End-to-End Machine Learning: From Idea to Implementation

Build, Manage, and Deploy Machine Learning (AI) Projects with Python and MLOps

Created by: Kıvanç Yüksel
Machine Learning Researcher / Engineer / Enthusiast

What Will I Learn?

• How To Efficiently Build Sustainable And Scalable Machine Learning Projects Using The Best Practices
• Data Versioning
• Distributed Data Processing
• Feature Extraction
• Distributed Model Training
• Model Evaluation
• Experiment Tracking
• Error analysis
• Model Inference
• Creating An Application Using The Model We Train
• Metadata management
• Reproducibility
• MLOps
• MLOps principals
• Machine Learning Operations
• Machine Learning
• Deep Learning
• Artificial Intelligence
• AI

Requirements

• Basic Understanding Of Machine Learning
• Python Programming Language
• You Will Learn The Rest In The Course

Target audience

• Students who are interested in pursuing a career in machine learning project development and want to gain expertise in sustainable and scalable development practices
• Machine learning engineers who are interested in developing machine learning solutions that are scalable and sustainable in the long run
• Data scientists who are looking to expand their skill set to include machine learning project development that is scalable and sustainable
• Researchers who are interested in developing machine learning models more efficiently
• Software developers who want to gain expertise in developing sustainable and scalable machine learning projects
• Start-up founders who want to develop machine learning projects that can be scaled up to meet future demands while also being sustainable
• Technical project managers who want to learn how to effectively manage and oversee sustainable and scalable machine learning projects
• Professionals in the technology industry who want to stay up-to-date with the latest trends and advancements in machine learning project development
• Companies and organizations that want to implement sustainable and scalable machine learning projects to improve their operations, efficiency, and profitability