Faisalsardar1
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Naive Bayes, Laplace Smoothing summary
Outline Naive Bayes Laplacesmoothing Event Models Kernel Methods
- Package deal
- Summary
- • 7 pages •
Outline Naive Bayes Laplacesmoothing Event Models Kernel Methods
Gaussian discriminant analysis. Naive Bayes.
Gaussian discriminant analysis & it is model Naive Bayes.
- Package deal
- Summary
- • 6 pages •
Gaussian discriminant analysis & it is model Naive Bayes.
Gaussian discriminant analysis. Naive Bayes.Laplace Smoothing.
Generative Learning algorithms Gaussian discriminant analysis. Naive Bayes. Laplace Smoothing.
- Package deal
- Class notes
- • 14 pages •
Generative Learning algorithms Gaussian discriminant analysis. Naive Bayes. Laplace Smoothing.
Linear Algebra
Outline 1 Basic Concepts and Notation 2 Matrix Multiplication 3 Operations and Properties 4 Matrix Calculus
- Package deal
- Presentation
- • 29 pages •
Outline 1 Basic Concepts and Notation 2 Matrix Multiplication 3 Operations and Properties 4 Matrix Calculus
Linear Algebra Review
Contents 1 Basic Concepts and Notation 2 1.1 Basic Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2 Matrix Multiplication 3 2.1 Vector-Vector Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Matrix-Vector Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.3 Matrix-Matrix Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3 Operations and Properties 7 3.1 The Identity Matrix and Diagonal Matric...
- Package deal
- Class notes
- • 94 pages •
Contents 1 Basic Concepts and Notation 2 1.1 Basic Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2 Matrix Multiplication 3 2.1 Vector-Vector Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Matrix-Vector Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.3 Matrix-Matrix Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3 Operations and Properties 7 3.1 The Identity Matrix and Diagonal Matric...
Dataset split; Exponential family. Generalized Linear Models.
Perception Exponential Family Generalized Linear Models Soft max Regression Multiclass Classification
- Package deal
- Summary
- • 8 pages •
Perception Exponential Family Generalized Linear Models Soft max Regression Multiclass Classification
Supervised learning setup
Supervised learning Linear Regression 1 LMS algorithm 2 The normal equations 2.1 Matrix derivatives 3 Probabilistic interpretation and more
- Package deal
- Class notes
- • 28 pages •
Supervised learning Linear Regression 1 LMS algorithm 2 The normal equations 2.1 Matrix derivatives 3 Probabilistic interpretation and more
computational biology overview
• Atomic-level modeling of biological macromolecules – Energy functions and their relationship to molecular conformation – Molecular dynamics simulation – Protein structure prediction – Protein design – Ligand docking • Coarser-level modeling and imaging-based methods – Fourier transforms and convolution – Image analysis – Microscopy – X-ray crystallography – Cryoelectron microscopy – Diffusion and cellular-level simulation • Recurring themes
- Summary
- • 72 pages •
• Atomic-level modeling of biological macromolecules – Energy functions and their relationship to molecular conformation – Molecular dynamics simulation – Protein structure prediction – Protein design – Ligand docking • Coarser-level modeling and imaging-based methods – Fourier transforms and convolution – Image analysis – Microscopy – X-ray crystallography – Cryoelectron microscopy – Diffusion and cellular-level simulation • Recurring themes
intro to cryo-electron microscopy
is a cryomicroscopy technique applied on samples cooled to cryogenic temperatures and embedded in an environment of vitreous water. An aqueous sample solution is applied to a grid-mesh and plunge-frozen in liquid ethane or a mixture of liquid ethane and propane.[2] While development of the technique began in the 1970s, recent advances in detector technology and software algorithms have allowed for the determination of biomolecular structures at near-atomic resolution.[3] This has attracted wide ...
- Class notes
- • 69 pages •
is a cryomicroscopy technique applied on samples cooled to cryogenic temperatures and embedded in an environment of vitreous water. An aqueous sample solution is applied to a grid-mesh and plunge-frozen in liquid ethane or a mixture of liquid ethane and propane.[2] While development of the technique began in the 1970s, recent advances in detector technology and software algorithms have allowed for the determination of biomolecular structures at near-atomic resolution.[3] This has attracted wide ...
Computational Biology exam + answers
Test Details The exam will be held on Friday, December 10, 2021 from 3:30 PM PM - 6:30 PM (in 320-105). The exam will be closed-book, but you may consult one double-sided 8.5x11 page (or two single-sided pages). Instructions These are practice questions in the style of questions you might expect on the exam. Each question should be answerable in a few sentences (that is, you’re not required to provide a great deal of detail). Question 1: Compare and contrast the energy functions used f...
- Exam (elaborations)
- • 3 pages •
Test Details The exam will be held on Friday, December 10, 2021 from 3:30 PM PM - 6:30 PM (in 320-105). The exam will be closed-book, but you may consult one double-sided 8.5x11 page (or two single-sided pages). Instructions These are practice questions in the style of questions you might expect on the exam. Each question should be answerable in a few sentences (that is, you’re not required to provide a great deal of detail). Question 1: Compare and contrast the energy functions used f...