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Linear Algebra for Machine Learning

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English

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14.43 GB

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8be0a0bd9df415ae204ed438faaa2ec47386e827

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tutsnode

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13-12-2020 14:32

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File	Size
TutsNode.com.txt	63.00 B
[TGx]Downloaded from torrentgalaxy.to .txt	585.00 B
[TutsNode.com] - Linear Algebra for Machine Learning/01-Topics.en.dfxp	1.31 kB
[TutsNode.com] - Linear Algebra for Machine Learning/01-Topics.mp4	40.43 MB
[TutsNode.com] - Linear Algebra for Machine Learning/02-Topics.en.dfxp	1.54 kB
[TutsNode.com] - Linear Algebra for Machine Learning/02-Topics.mp4	45.02 MB
[TutsNode.com] - Linear Algebra for Machine Learning/03-3.1 Tensor Transposition.en.dfxp	6.73 kB
[TutsNode.com] - Linear Algebra for Machine Learning/03-3.1 Tensor Transposition.mp4	92.22 MB
[TutsNode.com] - Linear Algebra for Machine Learning/04-3.5 Exercises.en.dfxp	9.56 kB
[TutsNode.com] - Linear Algebra for Machine Learning/04-3.5 Exercises.mp4	416.55 MB
[TutsNode.com] - Linear Algebra for Machine Learning/05-3.2 Basic Tensor Arithmetic.en.dfxp	10.99 kB
[TutsNode.com] - Linear Algebra for Machine Learning/05-3.2 Basic Tensor Arithmetic.mp4	143.94 MB
[TutsNode.com] - Linear Algebra for Machine Learning/06-Topics.en.dfxp	1,014.00 B
[TutsNode.com] - Linear Algebra for Machine Learning/06-Topics.mp4	29.79 MB
[TutsNode.com] - Linear Algebra for Machine Learning/07-5.4 Exercises.en.dfxp	14.51 kB
[TutsNode.com] - Linear Algebra for Machine Learning/07-5.4 Exercises.mp4	629.77 MB
[TutsNode.com] - Linear Algebra for Machine Learning/08-6.4 Orthogonal Matrices.en.dfxp	8.31 kB
[TutsNode.com] - Linear Algebra for Machine Learning/08-6.4 Orthogonal Matrices.mp4	126.01 MB
[TutsNode.com] - Linear Algebra for Machine Learning/09-6.2 Matrix Inversion.en.dfxp	28.72 kB
[TutsNode.com] - Linear Algebra for Machine Learning/09-6.2 Matrix Inversion.mp4	304.81 MB
[TutsNode.com] - Linear Algebra for Machine Learning/10-Topics.en.dfxp	1.04 kB
[TutsNode.com] - Linear Algebra for Machine Learning/10-Topics.mp4	32.22 MB
[TutsNode.com] - Linear Algebra for Machine Learning/11-Topics.en.dfxp	1.63 kB
[TutsNode.com] - Linear Algebra for Machine Learning/11-Topics.mp4	53.46 MB
[TutsNode.com] - Linear Algebra for Machine Learning/12-1.1 Defining Linear Algebra.en.dfxp	11.83 kB
[TutsNode.com] - Linear Algebra for Machine Learning/12-1.1 Defining Linear Algebra.mp4	168.05 MB
[TutsNode.com] - Linear Algebra for Machine Learning/13-1.5 Exercise.en.dfxp	14.93 kB
[TutsNode.com] - Linear Algebra for Machine Learning/13-1.5 Exercise.mp4	651.21 MB
[TutsNode.com] - Linear Algebra for Machine Learning/14-4.1 The Substitution Strategy.en.dfxp	6.62 kB
[TutsNode.com] - Linear Algebra for Machine Learning/14-4.1 The Substitution Strategy.mp4	270.70 MB
[TutsNode.com] - Linear Algebra for Machine Learning/15-4.2 Substitution Exercises.en.dfxp	13.21 kB
[TutsNode.com] - Linear Algebra for Machine Learning/15-4.2 Substitution Exercises.mp4	641.60 MB
[TutsNode.com] - Linear Algebra for Machine Learning/16-4.4 Elimination Exercises.en.dfxp	15.58 kB
[TutsNode.com] - Linear Algebra for Machine Learning/16-4.4 Elimination Exercises.mp4	725.60 MB
[TutsNode.com] - Linear Algebra for Machine Learning/17-Topics.en.dfxp	1.49 kB
[TutsNode.com] - Linear Algebra for Machine Learning/17-Topics.mp4	49.50 MB
[TutsNode.com] - Linear Algebra for Machine Learning/18-5.3 Symmetric and Identity Matrices.en.dfxp	9.31 kB
[TutsNode.com] - Linear Algebra for Machine Learning/18-5.3 Symmetric and Identity Matrices.mp4	121.07 MB
[TutsNode.com] - Linear Algebra for Machine Learning/19-7.4 High-Dimensional Eigenvectors.en.dfxp	7.40 kB
[TutsNode.com] - Linear Algebra for Machine Learning/19-7.4 High-Dimensional Eigenvectors.mp4	142.51 MB
[TutsNode.com] - Linear Algebra for Machine Learning/20-1.2 Solving a System of Equations Algebraically.en.dfxp	12.98 kB
[TutsNode.com] - Linear Algebra for Machine Learning/20-1.2 Solving a System of Equations Algebraically.mp4	115.00 MB
[TutsNode.com] - Linear Algebra for Machine Learning/21-Linear Algebra for Machine Learning (Machine Learning Foundations) - Introduction.en.dfxp	6.62 kB
[TutsNode.com] - Linear Algebra for Machine Learning/21-Linear Algebra for Machine Learning (Machine Learning Foundations) - Introduction.mp4	214.07 MB
[TutsNode.com] - Linear Algebra for Machine Learning/22-1.3 Linear Algebra in Machine Learning and Deep Learning.en.dfxp	18.95 kB
[TutsNode.com] - Linear Algebra for Machine Learning/22-1.3 Linear Algebra in Machine Learning and Deep Learning.mp4	268.86 MB
[TutsNode.com] - Linear Algebra for Machine Learning/23-2.1 Tensors.en.dfxp	7.72 kB
[TutsNode.com] - Linear Algebra for Machine Learning/23-2.1 Tensors.mp4	98.51 MB
[TutsNode.com] - Linear Algebra for Machine Learning/24-2.7 Generic Tensor Notation.en.dfxp	8.96 kB
[TutsNode.com] - Linear Algebra for Machine Learning/24-2.7 Generic Tensor Notation.mp4	198.67 MB
[TutsNode.com] - Linear Algebra for Machine Learning/25-2.3 Vectors and Vector Transposition.en.dfxp	19.10 kB
[TutsNode.com] - Linear Algebra for Machine Learning/25-2.3 Vectors and Vector Transposition.mp4	285.21 MB
[TutsNode.com] - Linear Algebra for Machine Learning/26-Topics.en.dfxp	844.00 B
[TutsNode.com] - Linear Algebra for Machine Learning/26-Topics.mp4	25.18 MB
[TutsNode.com] - Linear Algebra for Machine Learning/27-3.3 Reduction.en.dfxp	8.35 kB
[TutsNode.com] - Linear Algebra for Machine Learning/27-3.3 Reduction.mp4	90.88 MB
[TutsNode.com] - Linear Algebra for Machine Learning/28-2.4 Norms and Unit Vectors.en.dfxp	29.56 kB
[TutsNode.com] - Linear Algebra for Machine Learning/28-2.4 Norms and Unit Vectors.mp4	321.34 MB
[TutsNode.com] - Linear Algebra for Machine Learning/29-2.5 Basis, Orthogonal, and Orthonormal Vectors.en.dfxp	8.42 kB
[TutsNode.com] - Linear Algebra for Machine Learning/29-2.5 Basis, Orthogonal, and Orthonormal Vectors.mp4	80.91 MB
[TutsNode.com] - Linear Algebra for Machine Learning/30-4.3 The Elimination Strategy.en.dfxp	6.48 kB
[TutsNode.com] - Linear Algebra for Machine Learning/30-4.3 The Elimination Strategy.mp4	307.80 MB
[TutsNode.com] - Linear Algebra for Machine Learning/31-5.2 Matrix-by-Matrix Multiplication.en.dfxp	18.60 kB
[TutsNode.com] - Linear Algebra for Machine Learning/31-5.2 Matrix-by-Matrix Multiplication.mp4	598.93 MB
[TutsNode.com] - Linear Algebra for Machine Learning/32-5.1 Matrix-by-Vector Multiplication.en.dfxp	20.16 kB
[TutsNode.com] - Linear Algebra for Machine Learning/32-5.1 Matrix-by-Vector Multiplication.mp4	756.66 MB
[TutsNode.com] - Linear Algebra for Machine Learning/33-3.4 The Dot Product.en.dfxp	11.69 kB
[TutsNode.com] - Linear Algebra for Machine Learning/33-3.4 The Dot Product.mp4	153.97 MB
[TutsNode.com] - Linear Algebra for Machine Learning/34-5.5 Machine Learning and Deep Learning Applications.en.dfxp	22.56 kB
[TutsNode.com] - Linear Algebra for Machine Learning/34-5.5 Machine Learning and Deep Learning Applications.mp4	325.27 MB
[TutsNode.com] - Linear Algebra for Machine Learning/35-6.1 The Frobenius Norm.en.dfxp	6.47 kB
[TutsNode.com] - Linear Algebra for Machine Learning/35-6.1 The Frobenius Norm.mp4	111.89 MB
[TutsNode.com] - Linear Algebra for Machine Learning/36-7.1 The Eigenconcept.en.dfxp	15.25 kB
[TutsNode.com] - Linear Algebra for Machine Learning/36-7.1 The Eigenconcept.mp4	402.70 MB
[TutsNode.com] - Linear Algebra for Machine Learning/37-6.3 Diagonal Matrices.en.dfxp	6.93 kB
[TutsNode.com] - Linear Algebra for Machine Learning/37-6.3 Diagonal Matrices.mp4	125.65 MB
[TutsNode.com] - Linear Algebra for Machine Learning/38-7.2 Exercises.en.dfxp	14.45 kB
[TutsNode.com] - Linear Algebra for Machine Learning/38-7.2 Exercises.mp4	700.68 MB
[TutsNode.com] - Linear Algebra for Machine Learning/39-8.1 The Determinant of a 2 x 2 Matrix.en.dfxp	11.09 kB
[TutsNode.com] - Linear Algebra for Machine Learning/39-8.1 The Determinant of a 2 x 2 Matrix.mp4	146.54 MB
[TutsNode.com] - Linear Algebra for Machine Learning/40-Topics.en.dfxp	1.39 kB
[TutsNode.com] - Linear Algebra for Machine Learning/40-Topics.mp4	46.27 MB
[TutsNode.com] - Linear Algebra for Machine Learning/41-8.3 Exercises.en.dfxp	7.71 kB
[TutsNode.com] - Linear Algebra for Machine Learning/41-8.3 Exercises.mp4	294.38 MB
[TutsNode.com] - Linear Algebra for Machine Learning/42-8.2 The Determinants of Larger Matrices.en.dfxp	14.99 kB
[TutsNode.com] - Linear Algebra for Machine Learning/42-8.2 The Determinants of Larger Matrices.mp4	141.91 MB
[TutsNode.com] - Linear Algebra for Machine Learning/43-8.4 Determinants and Eigenvalues.en.dfxp	14.56 kB
[TutsNode.com] - Linear Algebra for Machine Learning/43-8.4 Determinants and Eigenvalues.mp4	177.48 MB
[TutsNode.com] - Linear Algebra for Machine Learning/44-9.4 Regression via Pseudoinversion.en.dfxp	24.41 kB
[TutsNode.com] - Linear Algebra for Machine Learning/44-9.4 Regression via Pseudoinversion.mp4	288.04 MB
[TutsNode.com] - Linear Algebra for Machine Learning/45-9.2 Media File Compression.en.dfxp	12.21 kB
[TutsNode.com] - Linear Algebra for Machine Learning/45-9.2 Media File Compression.mp4	138.60 MB
[TutsNode.com] - Linear Algebra for Machine Learning/46-9.1 Singular Value Decomposition.en.dfxp	14.29 kB
[TutsNode.com] - Linear Algebra for Machine Learning/46-9.1 Singular Value Decomposition.mp4	194.53 MB
[TutsNode.com] - Linear Algebra for Machine Learning/47-9.3 The Moore-Penrose Pseudoinverse.en.dfxp	17.56 kB
[TutsNode.com] - Linear Algebra for Machine Learning/47-9.3 The Moore-Penrose Pseudoinverse.mp4	240.44 MB
[TutsNode.com] - Linear Algebra for Machine Learning/48-9.6 Resources for Further Study of Linear Algebra.en.dfxp	7.42 kB
[TutsNode.com] - Linear Algebra for Machine Learning/48-9.6 Resources for Further Study of Linear Algebra.mp4	145.43 MB
[TutsNode.com] - Linear Algebra for Machine Learning/49-1.4 Historical and Contemporary Applications.en.dfxp	14.09 kB
[TutsNode.com] - Linear Algebra for Machine Learning/49-1.4 Historical and Contemporary Applications.mp4	252.57 MB
[TutsNode.com] - Linear Algebra for Machine Learning/50-2.2 Scalars.en.dfxp	42.32 kB
[TutsNode.com] - Linear Algebra for Machine Learning/50-2.2 Scalars.mp4	990.11 MB
[TutsNode.com] - Linear Algebra for Machine Learning/51-2.6 Matrices.en.dfxp	14.26 kB
[TutsNode.com] - Linear Algebra for Machine Learning/51-2.6 Matrices.mp4	189.87 MB
[TutsNode.com] - Linear Algebra for Machine Learning/52-2.8 Exercises.en.dfxp	3.74 kB
[TutsNode.com] - Linear Algebra for Machine Learning/52-2.8 Exercises.mp4	85.27 MB
[TutsNode.com] - Linear Algebra for Machine Learning/53-Topics.en.dfxp	943.00 B
[TutsNode.com] - Linear Algebra for Machine Learning/53-Topics.mp4	29.86 MB
[TutsNode.com] - Linear Algebra for Machine Learning/54-6.5 The Trace Operator.en.dfxp	7.30 kB
[TutsNode.com] - Linear Algebra for Machine Learning/54-6.5 The Trace Operator.mp4	114.65 MB
[TutsNode.com] - Linear Algebra for Machine Learning/55-7.3 Eigenvectors in Python.en.dfxp	57.35 kB
[TutsNode.com] - Linear Algebra for Machine Learning/55-7.3 Eigenvectors in Python.mp4	700.92 MB
[TutsNode.com] - Linear Algebra for Machine Learning/56-8.5 Eigendecomposition.en.dfxp	25.78 kB
[TutsNode.com] - Linear Algebra for Machine Learning/56-8.5 Eigendecomposition.mp4	443.35 MB
[TutsNode.com] - Linear Algebra for Machine Learning/57-Linear Algebra for Machine Learning (Machine Learning Foundations) - Summary.en.dfxp	2.50 kB
[TutsNode.com] - Linear Algebra for Machine Learning/57-Linear Algebra for Machine Learning (Machine Learning Foundations) - Summary.mp4	86.41 MB
[TutsNode.com] - Linear Algebra for Machine Learning/58-9.5 Principal Component Analysis.en.dfxp	13.55 kB
[TutsNode.com] - Linear Algebra for Machine Learning/58-9.5 Principal Component Analysis.mp4	207.29 MB

Description

Description

Linear Algebra for Machine Learning LiveLessons provides you with an understanding of the theory and practice of linear algebra, with a focus on machine learning applications.

About the Instructor

Jon Krohn is Chief Data Scientist at the machine learning company untapt. He authored the book Deep Learning Illustrated (Addison-Wesley, 2020), an instant #1 bestseller that has been translated into six languages. Jon is renowned for his compelling lectures, which he offers in-person at Columbia University and New York University, as well as online via O’Reilly, YouTube, and the Super Data Science Podcast. Jon holds a PhD from Oxford and has been publishing on machine learning in leading academic journals since 2010; his papers have been cited over a thousand times.

Skill Level

Intermediate

Learn How To

Appreciate the role of algebra in machine and deep learning
Understand the fundamentals of linear algebra, a ubiquitous approach for solving for unknowns within high-dimensional spaces
Develop a geometric intuition of what’s going on beneath the hood of machine learning algorithms, including those used for deep learning
Be able to more intimately grasp the details of machine learning papers as well as all of the other subjects that underlie ML, including calculus, statistics, and optimization algorithms
Manipulate tensors of all dimensionalities including scalars, vectors, and matrices, in all of the leading Python tensor libraries: NumPy, TensorFlow, and PyTorch
Reduce the dimensionality of complex spaces down to their most informative elements with techniques such as eigendecomposition (eigenvectors and eigenvalues), singular value decomposition, and principal components analysis

Who Should Take This Course

Users of high-level software libraries (e.g., scikit-learn, Keras, TensorFlow) to train or deploy machine learning algorithms who would now like to understand the fundamentals underlying the abstractions, enabling them to expand their capabilities
Software developers who would like to develop a firm foundation for the deployment of machine learning algorithms into production systems
Data scientists who would like to reinforce their understanding of the subjects at the core of their professional discipline
Data analysts or AI enthusiasts who would like to become a data scientist or data/ML engineer and are keen to deeply understand from the ground up the field they’re entering (very wise!)

Course Requirements

Mathematics: Familiarity with secondary school-level mathematics will make the course easier to follow. If you are comfortable dealing with quantitative information—such as understanding charts and rearranging simple equations—then you should be well-prepared to follow along with all of the mathematics.
Programming: All code demos are in Python so experience with it or another object-oriented programming language would be helpful for following along with the hands-on examples.

Released December 2020