Machine learning algorithms use computational methods to “learn” information directly from data without assuming a predetermined equation as a model. They can adaptively improve their performance as you increase the number of samples available for learning. Machine learning algorithms are used in applications such as computational finance (credit scoring and algorithmic trading), image processing and computer vision (face recognition, object detection, object recognition), computational biology (tumor detection, drug discovery, and DNA sequencing), energy production (price and load forecasting), natural language processing, speech and image recognition, and advertising and recommendation systems.
Code: NES_SK_2254
Duration: 60 Hrs / 6 Weeks / Customized
Mode: Online / Offline / Onsite
Module 1 - Matlab Programming Fundamentals
Module 2 - Introduction to Applied Machine Learning
Module 3 - Machine Learning with Matlab
Module 4 - Introduction to Applied Machine Learning
Module 5 - Supervised Machine Learning Models
Module 6 - Un-Supervised Machine Learning Models
Module 7 - Resampling Machine Learning Models
Module 8 - Introduction to Deep Learning
Module 9 - Practicals
Target Audience
Training Customization