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Google Free Machine Learning Course with TensorFlow APIs | Problem Framing, Data Prep, Clustering, Recommendation, Testing and Debugging & GANs
Machine Learning Crash Course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.
- 30+ exercises
- 25 lessons
- Interactive visualizations of algorithms in action
- Real-world case studies
- Lectures from Google researchers
Prerequisites
Machine Learning Crash Course does not presume or require any prior knowledge in machine learning. However, to understand the concepts presented and complete the exercises, we recommend that students meet the following prerequisites:
- You must be comfortable with variables, linear equations, graphs of functions, histograms, and statistical means.
- You should be a good programmer. Ideally, you should have some experience programming in Python because the programming exercises are in Python. However, experienced programmers without Python experience can usually complete the programming exercises anyway.
Course Content:
- Machine Learning Basics and Advanced Concepts
- Problem Framing
- Data Prep
- Clustering
- Recommendation
- Testing and Debugging
- GANs
