AWS SageMaker, AI and Machine Learning

Complete Guide to AWS Certified Machine Learning – Specialty and Practice Test

What you’ll learn

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

Requirements

Familiarity with Python
AWS Account – I will walk through steps to set up one
Basic knowledge of Pandas, Numpy, Matplotlib

Description

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 ***

Benefits

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.

Hands-on Labs

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:

AWS SageMaker

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

AI Services

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.

Integration

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 Lake

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

Source Code

The source code for this course available on Git and that ensures you always get the latest code

Ideal Student

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