans\u0131n\u0131 farkl\u0131 veri alt k\u00fcmesi \u00fczerinde e\u011fiterek ve test ederek de\u011ferlendirme y\u00f6ntemidir.<\/span><\/i><\/li>\n<\/ol>\n

      \"veri<\/p>\n

      Veri Bilimciler \u0130\u00e7in \u0130ngilizce \u00d6\u011frenmenin Kolay Yolu<\/strong><\/h3>\n

      Veri bilimcileri i\u00e7in \u0130ngilizce kelimeler konulu yaz\u0131m\u0131zda, bu meslekte \u00e7al\u0131\u015fanlar\u0131n ihtiya\u00e7 duyabilecekleri pek \u00e7ok \u0130ngilizce kelimeyi \u00f6\u011frendin. Ancak, sadece bu kelimelerle s\u0131n\u0131rl\u0131 kalmamal\u0131s\u0131n. Veri bilimcileri i\u00e7in i\u015f \u0130ngilizcesi e\u011fitimi de olduk\u00e7a \u00f6nemlidir. Open English sayesinde \u00e7ok daha fazla \u015fey \u00f6\u011frenmek m\u00fcmk\u00fcnd\u00fcr.<\/span><\/p>\n

      Open English’te yer alan i\u015f \u0130ngilizcesi<\/a><\/strong><\/em> programlar\u0131 sayesinde Veri bilimcileri i\u00e7in \u0130ngilizce \u00f6\u011frenmek olduk\u00e7a kolayd\u0131r. Bu platform sadece i\u015f \u0130ngilizcesi e\u011fitimi sunmaz, ayn\u0131 zamanda her seviyeye uygun \u0130ngilizce e\u011fitimi alma imkan\u0131 sa\u011flar. Ana dili \u0130ngilizce olan e\u011fitmenlerden alaca\u011f\u0131n \u0130ngilizce e\u011fitimi ile \u0130ngilizce becerilerini kolayl\u0131kla geli\u015ftirebilirsin.<\/span><\/p>\n

      Veri bilimcileri i\u00e7in haz\u0131rlanm\u0131\u015f \u00f6zel i\u00e7erikli mesleki \u0130ngilizce programlar\u0131na ula\u015fmak i\u00e7in bu sayfada bulunan ileti\u015fim formunu doldur. Open English\u2019e aboneli\u011fini h\u0131zl\u0131ca ba\u015flatal\u0131m ve mesleki \u0130ngilizce programlar\u0131na kat\u0131lman i\u00e7in sana hemen yard\u0131mc\u0131 olal\u0131m.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

      Veri bilimi, verilerin analizi ve yorumlanmas\u0131 yoluyla bilgiye d\u00f6n\u00fc\u015ft\u00fcr\u00fclmesi s\u00fcrecidir. Veri biliminde, b\u00fcy\u00fck veri k\u00fcmeleri kullan\u0131larak istatistiksel y\u00f6ntemler, makine \u00f6\u011frenme algoritmalar\u0131 ve veri madencili\u011fi teknikleri gibi ara\u00e7lar kullan\u0131l\u0131r. Veri bilimi, bir\u00e7ok alanda kullan\u0131labilir, \u00f6rne\u011fin; i\u015fletme, sa\u011fl\u0131k, m\u00fchendislik ve sosyal bilimler gibi.\u00a0 Veri bilimci ise, veri biliminde uzmanla\u015fm\u0131\u015f bir ki\u015fidir. Veri bilimcileri, verileri toplamak, analiz etmek, […]<\/p>\n","protected":false},"author":24,"featured_media":13419,"comment_status":"open","ping_status":"open","sticky":false,"template":"post-2021.php","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1,4,11],"tags":[],"class_list":["post-13418","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-kelime-bilgisi","category-ingilizce-ogren","category-is-ingilizcesi"],"yoast_head":"\nVeri Bilimcileri \u0130\u00e7in \u0130ngilizce Kelimeler - Open English Blog<\/title>\n<meta name=\"description\" content=\"Veri bilimciler i\u00e7in \u0130ngilizce gerekli mi? 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