Machine Learning
Description The course covers practical issues in Machine learning which includes programming in Python, as well as a wide range of algorithms for supervised and unsupervised learning. The course will also discuss recent applications of machine learning such as recommendation systems, email spam detection, stock market prediction and sentiment analysis to determine the sentiment or opinion of a given text. This course is designed to give you the practical experience you need to quickly apply these techniques to new problems.
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47 Students enrolled
Requirements
- The course is dedicated for individuals interested in Machine Learning who have a basic understand of probabilities, statistics and algebra and fundamental background on IT Programming with focus on python who wants to create added value to the businesses by using powerful Machine Learning tools.
Description
Description The course covers practical issues in Machine learning which includes programming in Python, as well as a wide range of algorithms for supervised and unsupervised learning. The course will also discuss recent applications of machine learning such as recommendation systems, email spam detection, stock market prediction and sentiment analysis to determine the sentiment or opinion of a given text. This course is designed to give you the practical experience you need to quickly apply these techniques to new problems. Target Audience The course is dedicated for individuals interested in Machine Learning who have a basic understand of probabilities, statistics and algebra and fundamental background on IT Programming with focus on python who wants to create added value to the businesses by using powerful Machine Learning tools. Training Content • Introduction to Machine Learning • Naive Bayes classifier • Support Vector Machine • K-Nearest Neighbors • Bayesian Machine Learning • Bootstrap and Re-sampling methods • Deep Learning and Optimization techniques
Courses
- 47
