*** Proof of Product ***
Exploring the Essential Features of “Stone River eLearning – Machine Learning with Jupyter Notebooks in Amazon AWS”
Machine Learning with Jupyter Notebooks in Amazon AWS
A comprehensive look into Machine Learning using Dynamic Programming, Python and SageMaker service offered by Amazon AWS
Are you a company or a IT administrator, data center architect, consultant, enterprise architect, data protection officer, programmer, data security specialist, or big data analyst and want to gain fundamental and intermediate level skills and enjoy a fascinating high paying career?
Or maybe you just want to learn additional tips and techniques taking to a whole new level?
In this course, you’ll learn and practice:
- Machine Learning topics
- Jupyter Notebooks
- Reinforcement Learning
- Machine Learning Services in AWS
- AWS Sagemaker
- Dynamic Programming
- Q-Learning
- Understand best practices, and much more….
Who this course is for:
- Beginner IT professionals who want to get in the forefront of the Artificial Intelligence and Machine Learning game
- Anyone who is curios about machine learning
Requirements
- Basic knowledge of AWS services
- Valid AWS account is required, that is, a credit card is required to open an AWS account
Course Curriculum
- Introduction
Course Agenda (3:32)
Creating a billing alert (5:06)
AWS Management Console (4:05)
EC2 Dashboard Experience (3:55) - Machine Learning
Intro to Reinforcement Learning (6:19)
Reinforcement Learning in Action (6:48)
Basics of Machine Learning (7:50)
Supervised Learning (8:46)
Unsupervised Learning (9:55)
Deep Neural Networks (13:59)
Neural Network Techniques (20:50) - Reinforcement Learning
Modeling a Reinforcement Learning environment (7:59)
What is dynamic programming (10:28)
What is Q Learning ? (6:37)
Demonstrating Q Learning (4:48)
QLearning Shortest Path (4:43)
Dynamic Programming in Action (13:11) - Jupyter Notebooks
What is a notebook and Installing Jupyter ? (4:19)
Creating first Jupyter Notebook through Anaconda (7:36)
Looking at Jupyter Kernels (5:20)
Data Analysis in Jupyter (6:43)
Plotting with Matplotlib in Jupyter (3:43) - Machine Learning in AWS
The AWS Machine Learning Service (7:25)
First steps in building a Machine Learning model (10:45)
Understanding AWS Datasources (9:54)
Machine Learning Training Models in AWS (7:24)
Importance of Feature Transformation (6:26)
Evaluating Models (13:40)
Creating a datasource and model in AWS (7:01)
Serverless machine learning inference with AWS Lambda (8:31) - AWS SageMaker
What is SageMaker (5:00)
Setting up AWS for SageMaker (12:11)
Machine Learning in SageMaker (5:30)
Intro to Linear Learner (5:27)
Preparing data for Linear Learner algorithm (6:43)
Training data using Linear Learner (7:18)
Creating a Hyperparameter Tuning Job (9:54)
Please see the full list of alternative group-buy courses available here: https://lunacourse.com/shop/
