Machine Learning Foundations: A Case Study Approach

Machine Learning Foundations: A Case Study Approach

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Английский
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30 h
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  • From www.coursera.org
Conditions
  • Self-paced
  • Free Access
  • Fee-based Certificate
More info
  • 6 Sequences
  • Introductive Level
  • Субтитры доступны на Korean, Vietnamese, Chinese

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Course details

Syllabus

  • Week 1 - Welcome
    Machine learning is everywhere, but is often operating behind the scenes.

    This introduction to the specialization provides you with insights into the power of machine learning, and the multitude of intelligent applications you personally will be able to dev...

  • Week 2 - Regression: Predicting House Prices
    This week you will build your first intelligent application that makes predictions from data.

    We will explore this idea within the context of our first case study, predicting house prices, where you will create models that predict a continuous value (price) ...

  • Week 3 - Classification: Analyzing Sentiment
    How do you guess whether a person felt positively or negatively about an experience, just from a short review they wrote?

    In our second case study, analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input feat...

  • Week 4 - Clustering and Similarity: Retrieving Documents
    A reader is interested in a specific news article and you want to find a similar articles to recommend. What is the right notion of similarity? How do I automatically search over documents to find the one that is most similar? How do I quantitatively repres...
  • Week 5 - Recommending Products
    Ever wonder how Amazon forms its personalized product recommendations? How Netflix suggests movies to watch? How Pandora selects the next song to stream? How Facebook or LinkedIn finds people you might connect with? Underlying all of these technologies for...
  • Week 6 - Deep Learning: Searching for Images
    You’ve probably heard that Deep Learning is making news across the world as one of the most promising techniques in machine learning. Every industry is dedicating resources to unlock the deep learning potential, including for tasks such as image tagging, objec...
  • Week 6 - Closing Remarks
    In the conclusion of the course, we will describe the final stage in turning our machine learning tools into a service: deployment.

    We will also discuss some open challenges that the field of machine learning still faces, and where we think machine learning ...

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.

Coursera работает с ведущими университетами и организациями, чтобы сделать некоторые из своих курсов доступными в Интернете, и предлагает курсы по многим предметам, включая: физику, инженерию, гуманитарные науки, медицину, биологию, социальные науки, математику, бизнес, информатику, цифровой маркетинг, науку о данных и другие предметы.

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