Linear Algebra for Machine Learning || vector

Overview :

Linear algebra is heart of Machine Learning algorithms . It has vast area here I am particularly focus some history of LA , application fields and Vector . This is part of #ml_study_jam and Machine Learning , AI , Deep Learning and NLP community Bangladesh

Description :
This video commences with the early use of linear equations in ancient China and traces its development through Europe in the 17th century. Key milestones include:
- 1844 Hermann's Theory of Extension: The foundation of modern linear algebra.
- Matrices in Engineering: Applications such as analyzing a line of springs.
- Graphs and Networks: Used for network analysis.
- Markov Matrices: Applied in population studies and economics.
- Linear Programming: Featuring the simplex optimization method.
- Fourier Series: Utilized in signal processing.
- Statistics and Probability: Techniques like least squares for regression.
- Computer Graphics: Techniques for image translation, rescaling, and rotation.

We also dive into concrete examples of linear algebra in machine learning, including:
1. Datasets and Data Files
2. Images and Photographs
3. One-Hot Encoding
4. Linear Regression
5. Regularization
6. Principal Component Analysis (PCA)
7. Singular-Value Decomposition (SVD)
8. Latent Semantic Analysis (LSA)
9. Recommender Systems
10. Deep Learning

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Linear Algebra for Machine Learning || vector

#ai LinearAlgebra #MachineLearning #HistoryOfMath #DataScience #Numpy #GoogleColab #Matrices #Optimization #SignalProcessing #Statistics #ComputerGraphics #DeepLearning #PCA #SVD #LSA #recommendersystems #cprogramming #cosoleproject #medicalsystem #programming c #programing #cse #cseengineering

Видео Linear Algebra for Machine Learning || vector канала sajjad rahman