University of Colorado Boulder
Machine Learning: Theory and Hands-on Practice with Python Specialization
University of Colorado Boulder

Machine Learning: Theory and Hands-on Practice with Python Specialization

Develop Foundational Machine Learning Skills. Add Supervised, Unsupervised, and Deep Learning techniques to your Data Science toolkit.

Taught in English

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Geena Kim

Instructor: Geena Kim

9,154 already enrolled

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Specialization - 3 course series

Get in-depth knowledge of a subject

3.5

(47 reviews)

Intermediate level

Recommended experience

3 months at 10 hours a week
Flexible schedule
Learn at your own pace
Progress towards a degree

What you'll learn

  • Explore several classic Supervised and Unsupervised Learning algorithms and introductory Deep Learning topics.

  • Build and evaluate Machine Learning models utilizing popular Python libraries and compare each algorithm’s strengths and weaknesses.

  • Explain which Machine Learning models would be best to apply to a Machine Learning task based on the data’s properties.

  • Improve model performance by tuning hyperparameters and applying various techniques such as sampling and regularization.

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Specialization - 3 course series

Get in-depth knowledge of a subject

3.5

(47 reviews)

Intermediate level

Recommended experience

3 months at 10 hours a week
Flexible schedule
Learn at your own pace
Progress towards a degree

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Specialization - 3 course series

Introduction to Machine Learning: Supervised Learning

Course 139 hours3.3 (51 ratings)

What you'll learn

  • Use modern machine learning tools and python libraries.

  • Compare logistic regression’s strengths and weaknesses.

  • Explain how to deal with linearly-inseparable data.

  • Explain what decision tree is & how it splits nodes.

Skills you'll gain

Category: Hyperparameter
Category: sklearn
Category: ensembling
Category: Decision Tree

Unsupervised Algorithms in Machine Learning

Course 238 hours3.6 (10 ratings)

What you'll learn

  • Explain what unsupervised learning is, and list methods used in unsupervised learning.

  • List and explain algorithms for various matrix factorization methods, and what each is used for.

  • List and explain algorithms for various matrix factorization methods, and what each is used for.

Skills you'll gain

Category: Cluster Analysis
Category: Dimensionality Reduction
Category: Unsupervised Learning
Category: Recommender Systems
Category: Matrix Factorization

Introduction to Deep Learning

Course 360 hours3.6 (27 ratings)

What you'll learn

  • Apply different optimization methods while training and explain different behavior.

  • Use cloud tools and deep learning libraries to implement CNN architecture and train for image classification tasks.

  • Apply deep learning package to sequential data, build models, train, and tune.

Skills you'll gain

Category: Recurrent Neural Network
Category: Convolutional Neural Network
Category: Artificial Neural Network
Category: Unsupervised Deep Learning
Category: Deep Learning

Instructor

Geena Kim
University of Colorado Boulder
3 Courses20,871 learners

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Get a head start on your degree

This Specialization is part of the following degree programs offered by University of Colorado Boulder. If you are admitted and enroll, your coursework can count toward your degree learning and your progress can transfer with you.

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