4 Weekends Only Machine Learning Beginners Training Course Bethlehem

This event has been UPDATED since it was first published. View the UPDATED & Detailed Machine Learning Training course for beginners Information here.

4 Weekends Only Machine Learning training course for Beginners is a 4 weekends long Instructor-led and guided training with Practical Hands-On Lab exercises to be taught over 4 Weekends, 2 sessions per weekend, 2 hours per session.

• The medium of instruction is English.
• All Published Ticket Prices are in US Dollars.

• January 16, 2021 - February 7, 2021 US Pacific time
• 4 Weekends | 2 Hours on Saturdays, 2 Hours on Sundays every weekend US Pacific time
• 7:30 AM - 9:30 AM US Pacific time each of those days
• Please click here to add your city name and check your local date and time for the first session to be held on January 16, 2021 at 7:30 AM US Pacific Time.

• 4 weekends, 8 sessions, 16 hours of total Instructor-led and guided training
• Training material, instructor handouts and access to useful resources on the cloud provided
• Practical Hands-on Lab exercises provided
• Actual code and scripts provided
• Real-life Scenarios

• Demonstrate the knowledge of decision tree learning, artificial neural networks, Bayesian networks, instance-based learning, analytic learning, reinforcement learning, genetic programming, deep learning, etc.
• Demonstrate the knowledge of MLlib on Spark, or other machine learning libraries.
• Practice examples of machine learning programming and open source machine learning tools, and implement example machine learning applications.

Anyone who wants to learn machine learning for any purpose

• Computer concepts
• Knowledge of any programming language is desirable but not required.
• Knowledge of these concepts is nice to have but not required: Data Structures and Computer Algorithms, Statistics, Probability, Linear Algebra, Calculus

1. Introduction to Machine Learning

2. Working with Python or R

3. Machine Learning Techniques

• Types of Learning
• Applying Machine Learning
• Machine learning system, design

4. Types of Machine Learning Algorithms

• Supervised Learning
• -Regression
• -Classification
• Unsupervised Learning
• -Clustering
• - Recommendation
• deep learning
• Semi-Supervised Learning
• Reinforcement

5. Supervised Learning Regression

6. Supervised Learning Classification

7. Unsupervised Learning

• Clustering
• Recommendation
• deep learning

8. Spark Core and MLLib

• Spark Core
• Spark Architecture
• Working with RDDs
• Machine learning with Spark – Mllib

9. Common Machine Learning Algorithms

• Linear Regression
• Logistic Regression
• Decision Tree
• SVM
• Naive Bayes
• KNN
• KMeans
• Random Forest
• Dimensionality Reduction Algorithms
• Gradient Boost & Adaboost
• artificial neural networks
• Bayesian networks
• instance-based learning
• analytic learning,
• reinforcement
• genetic programming

Event Venue & Nearby Stays

IT Training Center, Tech Training Solutions, Bethlehem, United States