Complete Guide to AWS Certified Machine Learning – Specialty and Practice Test
What you’ll learn
AWS SageMaker, AI and Machine Learning
- Learn AWS Machine Learning algorithms, Predictive Quality assessment, Model Optimization
- Integrate predictive models with your application using simple and secure APIs
- Convert your ideas into highly scalable products in days
- Practice test and resources to gain AWS Certified Machine Learning – Specialty Certification
- Familiarity with Python
- AWS Account – I will walk through steps to set up one
- Basic knowledge of Pandas, Numpy, Matplotlib
Learn about cloud-based machine learning algorithms, how to integrate with your applications and Certification Prep*** SageMaker Lectures – DeepAR – Time Series Forecasting, XGBoost – Gradient Boosted Tree algorithm in-depth with hands-on. XGBoost has won several competitions and is a very popular Regression and Classification Algorithm, Factorization Machine based Recommender Systems and PCA for dimensionality reduction ***
There are several courses on Machine Learning and AI. What is unique about this course?
Here are the top reasons:
1. Cloud-based machine learning keeps you focused on the current best practices.
2. In this course, you will learn the most useful algorithms. Don’t waste your time sifting through mountains of techniques that are in the wild
4. Cloud-based service is straightforward to integrate with your application and has support for a wide variety of programming languages.
5. Whether you have small data or big data, the elastic nature of the AWS cloud allows you to handle them all.
In this course, you will learn with hands-on labs and work on exciting and challenging problems
What exactly will you learn in this course?
Here are the things that you will learn in this course:
You will learn how to deploy a Notebook instance on the AWS Cloud.
You will gain insight into algorithms provided by SageMaker service
Learn how to train, optimize and deploy your models
In the AI Services section of this course,
You will learn about a set of pre-trained services that you can directly integrate with your application.
Within a few minutes, you can build image and video analysis applications – like face recognition
You can develop solutions for natural language processing, like finding sentiment, text translation, and conversational chatbots.
Learning algorithms is one part of the story – You need to know how to integrate the trained models in your application.
You will learn how to host your models, scale on-demand, handle failures
Provide a clean interface for the applications using Lambda and API Gateway
Data management is one of the most complex and time-consuming activities when working on machine learning projects.
With AWS, you have a variety of powerful tools for ingesting, cataloging, transforming, securing, visualization of your data assets.
We will build a data lake solution in this course.
Machine Learning Certification
If you are planning to get AWS Machine Learning Specialty Certification, you will find all the resources that you need to pass the exam in this course.
Timed Practice Exam and Quizzes
The source code for this course available on Git and that ensures you always get the latest code
The ideal student for this course is willing to learn, participate in the course Q&A forum when you need help, and you need to be comfortable coding in Python.
Who this course is for:
- This course is designed for anyone who is interested in AWS cloud-based machine learning and data science
- AWS Certified Machine Learning – Specialty Preparation
- Content From: https://www.udemy.com/course/aws-machine-learning-a-complete-guide-with-python/
- Last updated 1/2021