The Power of Machine Learning (2023) beginner bootcamp
We will be covering 10 chapters + 1 exam overviewing the key fundamentals to understanding machine learning.
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What You Will Learn!
- Introduction to Machine Learning
- The Math Behind Machine Learning
- Supervised Leaning
- Unsupervised Learning
- Reinforcement Learning
- Overfitting and Underfitting
- Model Evaluation
- Feature Engineering
- Deep Learning
- Real-World Applications of Machine Learning
Description
This course is a comprehensive and intensive introduction to the field of machine learning. It covers the fundamental concepts and techniques used in the field and will provide you with a solid foundation for further study and exploration. The course covers a wide range of topics, including supervised and unsupervised learning, linear and logistic regression, decision trees and random forests, clustering, and model evaluation and selection. These topics are all essential for anyone looking to get a comprehensive understanding of machine learning and how to apply these techniques to real-world problems.
The course is designed for those with little to no prior experience in machine learning and will provide you with the skills and knowledge you need to get started in the field. You will understand how real-world data and common programming tools are used such as Python and scikit-learn to apply the algorithms you learn about. This hands-on approach to learning will ensure that you have a solid understanding of the key principles and methods of machine learning and that you are able to apply these to tackle a range of practical problems.
Whether you are a beginner looking to start your journey in the field of machine learning or a seasoned professional looking to expand your knowledge and skills, this course is designed to provide you with the knowledge and expertise you need to succeed. With a strong focus on hands-on learning, you will have the opportunity to put your new skills into practice and gain a solid understanding of the key concepts and techniques used in machine learning.
Who Should Attend!
- This course is intended for individuals with little to no prior experience in machine learning who are looking to learn about the basics of this field. This includes aspiring data scientists, software engineers, and anyone who wants to understand how machines can learn from data. A basic understanding of mathematics and programming concepts will be helpful but not necessary. The course is designed to be hands-on and action-oriented, with a focus on helping learners apply the concepts they learn to real-world problems.
