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Harvard University

Data Science: Machine Learning

Harvard University via edX

Overview

Perhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data. Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors.

In this course,part ofourProfessional Certificate Program in Data Science, you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system.

You will learn about training data, and how to use a set of data to discover potentially predictive relationships. As you build the movie recommendation system, you will learn how to train algorithms using training data so you can predict the outcome for future datasets. You will also learn about overtraining and techniques to avoid it such as cross-validation. All of these skills are fundamental to machine learning.

Taught by

Rafael Irizarry

Reviews

4.3 rating, based on 3 Class Central reviews

4.3 rating at edX based on 36 ratings

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  • I love the teaching on python. it is well taking me through python. congratulations Harvard university for such a wonderful support that you are giving me
  • Profile image for Luiz Cunha
    Luiz Cunha
    The climax Course of the Data Science Series from Harvard.
    All in all, good. But some important issues prevented the Course from being top notch:
    - some obvious messiness in the Course: assignments on some topics whereas they were not mentioned in the Course content (PCA, Clustering)
    - some bugs in the assignments
    - some important algos not included in the Course content: SVM, Boosting
    The other Courses were almost bug free. So this is disapointing
  • I want appreciation the institution who organized the program to help individuals during this difficult period. I hope to learn new things from here to help me in future .

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