Machine Learning Specialization Coursera Answers / Stanford Machine Learning Coursera Answers Courses Answers:Course 1: Supervised Machine Learning: Regression and Classification Course 2: Advanced Learning AlgorithmsCourse 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 methodsApply best practices for ML development & use unsupervised learning techniques for unsupervised learning including clustering & anomaly detectionBuild recommender systems with a collaborative filtering approach & a content-based deep learning method & build a deep reinforcement learning model Outcomes:Advance your subject-matter expertiseLearn in-demand skills from university and industry expertsMaster a subject or tool with hands-on projectsDevelop a deep understanding of key conceptsEarn a career certificate from Stanford University Share the love Share this content Opens in a new window Opens in a new window Opens in a new window Opens in a new window Opens in a new window Opens in a new window Opens in a new window You Might Also Like Week 2 – Project foundations – Shuffle Q/A 2 Week 3 – Social Media Content Management Module 1: Introduction to Data Analysis Using Spreadsheets Leave a Reply Cancel replyCommentEnter your name or username to comment Enter your email address to comment Enter your website URL (optional) Save my name, email, and website in this browser for the next time I comment.