Alliance Micro Solutions provides certified and advanced degree computer instructors and consultants

Join an engaging hands-on learning environment, where you’ll learn:

• Core machine learning mathematics and statistics
• Supervised Learning vs. Unsupervised Learning
• Classification Algorithms including Support Vector Machines, Discriminant Analysis, Naïve Bayes, and Nearest Neighbor
• Regression Algorithms including Linear and Logistic Regression, Generalized Linear Modeling, Support Vector Regression, Decision Trees, and k-Nearest Neighbors (KNN)
• Clustering Algorithms including k-Means, Fuzzy clustering, and Gaussian Mixture
• Neural Networks including Hidden Markov (HMM), Recurrent (RNN), and Long-Short Term Memory (LSTM)
• Dimensionality Reduction, Single Value Decomposition (SVD), and Principle Component Analysis (PCA)
• How to choose an algorithm for a given problem
• How to choose parameters and activation functions
• Ensemble methods

This course has a 50% hands-on labs to 50% lecture ratio with engaging instruction, demos, group discussions, labs, and project work.

Experienced Data Scientists, Data Analysts, Developers, Administrators, Architects, and Managers interested in a deeper exploration of common algorithms and best practices in machine learning.

This course focuses on the mathematics aspect of machine learning as opposed to more general skills and concepts. It is also offered using R or Scala – please inquire for details.