Introduction to Pattern Recognition - Great Learning

Mar 31, 2020

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https://www.mygreatlearning.com/blog/introduction-to-pattern-recognition-infographic/ - Patterns are all around us. From the design of our clothes to the voice assistant being used, everything involves some kind of pattern. Recognition of patterns can be done using physically, mathematically or through algorithms. Pattern Recognition has several applications, such as trend analysis, biometric devices, computer vision, and e-commerce. The Image Recognition market is said to reach 38.9 U.S Dollars by 2021.

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Introduction to Pattern Recognition - Great Learning

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Introduction to Pattern Recognition

Introduction to Pattern Recognition. What was that….?. Recognition Or Classification. Recognition Etymologically, the act of thinking again Involves “identifying” or “acknowledging” Classification Etymologically, the act of separating into groups

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Pattern Recognition and Machine Learning. Chapter 3: Linear models for regression. Linear Basis Function Models (1). Example: Polynomial Curve Fitting. Linear Basis Function Models (2). Generally where Á j ( x ) are known as basis functions .

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Pattern Recognition and Machine Learning. Chapter 2: Probability distributions. Parametric Distributions. Basic building blocks: Need to determine given Representation: or ? Recall Curve Fitting. Binary Variables (1). Coin flipping: heads=1, tails=0

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Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning. Chapter 1: Introduction. Example. Handwritten Digit Recognition. Polynomial Curve Fitting . Sum-of-Squares Error Function. 0 th Order Polynomial. 1 st Order Polynomial. 3 rd Order Polynomial. 9 th Order Polynomial. Over-fitting.

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Pattern Recognition and Machine Learning

Source: Bishop book chapter 1 with modifications by Christoph F. Eick. Pattern Recognition and Machine Learning. Chapter 1: Introduction. Polynomial Curve Fitting . Experiment: Given a function; create N training example. What M should we choose?  Model Selection

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Pattern Recognition and Machine Learning

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Chapter 1: Introduction to Pattern Recognition

Chapter 1: Introduction to Pattern Recognition. Machine Perception An example Pattern Recognition Systems The Design Cycle Learning and Adaptation Conclusion.

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Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning. Chapter 3: Linear models for regression. Linear Basis Function Models (1). Example: Polynomial Curve Fitting. Sum-of-Squares Error Function. 0 th Order Polynomial. 1 st Order Polynomial. 3 rd Order Polynomial. 9 th Order Polynomial.

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Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning. Chapter 7: sparse kernel Machines. Outline. The problem: finding a sparse decision (and regression) machine that uses kernels The solution: Support Vector Machines (SVMs) and Relevance Vector Machines (RVMs) The core ideas behind the solutions

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Introduction to Machine Learning and Pattern Recognition. ECE8527: Final Project Professor: Dr. Picone Temple University Brian Thibodeau. Overview. K-Nearest Neighbor Standard and cross validated error Principle Components Analysis (PCA) Evaluation Linear Discriminant Analysis

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Pattern Recognition and Machine Learning

Lars Kasper, December 15 th 2010. Pattern Recognition and Machine Learning. Chapter 12: Continuous Latent Variables. Relation To Other Topics. Last weeks: Approximate Inference Today: Back to data-preprocessing Data representation/Feature extraction “Model-free” analysis

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Introduction to Pattern Recognition

Introduction to Pattern Recognition. Prediction in Bioinformatics What do we want to predict? Features from sequence Data mining How can we predict? Homology / Alignment Pattern Recognition / Statistical Methods / Machine Learning What is prediction? Generalization / Overfitting

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Introduction to Pattern Recognition for human ICT Introduction

Introduction to Pattern Recognition for human ICT Introduction. 2014. 9. 5 Hyunki Hong. Contents. What is pattern recognition? Components of pattern recognition system Pattern recognition apporaches. What is pattern recognition?. • Definitions from the literature

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Pattern Recognition & Machine Learning

Pattern Recognition & Machine Learning. Debrup Chakraborty debrup@delta.cs.cinvestav.mx. The Initials. Time: Wednesday: 16 hrs to 18 hrs Friday : 16 hrs to 18 hrs. Course website: http://delta.cs.cinvestav.mx/ ~debrup/Machine_Learning.html. Books:

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Introduction to Pattern Recognition

For 정보과학회 , Pattern Recognition Winter School. Introduction to Pattern Recognition. 2011 년 2 월 김 진형 KAIST 전산학과 http://ai.kaist.ac.kr/~jkim. What is Pattern R ecognition?. A pattern is an object, process or event that can be given a name Pattern Recognition

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Introduction to Pattern Recognition

Introduction to Pattern Recognition. Center for Machine Perception Czech Technical University in Prague. Vojtěch Franc xfrancv@cmp.felk.cvut.cz. What is pattern recognition?. “The assignment of a physical object or event to one of several prespecified categeries” -- Duda & Hart.

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INTRODUCTION TO STATISTICAL PATTERN RECOGNITION

INTRODUCTION TO STATISTICAL PATTERN RECOGNITION. Thotreingam Kasar Medical Intelligence and Language Engineering Laboratory, Department of Electrical Engineering, Indian Institute of Science, Bangalore, INDIA - 560012. Outline. Basic Probability Theory

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Pattern Recognition: An Introduction

Pattern Recognition: An Introduction. Prof. George M. Papadourakis. Definition. P attern recognition (PR) is a subtopic of machine learning. Is the study of how machines can Observe the environment, learn to distinguish patterns of interest,

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Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning. Chapter 8: graphical models. Bayesian Networks. Directed Acyclic Graph (DAG). Bayesian Networks. General Factorization. Bayesian Curve Fitting (1) . Polynomial. Bayesian Curve Fitting (2) . Plate. Bayesian Curve Fitting (3) .

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Introduction to Pattern Recognition and Machine Learning

Introduction to Pattern Recognition and Machine Learning. Charles Tappert Seidenberg School of CSIS, Pace University.

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Introduction to Pattern Recognition and Machine Learning

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Introduction to Pattern Recognition - Great Learning

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Presentation Transcript

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