Machine Learning: Classification

Machine Learning: Classification

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Английский
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35 h
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Source
  • From www.coursera.org
Conditions
  • Self-paced
  • Free Access
  • Fee-based Certificate
More info
  • 7 Sequences
  • Introductive Level
  • Субтитры доступны на Arabic

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Course details

Syllabus

  • Week 1 - Welcome!
    Classification is one of the most widely used techniques in machine learning, with a broad array of applications, including sentiment analysis, ad targeting, spam detection, risk assessment, medical diagnosis and image classification. The core goal of classifi...
  • Week 1 - Linear Classifiers & Logistic Regression
    Linear classifiers are amongst the most practical classification methods. For example, in our sentiment analysis case-study, a linear classifier associates a coefficient with the counts of each word in the sentence. In this module, you will become proficient i...
  • Week 2 - Learning Linear Classifiers
    Once familiar with linear classifiers and logistic regression, you can now dive in and write your first learning algorithm for classification. In particular, you will use gradient ascent to learn the coefficients of your classifier from data. You first will ne...
  • Week 2 - Overfitting & Regularization in Logistic Regression
    As we saw in the regression course, overfitting is perhaps the most significant challenge you will face as you apply machine learning approaches in practice. This challenge can be particularly significant for logistic regression, as you will discover in this m...
  • Week 3 - Decision Trees
    Along with linear classifiers, decision trees are amongst the most widely used classification techniques in the real world. This method is extremely intuitive, simple to implement and provides interpretable predictions. In this module, you will become familiar...
  • Week 4 - Preventing Overfitting in Decision Trees
    Out of all machine learning techniques, decision trees are amongst the most prone to overfitting. No practical implementation is possible without including approaches that mitigate this challenge. In this module, through various visualizations and investigatio...
  • Week 4 - Handling Missing Data
    Real-world machine learning problems are fraught with missing data. That is, very often, some of the inputs are not observed for all data points. This challenge is very significant, happens in most cases, and needs to be addressed carefully to obtain great per...
  • Week 5 - Boosting
    One of the most exciting theoretical questions that have been asked about machine learning is whether simple classifiers can be combined into a highly accurate ensemble. This question lead to the developing of boosting, one of the most important and practical ...
  • Week 6 - Precision-Recall
    In many real-world settings, accuracy or error are not the best quality metrics for classification. You will explore a case-study that significantly highlights this issue: using sentiment analysis to display positive reviews on a restaurant website. Instead of...
  • Week 7 - Scaling to Huge Datasets & Online Learning
    With the advent of the internet, the growth of social media, and the embedding of sensors in the world, the magnitudes of data that our machine learning algorithms must handle have grown tremendously over the last decade. This effect is sometimes called "Big D...

Prerequisite

None.

Instructors

Carlos Guestrin
Amazon Professor of Machine Learning
Computer Science and Engineering

Emily Fox
Amazon Professor of Machine Learning
Statistics

Editor

L'Université de Washington est une université publique de recherche à Seattle , Washington. Fondée le 4 novembre 1861 sous le nom de Territorial University, Washington est l'une des plus anciennes universités de la côte ouest, il a été établi à Seattle environ une décennie après la fondation de la ville.

L'université possède un campus principal de 703 acres situé dans le quartier universitaire de la ville , ainsi que des campus à Tacoma et Bothell. Dans l'ensemble, UW comprend plus de 500 bâtiments et plus de 20 millions de pieds carrés bruts d'espace, y compris l'un des plus grands systèmes de bibliothèques au monde avec plus de 26 bibliothèques universitaires, centres d'art, musées, laboratoires, amphithéâtres et stades.

Washington est l'institution phare des six universités publiques de l'État de Washington. Il est connu pour sa recherche médicale, technique et scientifique.

Platform

Coursera - это цифровая компания, предлагающая массовые открытые онлайн-курсы, основанные учителями компьютеров Эндрю Нгом и Стэнфордским университетом Дафни Коллер, расположенные в Маунтин-Вью, штат Калифорния.

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