What will you in the Machine Learning Foundations: A Case Study Approach Course
Understand real-world applications of machine learning
Distinguish between regression, classification, clustering, and recommendation systems
Apply machine learning techniques using Python and Turi Create
Evaluate model performance using appropriate metrics
Build end-to-end ML applications from data preprocessing to deployment
Program Overview
1. Welcome
Duration: 3 hours
Introduction to machine learning and its business impact
Overview of tools like Python, Jupyter Notebook, and Turi Create
Preview of case study-driven learning structure
2. Regression: Predicting House Prices
Duration: 3 hours
Introduction to regression and its use in predicting house prices
Feature selection, model training, and evaluation
Implementation using real datasets
3. Classification: Analyzing Sentiment
Duration: 3 hours
Basics of classification with a focus on sentiment analysis
Text feature extraction and Naive Bayes classification
Evaluation of prediction accuracy
4. Retrieval: Finding Similar Documents
Duration: 3 hours
Introduction to similarity-based search
Document representation and nearest neighbor methods
Use cases in recommendation and content discovery
5. Recommender Systems: Recommending Products
Duration: 3 hours
Collaborative filtering and matrix factorization
Building recommendation models
Evaluation metrics for recommender systems
6. Deep Learning: Searching for Images
Duration: 3 hours
Intro to deep learning and neural networks
Image classification and feature extraction
Image similarity and search systems
7. Summary and Review
Duration: 2 hours
Recap of key concepts and models
Guidance on advancing further in ML
Final quiz and peer review
Get certificate
Job Outlook
Aspiring Data Scientists: Gain a foundational understanding of ML techniques
Software Developers: Learn to integrate ML features into applications
Business Analysts: Use ML for smarter decision-making
Researchers: Apply ML methods to large data problems
Students: Build a base for AI and data science career paths
Specification: Machine Learning Foundations: A Case Study Approach
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