Join over 2.5m+ professionals who have enrolled in the Machine Learning program from Stanford University

Software Developers and Engineers, this program provides a broad introduction to machine learning, data mining, 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). The course will also draw from numerous case studies and applications, so that you will also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas. You will gain valuable skills in: Logistic Regression, Artificial Neural Network, Machine Learning (ML),  Algorithms, Machine Learning. Training Modules include: Linear Regression with One Variable, Linear Algebra Review, Linear Regression with Multiple Variables, Octave/Matlab Tutorial, Logistic Regression, Regularization, Neural Networks: Representation, Neural Networks: Learning, Advice for Applying Machine Learning, Machine Learning System Design, Support Vector Machines, Unsupervised Learning, Dimensionality Reduction, Anomaly Detection, Recommender Systems, Large Scale Machine Learning, Application Example: Photo OCR … plus multiple Electives. Much career success, Lawrence Wilson – Artificial Intelligence Academy

Enroll now at: https://fxo.co/87TG