“Machine Learning From Basic to Advanced” is a comprehensive course designed to provide students with a complete understanding of machine learning concepts and techniques. The course covers the fundamentals of machine learning, including data preprocessing, feature selection, and model training and evaluation.
It also covers advanced topics such as deep learning, neural networks, and natural language processing. Students will learn how to use popular machine learning tools and libraries such as Python, TensorFlow, and scikit-learn. Through a series of hands-on exercises and real-world projects, students will have the opportunity to apply their knowledge and build their own machine learning models.
The course is perfect for beginners who want to learn machine learning from scratch, as well as for intermediate developers who want to expand their knowledge of machine learning techniques. By the end of the course, students will have a solid foundation in machine learning concepts and techniques, and the ability to use machine learning to solve real-world problems.
Machine Learning From Basic to Advanced Course Description
Are you ready to start your path to becoming a Machine Learning Engineer!
This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!
Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems!
This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Machine Learning as well as Data Scientist!
Interested in the field of Machine Learning? Then this course is for you!
This course has been designed by Code Warriors the ML Enthusiasts so that we can share our knowledge and help you learn complex theories, algorithms, and coding libraries in a simple way.
We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.
This course is fun and exciting, but at the same time, we dive deep into Machine Learning. It is structured the following way:
Part 1 – Data Preprocessing
Part 2 – Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression.
Part 3 – Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
Part 4 – Clustering: K-Means, Hierarchical Clustering.
And as a bonus, this course includes Python code templates which you can download and use on your own projects.