Planet Odisha

Looks like even if mumbai is getting heavy rain, there is nothing is odisha


7 Opinions
Sushil Subedi

Sushil Subedi

  • Answered on Aug 29, 2017

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Sushil Subedi

Sushil Subedi

  • Answered on Aug 29, 2017

sfa 

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Sushil Subedi

Sushil Subedi

  • Answered on Aug 29, 2017

sadf df sdf

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Kirendra Yadav

Kirendra Yadav

  • Answered on Aug 28, 2017
How do I learn data science in a time-efficient manner? Data science is a broad field. What is the How do I learn data science in a time-efficient manner? Data science is a broad field. What is the How do I learn data science in a time-efficient manner? Data science is a broad field. What is the
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Kirendra Yadav

Kirendra Yadav

  • Answered on Aug 28, 2017
Understand basic linear algebra really , really, really well. How to solve a regression : Ax = b How to solve for eigenvalues / vectors: Ax = ax Machine learning is all about modern techniques for solving these basic problems on very large and/ or ill-formed data sets with very noisy data. Understand the theory. Know the numerical techniques. You can study the MIT online coursework in linear algebra (Strang lectures) if you never took a course in linear algebra: http://web.mit.e
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Ok noted
Sushil Subedi

Sushil Subedi

  • Answered on Aug 28, 2017
Linear Algebra - Matrices Part I - A Tutorial with Examples Introduction to Matrices. Theory, definitions. What a Matrix is, order of a matrix, equality of matrices, different kind of matrices: row matrix, column matrix, square matrix, diagonal, identity and triangular matrices. Definitions of Trace, Minor, Cofactors, Adjoint, Inverse, Transpose of a matrix. Addition, subtraction, scalar multiplication, multiplication of matrices. Defining special types of matrices like Symmetric, Skew Symmetric, Idempotent, Involuntary, Nil-potent, Singular, Non-Singular, Unitary matrices. Linear Algerba - Matrices Part II - A Tutorial with Examples, Problems and Solutions Problems and solved examples based on the sub-topics mentioned above. Some of the problems in this part demonstrate finding the rank, inverse or characteristic equations of matrices. Representing real life problems in matrix form. Linear Algebra - Determinants - A Tutorial with Examples, Problems and Solutions Introduction to determinants. Second and third order determinants, minors and co-factors. Properties of determinants and how it remains altered or unaltered based on simple transformations is matrices. Expanding the determinant. Solved problems related to determinants.
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Planet Odisha

Planet Odisha

  • Answered on Aug 28, 2017
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