basics of machine learning

Upload: frank-evans

Post on 18-Jul-2015

70 views

Category:

Data & Analytics

2 download

Report

Download

Tags:

Embed Size (px):

TRANSCRIPT

ObjectiveEntice you to want to go learn more about machine learning.

Data is huge. People are expensive. Computation is cheap.

Use applied statistics to let the computers program themselves.

Types

Types

Supervised "I have a set of examples with the right answers, I want to learn a pattern and use it on examples where I don't have the answers."

Types

Unsupervised "I have data with no answers, but I want to find a pattern that might lead me to an answer."

TypesReinforcement "I want to start with what I know now, and be able to learn new things as they come along."

Types

Supervised "I have a set of examples with the right answers, I want to learn a pattern and use it on examples where I don't have the answers."

Unsupervised "I have data with no answers, but I want to find a pattern that might lead me to an answer."

Reinforcement "I want to start with what I know now, and be able to learn new things as they come along."

Types

Supervised "I have a set of examples with the right answers, I want to learn a pattern and use it on examples where I don't have the answers."

Unsupervised "I have data with no answers, but I want to find a pattern that might lead me to an answer."

Reinforcement "I want to start with what I know now, and be able to learn new things as they come along."

Regression vs Classification

Supervised Learning

RegressionUse continuous data to make a model that predicts where new data will fit.

ClassificationLabel data into "buckets", and make predictions on which bucket a new data point will fall into.

Where to learn more

Books

Podcasts

Interactive

Where to learn more

Books

Podcasts

Interactive

Where to learn more

Books

Podcasts

Interactive

Where to learn more

Books

Podcasts

Interactive

Where to learn more

frankdevans

Lecture 4: Machine Learning Basics - shuaili8.github.io basics.pdf · Machine Learning Categories •Unsupervised learning •No labeled data •Supervised learning •Use labeled

Basics of Machine Learning

Probability*Basics** for*Machine*Learning*Probability*Basics** for*Machine*Learning* CSC411 Shenlong*Wang* Friday,*January*15,*2015* *Based*on*many*others’*slides*and*resources*from*Wikipedia*

Machine Learning – some basics - Bishop PRML Ch. 1

Natural Language Processing and Machine Learning Basics

Machine Learning Basics - Indian Institute of Technology ...cse.iitkgp.ac.in/~sudeshna/courses/DL17/Backprop-19-Jan-17(1).pdf · Machine Learning Basics Author: Sudeshna Created Date:

Machine Learning Basics - GitHub Pages · 2019-12-13 · 1 Machine Learning basics Why Machine Learning is needed? Main Concepts: Generalization, Model Expressiveness, Over tting

Probability*Basics** for*Machine*Learning*

Basics of Machine Learning€¦ · Basics of Machine Learning Joel Reijonen Lead Data Scientist at Ericsson [email protected]. Ericsson Internal | 2018-02-21 Machine Learning

Topics: GPU basics, accelerators for machine learning

MACHINE LEARNING BASICS David Kauchak CS457 Fall 2011

Bayesian Machine Learning - Cornell University · Bayesian Machine Learning Andrew Gordon Wilson ORIE 6741 Lecture 2: Bayesian Basics Cornell University

Machine Learning and Pattern Recognition *1cm Basics fileOther books D. Barber, Bayesian Reasoning and Machine Learning, Cambridge 2012. C. M. Bishop. Pattern Recognition and Machine

Machine Learning Basics - ECE:Course Page

UVA CS 6316: Machine Learning Lecture 3: Linear Regression ... · Machine Learning Lecture 3: Linear Regression Basics Dr. YanjunQi ... qGraphical models qReinforcement Learning 9/18/19

4 - 1: Basics of machine learning Prof. J.C. Kao, UCLA ...kao/nndl/lectures/ml-basics.pdf4 - 5: Basics of machine learning Prof. J.C. Kao, UCLA Regression example (1D) Let’s say

Machine Learning: Overview Part 1: Basics - selection ...cameron.econ.ucdavis.edu/e240f/machlearn2019_part1.pdf · Machine Learning: Overview Part 1: Basics - selection, shrinkage,

Machine Learning Damon Waring 22 April 2003. 2 of 15 Agenda Problem, Solution, Benefits Problem, Solution, Benefits Machine Learning Overview/Basics Machine

Machine Learning BasicsMachine Learning Basics Lecture slides for Chapter 5 of Deep Learning Ian Goodfellow 2016-09-26

Boosting for Probability Estimation & Cost-Sensitive Learning€¦ · Estimation & Cost-Sensitive Learning. Introduction: Supervised Machine Learning Basics (Classification) Classification

Machine Learning Basics Lecture 1: Linear Regression · Machine Learning Basics Lecture 1: Linear Regression ... Real data: Prostate Cancer ... Linear regression with bias •Given

Machine Learning Basics

Machine Learning Basics III · Machine Learning Basics III Benjamin Roth, Nina Poerner CIS LMU Munchen Benjamin Roth, Nina Poerner (CIS LMU Munchen) Machine Learning Basics III 1

Chapter 1:Machine Learning Basics...Chapter 1:Machine Learning Basics Chapter 2: ReflectInsight – Real-Time Monitoring Chapter 3:Bayes Intuition – Solving the Hit and Run Mystery

CS 2750: Machine Learning Machine Learning Basics + Matlab ...kovashka/cs2750_sp16/kovashka_ml_02.… · Machine Learning Basics + Matlab Tutorial Prof. Adriana Kovashka ... Training

Machine Learning: Supervised Techniques / Unit 2: Basics ... · Unit 2: Basics of Supervised Machine Learning 32 QUESTIONS WE NEED TO ADDRESS Does learning help in the future, i.e

Basics of Machine Learning - Duke University...COMPSCI 527 — Computer Vision Basics of Machine Learning 20 / 23. The State of the Art of Image Classiﬁcation [Image from Russakovsky

Machine Learning Basics Lecture 7: Multiclass classification · 2016. 9. 1. · Machine Learning Basics Lecture 7: Multiclass Classification Princeton University COS 495 Instructor:

Machine Learning Basics II - dl-nlp.github.io

Machine Learning Basics 1. General Introduction

Applied Machine Learning Introductionlasa.epfl.ch/teaching/lectures/ML_Msc/Slides/Introduction_AML.pdfAPPLIED MACHINE LEARNING 10 -To understand the basics of some key algorithms of

Machine Learning Basics - dl.ee.cuhk.edu.hk

Machine Learning Basics · Machine Learning Basics I2DL: Prof. Niessner, Prof. Leal-Taixé 1. Machine Learning Task ... Basic Recipe for Machine Learning •Split your data I2DL:

Machine Learning Basics: Supervised Learning Algorithmssrihari/CSE676/5.7 MLBasics-Supervised.pdfDeep Learning Srihari 1 Machine Learning Basics: Supervised Learning Algorithms Sargur

Machine Learning Lecture Regression basics...Machine Learning Regression basics linear regression, non-linear features (polynomial, RBFs, piece-wise), regularization, cross validation,