BLX 201 – Greek I: Foundations
Created by
Damion Barrett
Description
This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, 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.
What you'll learn
- Handle advanced techniques like Dimensionality Reduction
- Handle specific topics like Reinforcement Learning best
- Know which Machine Learning model to choose for each type of problem
- Reinforcement learning upper confidence bound Thompson sampling
- Model Selection & Boosting fold cross validation parameter
- Use Machine Learning for personal purpose of machine
Requirements
- High School Mathematics Level
- Basic Python Knowledge Required
- Broadband Internet
Curriculum
15 lectures • 2h 29m 12s total length
• Introduction (5:00)
• Course Overview (10:00)
Data Manipulation Tools 6:30 🔒
Importing the libraries 8:30 🔒
• Lecture 1 (5:00)
• Lecture 2 (4:00)
• Lecture 1 (5:00)
• Lecture 2 (4:00)
• Lecture 1 (6:00)
• Lecture 2 (8:00)