Data Science: Machine Learning

Mark as Favorite Share
image

What Will You Learn?

The basics of machine learning
How to perform cross-validation to avoid overtraining
Several popular machine learning algorithms
How to build a recommendation system
What is regularization and why it is useful

About This Course

Provider: Edx
Format: Online
Duration: 32 hours to complete [Approx]
Target Audience: Beginners
Learning Objectives: Upon completion, you will be able to implement popular machine learning algorithms, apply principal component analysis, and incorporate regularization techniques to construct a proficient movie recommendation system.
Course Prerequisites: Fundamental programming skills, Statistical concepts such as probability, inference, and modeling
Assessment and Certification: Earn a Certificate upon completion from the relevant Provider
Instructor: Harvard University
Key Topics: Machine Learning Algorithms, Algorithms, Data Science, Recommender Systems, Machine Learning, Forecasting, Speech Recognition, Principal Component Analysis
Topic Covered: 
  1. - Introduction and Welcome
  2. - Introduction to Machine Learning
  3. - Machine Learning Basics
  4. - Smoothing and Linear Regression for Prediction
  5. - Cross-validation and k-Nearest Neighbors
  6. - The Caret Package
  7. - Model Fitting and Recommendation Systems
  8. - Final Assessment and Course Wrap-Up

0 Comments

No reviews yet !!

Please login first