Machine Learning Training Bootcamp : Tonex Experts

Machine Learning training bootcamp is a 3-day specialized training course that covers the essentials of machine learning, a shape and utilization of man-made reasoning (AI).
Machine learning computerizes the information investigation process by empowering PCs, machines and IoT to learn and adjust through experience connected to particular undertakings without unequivocal programming. 

Learning Objectives:

• Learn about Artificial Intelligence and Machine Learning 
• List similarities and differences between AI, Machine Learning and Data Mining 
• Learn how Artificial Intelligence uses data to offer solutions to existing problems 
• Explore how Machine Learning goes beyond AI to offer data necessary for a machine to learn, adapt and optimize / Clarify how Data Mining can serve as foundation for AI and machine learning to use existing information to highlight patterns 
• List the various applications of machine learning and related algorithms 
• Learn how to classify the types of learning such as supervised and unsupervised learning 
• Implement supervised learning techniques such as linear and logistic regression 
• Use unsupervised learning algorithms including deep learning, clustering and recommender systems (RS) used to help users find new items or services, such as books, music, transportation, people and jobs based on information about the user or the recommended item 
• Learn about classification data and Machine Learning models 
• Select the best algorithms applied to Machine Learning 
• Make accurate predictions and analysis to effectively solve potential problems 
• List Machine Learning concepts, principles, algorithms, tools and applications 
• Learn the concepts and operation of support neural networks, vector machines, kernel SVM, naive bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means and clustering 
• Comprehend the theoretical concepts and how they relate to the practical aspects of machine learning / Be able to model a wide variety of robust machine learning algorithms including deep learning, clustering and recommendation systems 

Course Agenda and Topics:

• The Basics of Machine Learning 
• Machine Learning Techniques, Tools and Algorithms 
• Data and Data Science 
• Review of Terminology and Principles 
• Applied Artificial Intelligence (AI) and Machine Learning 
• Popular Machine Learning Methods 
• Learning Applied to Machine Learning 
• Principal component Analysis 
• Principles of Supervised Machine Learning Algorithms 
• Principles of Unsupervised Machine Learning 
• Regression Applied to Machines Learning 
• Principles of Neural Networks 
• Large Scale Machine Learning 
• Introduction to Deep Learning 
• Applying Machine Learning 
• Overview of Algorithms 
• Overview of Tools and Processes 

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Machine Learning Training Bootcamp