Machine Learning Specialization Coursera Answers / Stanford Machine Learning Coursera Answers
Courses Answers:
Course 1: Supervised Machine Learning: Regression and ClassificationÂ
Course 2: Advanced Learning Algorithms
Course 3: Unsupervised Learning, Recommenders, Reinforcement Learning
About the course:
You’ll learn,
Build ML models with NumPy & scikit-learn, build & train supervised models for prediction & binary classification tasks (linear, logistic regression)
Build & train a neural network with TensorFlow to perform multi-class classification, & build & use decision trees & tree ensemble methods
Apply best practices for ML development & use unsupervised learning techniques for unsupervised learning including clustering & anomaly detection
Build recommender systems with a collaborative filtering approach & a content-based deep learning method & build a deep reinforcement learning model
Outcomes:
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Stanford University
