Machine Learning Terminology Process For Beginners
 
This course offers comprehensive learning and practical application covering:

- Foundational machine learning terminology and processes.
- Understanding the process of framing a machine-learning problem and determining its applicability.
- Techniques for preparing and developing machine learning datasets.
- Solid grasp of feature engineering and data visualization concepts.
- Hands-on experience with model training and evaluation.
- Evaluation of business goals in the context of machine learning.
- Implementation and interpretation of machine learning predictions, and much more.

Additionally, this course provides complete resources and applicable code. This course, developed by Team ClayDesk and consisting of industry-recognized developers and consultants, ensures the highest quality learning experience.

If you're looking to:

- Build a strong foundation in Machine Learning,
- Acquire marketable skills as an IT expert and professional,

Then this course is tailored for you. Please note that this course is not designed for intermediate or advanced-level students.

In this course, you'll learn:

- Fundamental Machine Learning Terminology & Processes.
- Techniques for framing machine-learning problems and their appropriate application.
- Methods for preparing and developing machine learning datasets.
- Understanding of feature engineering and data visualization techniques.
- Practical skills in model training and evaluation.
- Assessment of business goals within machine learning contexts.
- Implementation and interpretation of machine learning predictions.
- Hands-on experience using Python in AWS Rekognition.

Course Components:

- Machine Learning Terminology & Process For Beginners Course