Machine Learning

• ​Machine Learning A-Z​ Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.

• ​Machine Learning Specialization​ Build Intelligent Applications. Master machine learning fundamentals in four hands-on courses.

• ​Advanced Machine Learning​

  Deep Dive Into The Modern AI Techniques. You will teach computer to see, draw, read, talk, play games and solve industry problems.

• ​Learn Machine Learning​

  Learn advanced machine learning techniques and algorithms -- including how to package and deploy your models to a production environment.

• ​Python for Data Science and Machine Learning Bootcamp​ Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!

• ​Scala and Spark for Big Data and Machine Learning​ Learn the latest Big Data technology - Spark and Scala, including Spark 2.0 DataFrames!

• ​Machine Learning, Data Science and Deep Learning with Python​ Complete hands-on machine learning tutorial with data science, Tensorflow, artificial intelligence, and neural networks

• ​Data Science and Machine Learning Bootcamp with R​ Learn how to use the R programming language for data science and machine learning and data visualization!

• ​Machine Learning (By Georgia Tech)​ Learn about machine learning, the area of artificial intelligence (AI) that is concerned with computational artifacts that modify and improve performance through experience.

• ​Machine Learning (By Columbia University)​ Master the essentials of machine learning and algorithms to help improve learning from data without human intervention.

• ​Robotics: Vision Intelligence and Machine Learning​ Learn how to design robot vision systems that avoid collisions, safely work with humans and understand their environment.

• ​Machine Learning AI Certification by Stanford University (Coursera)​ This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).

• ​Learn AI from ML experts at Google (Google)​ Whether you’re just learning to code or you’re a seasoned machine learning practitioner, you’ll find information and exercises to help you develop your skills and advance your projects.

• ​Machine Learning Certification from University of Washington (Coursera)​ Build Intelligent Applications. Master machine learning fundamentals in four hands-on courses.