In this Machine Learning Capstone course, you will be using various Python-based machine learning libraries such as Pandas, scikit-learn, Tensorflow/Keras, to:
This course is part of the IBM Machine Learning Professional Certificate
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About this Course
Comfort with Python and completion of the prerequisite IBM Machine Learning Professional Certificate.
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Try Coursera for BusinessWhat you will learn
Compare and contrast different machine learning algorithms by creating recommender systems in Python
Develop a final project using machine learning methods and evaluate your peers’ projects
Predict course ratings by training a neural network and constructing regression and classification models
Create recommendation systems by applying your knowledge of KNN, PCA, and non-negative matrix collaborative filtering
Skills you will gain
- Artificial Neural Network
- Python Programming
- Data Analysis
- Supervised Learning
- unsupervised machine learning
Comfort with Python and completion of the prerequisite IBM Machine Learning Professional Certificate.
Could your company benefit from training employees on in-demand skills?
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Syllabus - What you will learn from this course
Capstone Overview
Exploratory Data Analysis and Feature Engineering
Unsupervised-Learning Based Recommender System
Supervised-Learning Based Recommender Systems
About the IBM Machine Learning Professional Certificate

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