Specialization - 4 course series
This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning. Through a series of practical case studies, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. You will learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data.
Applied Learning Project
Learners will implement and apply predictive, classification, clustering, and information retrieval machine learning algorithms to real datasets throughout each course in the specialization. They will walk away with applied machine learning and Python programming experience.
What you'll learn
Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems?
Skills you'll gain
Category: Model Evaluation Category: Transfer Learning Category: Deep Learning Category: Regression Analysis Category: Machine Learning Category: Classification Algorithms Category: Text Mining Category: Machine Learning Methods Category: Feature Engineering Category: Machine Learning Algorithms Category: Application Development Category: Applied Machine Learning Category: Predictive Modeling Category: Model Deployment Category: Image Analysis Category: AI Personalization Category: Model Training Category: Python Programming
What you'll learn
Case Study - Predicting Housing Prices
Skills you'll gain
Category: Regression Analysis Category: Model Evaluation Category: Model Optimization Category: Feature Engineering Category: Predictive Modeling Category: Machine Learning Methods Category: Machine Learning Category: Statistical Machine Learning Category: Machine Learning Algorithms Category: Statistical Methods Category: Model Training Category: Supervised Learning Category: Applied Machine Learning Category: Statistical Modeling Category: Algorithms Category: Data Preprocessing
What you'll learn
Case Studies: Analyzing Sentiment & Loan Default Prediction
Skills you'll gain
Category: Logistic Regression Category: Decision Tree Learning Category: Model Evaluation Category: Feature Engineering Category: Scalability Category: Model Optimization Category: Machine Learning Algorithms Category: Classification Algorithms Category: Machine Learning Category: Model Training Category: Supervised Learning Category: Data Preprocessing Category: Risking Category: Text Mining Category: Natural Language Processing Category: Data Cleansing Category: Applied Machine Learning Category: Predictive Modeling Category: Probability & Statistics Category: Classification And Regression Tree (CART)
What you'll learn
Case Studies: Finding Similar Documents
Skills you'll gain
Category: Unsupervised Learning Category: Scalability Category: Machine Learning Algorithms Category: Bayesian Statistics Category: Machine Learning Category: Statistical Modeling Category: Machine Learning Methods Category: Distributed Computing Category: Applied Machine Learning Category: Sampling (Statistics) Category: Algorithms Category: Data Mining Category: Text Mining Category: Unstructured Data Category: Statistical Inference Category: Probability Distribution Category: Statistical Machine Learning
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Instructors
University of Washington
6 Courses501,103 learners
Offered by
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