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Stone River Elearning – Machine Learning with Jupyter Notebooks in Amazon AWS
Stone River Elearning – 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)
Sale Page: https://stoneriverelearning.com/p/machine-learning-with-jupyter-notebooks-in-amazon-aws
Archive: https://archive.ph/wip/uTPLw
Shipping method
– After making a purchase, you will see a View your order link to the Downloads page. Here you can download all the files related to your order.
– In case the link is broken for any reason, please contact us and we will resend a new download link.
– If you can’t find the download link, please don’t worry about it. This course is usually available and shipped within one day
– The course you purchased will have lifetime access
– Our support staff is the best by far! Please contact us at email: cs.hodollar@gmail.com and we will be happy to help!
