SlideShare a Scribd company logo
1 of 8
Download to read offline
Fundamental
Mathematics
for DL
CSE 5172 – Deep Learning &
Applications
Overview
• Tensors
• Vectors
• Matrices
• Notational convention
Tensors
Tensors are a specialized data structure that are very similar
to arrays and matrices.
In PyTorch, tensors are used to encode the inputs and
outputs of a model, as well as the model’s parameters.
Tensors are similar to NumPy’s ndarrays, except that tensors
can run on GPUs.
Tensors are also optimized for automatic differentiation.
https://pytorch.org/tutorials/beginner/basics/tensorqs_tutorial.html
Vectors, Matrices, and
Tensors
x 2 R
x = 1
Scalar
e.g.,
(rank-0 tensor)
x 2 Rn
Vector
(rank-1 tensor)
but in this lecture,
we will assume
x 2 Rn⇥1
x =
2
6
6
6
4
x1
x2
.
.
.
xn
3
7
7
7
5
e.g.,
Matrix
(rank-2 tensor)
e.g.,
X =
2
6
6
6
4
x1,1 x1,2 . . . x1,n
x2,1 x2,2 . . . x2,n
.
.
.
.
.
.
...
.
.
.
xm,1 xm,2 . . . xm,n
3
7
7
7
5
X 2 Rm⇥n
x>
=
⇥
x1 x2 . . . xn
⇤
, where x>
2 R1⇥n
.
Vectors, Matrices, and Tensors -- Notational Conventions
Vectors, Matrices, and
Tensors
We will often use X as a special convention to refer to the
"design matrix." That is, the matrix containing the training
examples and features (inputs)
X 2 Rn⇥m
and assume the structure
because n is often used to refer to the number of examples in
literature across many disciplines.
X =
2
6
6
6
6
6
6
4
x
[1]
1 x
[1]
2 . . . x
[1]
m
x
[2]
1 x
[2]
2 . . . x
[2]
m
.
.
.
.
.
.
...
.
.
.
x
[n]
1 x
[n]
2 . . . x
[n]
m
3
7
7
7
7
7
7
5
x
[1]
2 = 2nd feature value of the 1st
training example
E.g.,
Vectors, Matrices, and Tensors -- Notational Conventions
Vectors, Matrices, and
Tensors
(rank-3 tensor)
Vectors, Matrices, and Tensors -- Notational Conventions
3D Tensor
X 2 Rm⇥n⇥p
X =
2
6
6
6
4
x1,1 x1,2 . . . x1,n
x2,1 x2,2 . . . x2,n
.
.
.
.
.
.
...
.
.
.
xm,1 xm,2 . . . xm,n
3
7
7
7
5
X =
2
6
6
6
4
x1,1 x1,2 . . . x1,n
x2,1 x2,2 . . . x2,n
.
.
.
.
.
.
...
.
.
.
xm,1 xm,2 . . . xm,n
3
7
7
7
5
X =
2
6
6
6
4
x1,1 x1,2 . . . x1,n
x2,1 x2,2 . . . x2,n
.
.
.
.
.
.
...
.
.
.
xm,1 xm,2 . . . xm,n
3
7
7
7
5
p
...
Example of 3D Tensor
An Example of a 3D Tensor in DL
Image Source: https://code.tutsplus.com/tutorials/create-a-retro-crt-distortion-effect-using-rgb-shifting--active-3359
Single color image
(3D tensor for "multidimensional-array" storage and parallel computing purpose,
ppt of no tensors , how they word etc etc etc

More Related Content

Similar to ppt of no tensors , how they word etc etc etc

Deep Learning for Search
Deep Learning for SearchDeep Learning for Search
Deep Learning for SearchBhaskar Mitra
 
Random Matrix Theory and Machine Learning - Part 3
Random Matrix Theory and Machine Learning - Part 3Random Matrix Theory and Machine Learning - Part 3
Random Matrix Theory and Machine Learning - Part 3Fabian Pedregosa
 
Vectorise all the things - long version.pptx
Vectorise all the things - long version.pptxVectorise all the things - long version.pptx
Vectorise all the things - long version.pptxJodieBurchell1
 
5 DimensionalityReduction.pdf
5 DimensionalityReduction.pdf5 DimensionalityReduction.pdf
5 DimensionalityReduction.pdfRahul926331
 
2012 mdsp pr09 pca lda
2012 mdsp pr09 pca lda2012 mdsp pr09 pca lda
2012 mdsp pr09 pca ldanozomuhamada
 
Random process and noise
Random process and noiseRandom process and noise
Random process and noisePunk Pankaj
 
Efficient Analysis of high-dimensional data in tensor formats
Efficient Analysis of high-dimensional data in tensor formatsEfficient Analysis of high-dimensional data in tensor formats
Efficient Analysis of high-dimensional data in tensor formatsAlexander Litvinenko
 
Complex models in ecology: challenges and solutions
Complex models in ecology: challenges and solutionsComplex models in ecology: challenges and solutions
Complex models in ecology: challenges and solutionsPeter Solymos
 
TENSOR DECOMPOSITION WITH PYTHON
TENSOR DECOMPOSITION WITH PYTHONTENSOR DECOMPOSITION WITH PYTHON
TENSOR DECOMPOSITION WITH PYTHONAndré Panisson
 
Unit-1 Introduction and Mathematical Preliminaries.pptx
Unit-1 Introduction and Mathematical Preliminaries.pptxUnit-1 Introduction and Mathematical Preliminaries.pptx
Unit-1 Introduction and Mathematical Preliminaries.pptxavinashBajpayee1
 
Tensor Spectral Clustering
Tensor Spectral ClusteringTensor Spectral Clustering
Tensor Spectral ClusteringAustin Benson
 
Estimating structured vector autoregressive models
Estimating structured vector autoregressive modelsEstimating structured vector autoregressive models
Estimating structured vector autoregressive modelsAkira Tanimoto
 
X02 Supervised learning problem linear regression multiple features
X02 Supervised learning problem linear regression multiple featuresX02 Supervised learning problem linear regression multiple features
X02 Supervised learning problem linear regression multiple featuresMarco Moldenhauer
 
Principal Components Analysis, Calculation and Visualization
Principal Components Analysis, Calculation and VisualizationPrincipal Components Analysis, Calculation and Visualization
Principal Components Analysis, Calculation and VisualizationMarjan Sterjev
 
Clustering:k-means, expect-maximization and gaussian mixture model
Clustering:k-means, expect-maximization and gaussian mixture modelClustering:k-means, expect-maximization and gaussian mixture model
Clustering:k-means, expect-maximization and gaussian mixture modeljins0618
 
New data structures and algorithms for \\post-processing large data sets and ...
New data structures and algorithms for \\post-processing large data sets and ...New data structures and algorithms for \\post-processing large data sets and ...
New data structures and algorithms for \\post-processing large data sets and ...Alexander Litvinenko
 

Similar to ppt of no tensors , how they word etc etc etc (20)

Deep Learning for Search
Deep Learning for SearchDeep Learning for Search
Deep Learning for Search
 
Random Matrix Theory and Machine Learning - Part 3
Random Matrix Theory and Machine Learning - Part 3Random Matrix Theory and Machine Learning - Part 3
Random Matrix Theory and Machine Learning - Part 3
 
Introduction to R
Introduction to RIntroduction to R
Introduction to R
 
Vectorise all the things - long version.pptx
Vectorise all the things - long version.pptxVectorise all the things - long version.pptx
Vectorise all the things - long version.pptx
 
bobok
bobokbobok
bobok
 
5 DimensionalityReduction.pdf
5 DimensionalityReduction.pdf5 DimensionalityReduction.pdf
5 DimensionalityReduction.pdf
 
2012 mdsp pr09 pca lda
2012 mdsp pr09 pca lda2012 mdsp pr09 pca lda
2012 mdsp pr09 pca lda
 
1 6
1 61 6
1 6
 
Random process and noise
Random process and noiseRandom process and noise
Random process and noise
 
Efficient Analysis of high-dimensional data in tensor formats
Efficient Analysis of high-dimensional data in tensor formatsEfficient Analysis of high-dimensional data in tensor formats
Efficient Analysis of high-dimensional data in tensor formats
 
Complex models in ecology: challenges and solutions
Complex models in ecology: challenges and solutionsComplex models in ecology: challenges and solutions
Complex models in ecology: challenges and solutions
 
Statistics lab 1
Statistics lab 1Statistics lab 1
Statistics lab 1
 
TENSOR DECOMPOSITION WITH PYTHON
TENSOR DECOMPOSITION WITH PYTHONTENSOR DECOMPOSITION WITH PYTHON
TENSOR DECOMPOSITION WITH PYTHON
 
Unit-1 Introduction and Mathematical Preliminaries.pptx
Unit-1 Introduction and Mathematical Preliminaries.pptxUnit-1 Introduction and Mathematical Preliminaries.pptx
Unit-1 Introduction and Mathematical Preliminaries.pptx
 
Tensor Spectral Clustering
Tensor Spectral ClusteringTensor Spectral Clustering
Tensor Spectral Clustering
 
Estimating structured vector autoregressive models
Estimating structured vector autoregressive modelsEstimating structured vector autoregressive models
Estimating structured vector autoregressive models
 
X02 Supervised learning problem linear regression multiple features
X02 Supervised learning problem linear regression multiple featuresX02 Supervised learning problem linear regression multiple features
X02 Supervised learning problem linear regression multiple features
 
Principal Components Analysis, Calculation and Visualization
Principal Components Analysis, Calculation and VisualizationPrincipal Components Analysis, Calculation and Visualization
Principal Components Analysis, Calculation and Visualization
 
Clustering:k-means, expect-maximization and gaussian mixture model
Clustering:k-means, expect-maximization and gaussian mixture modelClustering:k-means, expect-maximization and gaussian mixture model
Clustering:k-means, expect-maximization and gaussian mixture model
 
New data structures and algorithms for \\post-processing large data sets and ...
New data structures and algorithms for \\post-processing large data sets and ...New data structures and algorithms for \\post-processing large data sets and ...
New data structures and algorithms for \\post-processing large data sets and ...
 

Recently uploaded

(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...ranjana rawat
 
University management System project report..pdf
University management System project report..pdfUniversity management System project report..pdf
University management System project report..pdfKamal Acharya
 
Processing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptxProcessing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptxpranjaldaimarysona
 
Glass Ceramics: Processing and Properties
Glass Ceramics: Processing and PropertiesGlass Ceramics: Processing and Properties
Glass Ceramics: Processing and PropertiesPrabhanshu Chaturvedi
 
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete RecordCCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete RecordAsst.prof M.Gokilavani
 
UNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and workingUNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and workingrknatarajan
 
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...ranjana rawat
 
Introduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptxIntroduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptxupamatechverse
 
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service NashikCollege Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service NashikCall Girls in Nagpur High Profile
 
Booking open Available Pune Call Girls Pargaon 6297143586 Call Hot Indian Gi...
Booking open Available Pune Call Girls Pargaon  6297143586 Call Hot Indian Gi...Booking open Available Pune Call Girls Pargaon  6297143586 Call Hot Indian Gi...
Booking open Available Pune Call Girls Pargaon 6297143586 Call Hot Indian Gi...Call Girls in Nagpur High Profile
 
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 BookingVIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Bookingdharasingh5698
 
Coefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxCoefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxAsutosh Ranjan
 
UNIT - IV - Air Compressors and its Performance
UNIT - IV - Air Compressors and its PerformanceUNIT - IV - Air Compressors and its Performance
UNIT - IV - Air Compressors and its Performancesivaprakash250
 
MANUFACTURING PROCESS-II UNIT-1 THEORY OF METAL CUTTING
MANUFACTURING PROCESS-II UNIT-1 THEORY OF METAL CUTTINGMANUFACTURING PROCESS-II UNIT-1 THEORY OF METAL CUTTING
MANUFACTURING PROCESS-II UNIT-1 THEORY OF METAL CUTTINGSIVASHANKAR N
 
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur EscortsHigh Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escortsranjana rawat
 
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur EscortsHigh Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur EscortsCall Girls in Nagpur High Profile
 

Recently uploaded (20)

(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
 
University management System project report..pdf
University management System project report..pdfUniversity management System project report..pdf
University management System project report..pdf
 
Processing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptxProcessing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptx
 
Glass Ceramics: Processing and Properties
Glass Ceramics: Processing and PropertiesGlass Ceramics: Processing and Properties
Glass Ceramics: Processing and Properties
 
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete RecordCCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
 
UNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and workingUNIT-V FMM.HYDRAULIC TURBINE - Construction and working
UNIT-V FMM.HYDRAULIC TURBINE - Construction and working
 
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(PRIYA) Rajgurunagar Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
 
Introduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptxIntroduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptx
 
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service NashikCollege Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
 
Booking open Available Pune Call Girls Pargaon 6297143586 Call Hot Indian Gi...
Booking open Available Pune Call Girls Pargaon  6297143586 Call Hot Indian Gi...Booking open Available Pune Call Girls Pargaon  6297143586 Call Hot Indian Gi...
Booking open Available Pune Call Girls Pargaon 6297143586 Call Hot Indian Gi...
 
DJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINE
DJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINEDJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINE
DJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINE
 
(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7
(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7
(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7
 
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 BookingVIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
 
Coefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxCoefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptx
 
Roadmap to Membership of RICS - Pathways and Routes
Roadmap to Membership of RICS - Pathways and RoutesRoadmap to Membership of RICS - Pathways and Routes
Roadmap to Membership of RICS - Pathways and Routes
 
Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024
 
UNIT - IV - Air Compressors and its Performance
UNIT - IV - Air Compressors and its PerformanceUNIT - IV - Air Compressors and its Performance
UNIT - IV - Air Compressors and its Performance
 
MANUFACTURING PROCESS-II UNIT-1 THEORY OF METAL CUTTING
MANUFACTURING PROCESS-II UNIT-1 THEORY OF METAL CUTTINGMANUFACTURING PROCESS-II UNIT-1 THEORY OF METAL CUTTING
MANUFACTURING PROCESS-II UNIT-1 THEORY OF METAL CUTTING
 
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur EscortsHigh Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Isha Call 7001035870 Meet With Nagpur Escorts
 
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur EscortsHigh Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
 

ppt of no tensors , how they word etc etc etc

  • 1. Fundamental Mathematics for DL CSE 5172 – Deep Learning & Applications
  • 2. Overview • Tensors • Vectors • Matrices • Notational convention
  • 3. Tensors Tensors are a specialized data structure that are very similar to arrays and matrices. In PyTorch, tensors are used to encode the inputs and outputs of a model, as well as the model’s parameters. Tensors are similar to NumPy’s ndarrays, except that tensors can run on GPUs. Tensors are also optimized for automatic differentiation. https://pytorch.org/tutorials/beginner/basics/tensorqs_tutorial.html
  • 4. Vectors, Matrices, and Tensors x 2 R x = 1 Scalar e.g., (rank-0 tensor) x 2 Rn Vector (rank-1 tensor) but in this lecture, we will assume x 2 Rn⇥1 x = 2 6 6 6 4 x1 x2 . . . xn 3 7 7 7 5 e.g., Matrix (rank-2 tensor) e.g., X = 2 6 6 6 4 x1,1 x1,2 . . . x1,n x2,1 x2,2 . . . x2,n . . . . . . ... . . . xm,1 xm,2 . . . xm,n 3 7 7 7 5 X 2 Rm⇥n x> = ⇥ x1 x2 . . . xn ⇤ , where x> 2 R1⇥n . Vectors, Matrices, and Tensors -- Notational Conventions
  • 5. Vectors, Matrices, and Tensors We will often use X as a special convention to refer to the "design matrix." That is, the matrix containing the training examples and features (inputs) X 2 Rn⇥m and assume the structure because n is often used to refer to the number of examples in literature across many disciplines. X = 2 6 6 6 6 6 6 4 x [1] 1 x [1] 2 . . . x [1] m x [2] 1 x [2] 2 . . . x [2] m . . . . . . ... . . . x [n] 1 x [n] 2 . . . x [n] m 3 7 7 7 7 7 7 5 x [1] 2 = 2nd feature value of the 1st training example E.g., Vectors, Matrices, and Tensors -- Notational Conventions
  • 6. Vectors, Matrices, and Tensors (rank-3 tensor) Vectors, Matrices, and Tensors -- Notational Conventions 3D Tensor X 2 Rm⇥n⇥p X = 2 6 6 6 4 x1,1 x1,2 . . . x1,n x2,1 x2,2 . . . x2,n . . . . . . ... . . . xm,1 xm,2 . . . xm,n 3 7 7 7 5 X = 2 6 6 6 4 x1,1 x1,2 . . . x1,n x2,1 x2,2 . . . x2,n . . . . . . ... . . . xm,1 xm,2 . . . xm,n 3 7 7 7 5 X = 2 6 6 6 4 x1,1 x1,2 . . . x1,n x2,1 x2,2 . . . x2,n . . . . . . ... . . . xm,1 xm,2 . . . xm,n 3 7 7 7 5 p ...
  • 7. Example of 3D Tensor An Example of a 3D Tensor in DL Image Source: https://code.tutsplus.com/tutorials/create-a-retro-crt-distortion-effect-using-rgb-shifting--active-3359 Single color image (3D tensor for "multidimensional-array" storage and parallel computing purpose,