Machine Learning Course

About Course

Embark on a journey into the fascinating world of Machine Learning with this comprehensive course. Designed for learners with a basic understanding of programming and statistics, this course delves into the principles, techniques, and applications of Machine Learning. Through a blend of theoretical knowledge and practical exercises, you will gain the skills needed to develop, implement, and evaluate machine learning models. The course culminates in a group project and a final evaluation test to assess your mastery of the subject.

Benefits of the course

Introduction to Machine Learning: Understand the basics, history, and key concepts of machine learning.
Supervised Learning: Explore algorithms such as linear regression, logistic regression, decision trees, and support vector machines.
Unsupervised Learning: Learn about clustering techniques like k-means, hierarchical clustering, and dimensionality reduction.
Neural Networks and Deep Learning: Delve into neural networks, deep learning architectures, and frameworks such as TensorFlow and Keras.
Model Evaluation and Validation: Understand techniques for evaluating and validating machine learning models, including cross-validation and metrics.
Feature Engineering: Learn how to select, extract, and transform features to improve model performance.
Natural Language Processing (NLP): Explore NLP techniques and applications in machine learning.
Reinforcement Learning: Understand the basics of reinforcement learning and its applications.
Advanced Topics: Study advanced machine learning techniques such as ensemble methods, transfer learning, and model optimization.
Real-world Applications: Discover practical applications of machine learning across various industries.

Student Feedback

4.5

Total 2 Rating

50%

Instructor

সানি জোবায়ের

4.75

(8 Ratings)

Skill LevelBeginner
Course Duration: 17h 20m

Your Instructors

সানি জোবায়ের

0 Courses
8 Reviews
0 Students

Mahtab Newaz

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5 Reviews
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Target Audience

Students: College and university students with a basic understanding of programming and statistics, looking to dive into machine learning.
Professionals: Data scientists, analysts, and technical professionals seeking to expand their expertise in machine learning for career advancement.
Researchers: Individuals involved in research and development who want to enhance their knowledge and skills in machine learning.
Educators: Teachers and instructors who wish to offer machine learning courses and provide in-depth learning experiences for their students.
Hobbyists and Enthusiasts: Individuals with a passion for technology and data science who have basic skills and knowledge in the field.