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Machine Learning Specialization Coursera Answers / Stanford Machine Learning Coursera Answers

Courses Answers:

Course 1: Supervised Machine Learning: Regression and Classification 
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


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

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