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Overview
How can you take your knowledge of machine learning (ML) concepts and how Python works within them to the next level? This data science course will give you a strong grounding in the theories of machine learning, along with practical scenarios and experience of building, validating and deploying machine learning models. Youll learn basic machine learning and artificial intelligence (AI) concepts and get to understand relationships in complex data. Learn to use the Python programming language and examine how state-of-the-art...
Syllabus
- Introduction to Course and Machine Learning
- Course Introduction
- Introduction to Machine Learning
- Exploratory Data Analysis for Regression
- Visualisation for High Dimensions
- Wrapping Up the Week
- Data Exploration & Preparation
- Exploratory Data Analysis for Classification
- Data Cleaning
- Data Preparation
- Data Preparation and Cleaning using Python
- Feature Engineering
- Weekly Wrap-Up
- Regression & Classification
- Regression
- Putting Regression Concepts Into Practice
- Classification
- RoC Curves
- Putting Classification Concepts Into Practice
- Weekly Wrap-Up
- Principles & Techniques of Model Improvement
- Principles of Model Improvement
- Techniques for Improving Models
- Cross Validation
- Dimensionality Reduction
- Introduction to Decision Trees
- Ensemble Methods: Boosting
- Weekly Wrap-Up
- Machine Learning Algorithms & Unsupervised Learning
- Ensemble Methods: Descent & Decision Forests
- Advanced Machine Learning Algorithm: Neural Networks
- Advanced Machine Learning Algorithm: SVMs
- Advanced Machine Learning Algorithm: Naive Bayes Models
- Unsupervised Machine Learning
- Unsupervised Machine Learning Labs
- Wrapping up the Course
Instructor
CloudSwyft Global Systems, Inc.
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