Machine Learning with AWS

Machine Learning with AWS, available at $49.99, has an average rating of 3.3, with 55 lectures, based on 56 reviews, and has 808 subscribers.

You will learn about Amazon Sagemaker to build, train, and deploy machine learning models at scale Amazon Comprehend for natural Language processing and text analytics Amazon Lex for conversational interfaces for your applications powered by the same deep learning technologies as Alexa Amazon Polly to turn text into lifelike speech using deep learning Object and scene detection,Image moderation,Facial analysis,Celebrity recognition,Face comparison,Text in image and many more Amazon Transcribe for automatic speech recognition Amazon Translate for natural and accurate language translation This course is ideal for individuals who are Anyone who is curious to experiment with Artificial Intelligence and develop applications or simply interested in exploring AWS Machine Learning and its powerful services available on AWS Cloud. It is particularly useful for Anyone who is curious to experiment with Artificial Intelligence and develop applications or simply interested in exploring AWS Machine Learning and its powerful services available on AWS Cloud.

Enroll now: Machine Learning with AWS

Summary

Title: Machine Learning with AWS

Price: $49.99

Average Rating: 3.3

Number of Lectures: 55

Number of Published Lectures: 55

Number of Curriculum Items: 55

Number of Published Curriculum Objects: 55

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Amazon Sagemaker to build, train, and deploy machine learning models at scale

Amazon Comprehend for natural Language processing and text analytics

Amazon Lex for conversational interfaces for your applications powered by the same deep learning technologies as Alexa

Amazon Polly to turn text into lifelike speech using deep learning

Object and scene detection,Image moderation,Facial analysis,Celebrity recognition,Face comparison,Text in image and many more

Amazon Transcribe for automatic speech recognition

Amazon Translate for natural and accurate language translation

Who Should Attend

Anyone who is curious to experiment with Artificial Intelligence and develop applications or simply interested in exploring AWS Machine Learning and its powerful services available on AWS Cloud.

Target Audiences

Anyone who is curious to experiment with Artificial Intelligence and develop applications or simply interested in exploring AWS Machine Learning and its powerful services available on AWS Cloud.

Machine learning engineer and data scientist are the two hottest jobs of 2020. To grab this job opportunity one should apply machine learning skills to solve complex problems of the real world.

Here in this course you’ll going to learn various machine learning services provided by Amazon AWS and able to kick start your career. Anyone can enroll this learning path whether you’re fresher or experienced.

This course is technology-driven will help you in seeking a lucrative job in machine learning domain. Enroll this course and showcase your skill set  to the world.

In this learning pathway, you’ll able to use Amazon AWS fundamental services and also integrate them in your Web, Android, IoT and Desktop Applications

Machine Learning Services of AWS which you’ll deploy on  the AWS cloud are:

Amazon Sagemaker to build, train, and deploy machine learning models at scale

Amazon Comprehend for natural Language processing and text analytics

Amazon Lex for conversational interfaces for your applications powered by the same deep learning technologies as Alexa

Amazon Polly to turn text into lifelike speech using deep learning

Amazon Rekognitionhas a wide range of features like Object and scene detection, Image moderation, Facial analysis, Celebrity recognition, Face comparison, Text in image and much more

Amazon Transcribe for automatic speech recognition

Amazon Translate for natural and accurate language translation

As mentioned earlier, this course is industry oriented, therefore it has lots of lot projects which helps you in applying machine learning skills. There is a section, completely focuses on AWS AutoML if you think that you’re newbie, don’t know how to ML algorithms. Don’t worry for such scenario, AutoML plays a vital role. It will help you to job done in autopilot mode. Other than this you’ll also learn to develop your chatbot and virtual assistant for your sites, helping your customers 24*7.

For Python Developers, who want to apply their machine learning skills on a higher scale than why to waste money on buying the resources. Use the power of cloud computing and implement all your machine learning skills with the help of Boto3, a python framework for managing AWS cloud services.

All the best !!!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Difference between AI and Machine Learning

Chapter 2: Quick Summary of all AWS Machine Learning services

Lecture 1: AI services [No machine learning skill]

Chapter 3: Quick Recap

Lecture 1: Quick Recap – NUMPY

Lecture 2: Quick Recap – Pandas

Chapter 4: NLP Project

Lecture 1: Build frontend for ML Application

Lecture 2: Build Backend for ML Application

Lecture 3: Add NLP task (translation)

Lecture 4: Demo: Translation ML app

Lecture 5: Creating Sentiment Analysis ML app

Lecture 6: Demo: Sentiment Analysis ML app

Lecture 7: POS tagging ML App

Lecture 8: Detect entity

Chapter 5: Amazon Comprehend

Lecture 1: Amazon Comprehend

Lecture 2: Practical:Amazon Comprehend

Lecture 3: (PythonBoto3)Comprehend 1

Lecture 4: (PythonBoto3)Comprehend 2

Lecture 5: (PythonBoto3)Comprehend 3

Chapter 6: Amazon Lex and Amazon Polly

Lecture 1: Amazon Lex

Lecture 2: Amazon Lex 2

Lecture 3: Amazon Polly

Lecture 4: Practical:Chatbot using Amazon Lex

Lecture 5: Practical:Amazon Polly

Lecture 6: (PythonBoto3)Polly

Chapter 7: Amazon Rekognition

Lecture 1: Amazon Rekognition

Lecture 2: Object and scene detection(Overview)

Lecture 3: Object and scene detection(Practical)

Lecture 4: (PythonBoto3)Detect Label

Lecture 5: Facial analysis(Overview)

Lecture 6: Facial analysis(Practical)

Lecture 7: (PythonBoto3)Detect Face

Lecture 8: Celebrity recognition(Overview)

Lecture 9: Celebrity recognition(Practical)

Lecture 10: (PythonBoto3)Celebrity Recognition

Lecture 11: Face comparison(Overview)

Lecture 12: Face comparison(Practical)

Lecture 13: (PythonBoto3)Face Comparison

Lecture 14: Text in image(Overview)

Lecture 15: Text in image(Practical)

Lecture 16: (PythonBoto3)Detect Text in Image

Lecture 17: Visual Analysis

Chapter 8: Amazon Transcribe and Translate

Lecture 1: Amazon Transcribe

Lecture 2: Amazon Translate

Lecture 3: Practical:Amazon Transcribe

Lecture 4: (PythonBoto3)Transcribe

Lecture 5: Practical:Amazon Translate

Lecture 6: (PythonBoto3)Translate

Chapter 9: Amazon SageMaker and AWS DeepLens

Lecture 1: Amazon SageMaker

Lecture 2: AWS DeepLens

Chapter 10: Machine Learning(Using Amazon ML to Predict Responses to a Marketing Offer

Lecture 1: Amazon Machine Learning(Overview)

Lecture 2: ML 1 -Prepare Your Data

Lecture 3: ML 2-Create a Training Datasource

Lecture 4: ML 3-Create an ML Model

Lecture 5: ML 4-Use the ML Model to Generate Predictions

Lecture 6: ML 5-Clean Up

Instructors

Pranjal Srivastava
Docker | Kubernetes | AWS | Azure | ML | Linux | Python

Rating Distribution

1 stars: 9 votes

2 stars: 3 votes

3 stars: 5 votes

4 stars: 8 votes

5 stars: 31 votes

Frequently Asked Questions

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