Advanced Predictive Techniques With Scikit-Learn & TensorFlow

Colleagues, the Advanced Predictive Techniques With Scikit-Learn And TensorFlow program will equip you to use ensemble methods to improve accuracy in classification and regression problems. Ensemble methods improve prediction accuracy by combining in a clever way predictions from many individual predictors. Artificial Neural Networks are models loosely based on how neural networks work in a living being. This course introduces the use of Deep Learning models for Predictive Analytics using the powerful TensorFlow library. Learn to use ensemble algorithms to combine many individual predictors to produce better predictions, apply advanced techniques such as dimensionality reduction to combine features and build better models, evaluate models and choose the optimal hyper-parameters using cross-validation, grasp the foundations for working and building models using Neural Networks and understand different techniques to solve problems that arise when doing Predictive Analytics in the real world. Training modules include: 1) Ensemble Methods for Regression and Classification, 2) Cross-Validation and Parameter Tuning, 3) Working with Features, 4) Introduction to Artificial Neural Networks and TensorFlow, and 5) Predictive Analytics with TensorFlow and Deep Neural Networks.  

Enroll today (individuals & teams welcome): https://tinyurl.com/4tyd7vjc 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy