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linear
algebra
By: Mohamed Essam
Linear algebra
Linear algebra has an interesting history in mathematics, dating
back to the 17th century in the West and much earlier in China.
Matrices—the spreadsheets of numbers at the heart of linear
algebra .
were used to provide a compact notation for storing sets of
numbers like geometric coordinates (this was Descartes’ original
use of matrices) and systems of equations (pioneered by Gauss).
In the 20th century, matrices and vectors were used for
multivariate mathematics including calculus, differential
equations, physics, and economics.
Linear algebra
But most people didn’t need to care about matrices until fairly
recently. Here’s the thing: Computers are extremely efficient at
working with matrices. And so, modern computing gave rise to
modern linear algebra. Modern linear algebra is computational
whereas traditional linear algebra is abstract. Modern linear
algebra is best learned through code and applications in
graphics, statistics, data science, A.I.,
Vectors
Creating and visualizing vectors in numpy
In linear algebra, a vector is an ordered list of numbers. (In abstract linear
algebra, vectors may contain other mathematical objects including
functions;
Dimensionality: The number of numbers in the vector.
Orientation: Whether the vector is in column orientation (standing up
tall) or row orientation (laying flat and wide).
Vectors-Adding two vectors
To add two vectors, simply add each corresponding element. Here is an
example:
Vectors-Adding two vectors
To add two vectors, simply add each corresponding element. Here is an
example:
Vectors-Adding two vectors
To add two vectors, simply add each corresponding element. Here is an
example:
Vectors- Dot prodcut
There are multiple ways to implement the dot product in Python; the most
straightforward way is to the use the np.dot() function.
CREDITS: This presentation template was created by Slidesgo,
including icons by Flaticon, and infographics & images by Freepik
Thank you

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Linear_algebra.pptx

  • 2. Linear algebra Linear algebra has an interesting history in mathematics, dating back to the 17th century in the West and much earlier in China. Matrices—the spreadsheets of numbers at the heart of linear algebra . were used to provide a compact notation for storing sets of numbers like geometric coordinates (this was Descartes’ original use of matrices) and systems of equations (pioneered by Gauss). In the 20th century, matrices and vectors were used for multivariate mathematics including calculus, differential equations, physics, and economics.
  • 3. Linear algebra But most people didn’t need to care about matrices until fairly recently. Here’s the thing: Computers are extremely efficient at working with matrices. And so, modern computing gave rise to modern linear algebra. Modern linear algebra is computational whereas traditional linear algebra is abstract. Modern linear algebra is best learned through code and applications in graphics, statistics, data science, A.I.,
  • 4. Vectors Creating and visualizing vectors in numpy In linear algebra, a vector is an ordered list of numbers. (In abstract linear algebra, vectors may contain other mathematical objects including functions; Dimensionality: The number of numbers in the vector. Orientation: Whether the vector is in column orientation (standing up tall) or row orientation (laying flat and wide).
  • 5.
  • 6. Vectors-Adding two vectors To add two vectors, simply add each corresponding element. Here is an example:
  • 7. Vectors-Adding two vectors To add two vectors, simply add each corresponding element. Here is an example:
  • 8. Vectors-Adding two vectors To add two vectors, simply add each corresponding element. Here is an example:
  • 9. Vectors- Dot prodcut There are multiple ways to implement the dot product in Python; the most straightforward way is to the use the np.dot() function.
  • 10. CREDITS: This presentation template was created by Slidesgo, including icons by Flaticon, and infographics & images by Freepik Thank you

Notas do Editor

  1. Because we choose the nearest one.
  2. للجبر الخطي تاريخ مثير للاهتمام في الرياضيات ، يعود تاريخه إلى القرن السابع عشر في الغرب وقبل ذلك بكثير في الصين. المصفوفات - جداول بيانات الأرقام الموجودة في قلب الجبر الخطي. تم استخدامها لتوفير تدوين مضغوط لتخزين مجموعات من الأرقام مثل الإحداثيات الهندسية (كان هذا هو استخدام ديكارت الأصلي للمصفوفات) وأنظمة المعادلات (التي ابتكرها Gauss). في القرن العشرين ، تم استخدام المصفوفات والمتجهات للرياضيات متعددة المتغيرات بما في ذلك حساب التفاضل والتكامل والمعادلات التفاضلية والفيزياء والاقتصاد.
  3. للجبر الخطي تاريخ مثير للاهتمام في الرياضيات ، يعود تاريخه إلى القرن السابع عشر في الغرب وقبل ذلك بكثير في الصين. المصفوفات - جداول بيانات الأرقام الموجودة في قلب الجبر الخطي. تم استخدامها لتوفير تدوين مضغوط لتخزين مجموعات من الأرقام مثل الإحداثيات الهندسية (كان هذا هو استخدام ديكارت الأصلي للمصفوفات) وأنظمة المعادلات (التي ابتكرها Gauss). في القرن العشرين ، تم استخدام المصفوفات والمتجهات للرياضيات متعددة المتغيرات بما في ذلك حساب التفاضل والتكامل والمعادلات التفاضلية والفيزياء والاقتصاد.
  4. للجبر الخطي تاريخ مثير للاهتمام في الرياضيات ، يعود تاريخه إلى القرن السابع عشر في الغرب وقبل ذلك بكثير في الصين. المصفوفات - جداول بيانات الأرقام الموجودة في قلب الجبر الخطي. تم استخدامها لتوفير تدوين مضغوط لتخزين مجموعات من الأرقام مثل الإحداثيات الهندسية (كان هذا هو استخدام ديكارت الأصلي للمصفوفات) وأنظمة المعادلات (التي ابتكرها Gauss). في القرن العشرين ، تم استخدام المصفوفات والمتجهات للرياضيات متعددة المتغيرات بما في ذلك حساب التفاضل والتكامل والمعادلات التفاضلية والفيزياء والاقتصاد.
  5. للجبر الخطي تاريخ مثير للاهتمام في الرياضيات ، يعود تاريخه إلى القرن السابع عشر في الغرب وقبل ذلك بكثير في الصين. المصفوفات - جداول بيانات الأرقام الموجودة في قلب الجبر الخطي. تم استخدامها لتوفير تدوين مضغوط لتخزين مجموعات من الأرقام مثل الإحداثيات الهندسية (كان هذا هو استخدام ديكارت الأصلي للمصفوفات) وأنظمة المعادلات (التي ابتكرها Gauss). في القرن العشرين ، تم استخدام المصفوفات والمتجهات للرياضيات متعددة المتغيرات بما في ذلك حساب التفاضل والتكامل والمعادلات التفاضلية والفيزياء والاقتصاد.
  6. للجبر الخطي تاريخ مثير للاهتمام في الرياضيات ، يعود تاريخه إلى القرن السابع عشر في الغرب وقبل ذلك بكثير في الصين. المصفوفات - جداول بيانات الأرقام الموجودة في قلب الجبر الخطي. تم استخدامها لتوفير تدوين مضغوط لتخزين مجموعات من الأرقام مثل الإحداثيات الهندسية (كان هذا هو استخدام ديكارت الأصلي للمصفوفات) وأنظمة المعادلات (التي ابتكرها Gauss). في القرن العشرين ، تم استخدام المصفوفات والمتجهات للرياضيات متعددة المتغيرات بما في ذلك حساب التفاضل والتكامل والمعادلات التفاضلية والفيزياء والاقتصاد.
  7. للجبر الخطي تاريخ مثير للاهتمام في الرياضيات ، يعود تاريخه إلى القرن السابع عشر في الغرب وقبل ذلك بكثير في الصين. المصفوفات - جداول بيانات الأرقام الموجودة في قلب الجبر الخطي. تم استخدامها لتوفير تدوين مضغوط لتخزين مجموعات من الأرقام مثل الإحداثيات الهندسية (كان هذا هو استخدام ديكارت الأصلي للمصفوفات) وأنظمة المعادلات (التي ابتكرها Gauss). في القرن العشرين ، تم استخدام المصفوفات والمتجهات للرياضيات متعددة المتغيرات بما في ذلك حساب التفاضل والتكامل والمعادلات التفاضلية والفيزياء والاقتصاد.
  8. للجبر الخطي تاريخ مثير للاهتمام في الرياضيات ، يعود تاريخه إلى القرن السابع عشر في الغرب وقبل ذلك بكثير في الصين. المصفوفات - جداول بيانات الأرقام الموجودة في قلب الجبر الخطي. تم استخدامها لتوفير تدوين مضغوط لتخزين مجموعات من الأرقام مثل الإحداثيات الهندسية (كان هذا هو استخدام ديكارت الأصلي للمصفوفات) وأنظمة المعادلات (التي ابتكرها Gauss). في القرن العشرين ، تم استخدام المصفوفات والمتجهات للرياضيات متعددة المتغيرات بما في ذلك حساب التفاضل والتكامل والمعادلات التفاضلية والفيزياء والاقتصاد.