Machine Learning Deployment For Professionals

Machine Learning Deployment For Professionals, available at $49.99, has an average rating of 4.35, with 46 lectures, 4 quizzes, based on 23 reviews, and has 304 subscribers.

You will learn about Learn to deploy your machine learning solutions Learn the process pipeline for machine learning systems Deploy in popular cloud hosting solutions Learn to deploy on Linux and Windows system This course is ideal for individuals who are Anyone who wants to learn to deploy machine learning solutions will find this course very useful It is particularly useful for Anyone who wants to learn to deploy machine learning solutions will find this course very useful.

Enroll now: Machine Learning Deployment For Professionals

Summary

Title: Machine Learning Deployment For Professionals

Price: $49.99

Average Rating: 4.35

Number of Lectures: 46

Number of Quizzes: 4

Number of Published Lectures: 46

Number of Published Quizzes: 4

Number of Curriculum Items: 50

Number of Published Curriculum Objects: 50

Original Price: $39.99

Quality Status: approved

Status: Live

What You Will Learn

Learn to deploy your machine learning solutions
Learn the process pipeline for machine learning systems
Deploy in popular cloud hosting solutions
Learn to deploy on Linux and Windows system

Who Should Attend

Anyone who wants to learn to deploy machine learning solutions will find this course very useful

Target Audiences

Anyone who wants to learn to deploy machine learning solutions will find this course very useful

Want To Master The Skills Behind The Machine Learning Deployment?

This program is designed for the ones who want to learn the art of machine learning model deployment. Through this program, you’ll learn the foundational theories and topics that help to construct machine learning pipelines and machine learning development and deployment lifecycles. Get in-depth knowledge on how to implement a machine learning project to load the data for the evaluation process after testing.

This program includes the must-learn machine learning model deployment patterns like the MlOPS foundation. Also, learn the challenges that you can face with model deployment and mitigation techniques to follow.

Major Concepts That You’ll Learn!

Introduction to machine learning in production
ML and Data lifecycle
ML Pipeline
Deploying ML solutions

This course aims to introduce different aspects of production in the Machine Learning models. It covers pre-requisites of ML deployment, ML Pipelines, challenges involved in the deployment process, and different methods of ML deployment. Finally, the course covers ML deployment solutions such as web service, batch prediction, and embedded models. This program includes all in-demand skills that any machine learning professional should learn.

Perks Of Availing This Program!

Get Well-Structured Content
Learn From Industry Experts
Learn Trending Machine Learning Tool & Technologies

So why are you waiting? Get yourself updated with the latest and in-demand machine learning skills.

Course Curriculum

Lecture 1: Course Introduction

Chapter 1: Introduction to machine learning in production

Lecture 1: Section Overview

Lecture 2: Recap: Implement an ML project

Lecture 3: Patterns of ML Model Deployment

Lecture 4: Deployment Challenges

Lecture 5: What's the solution?

Lecture 6: Output Data Challenges

Lecture 7: Section Summary

Chapter 2: ML and Data lifecycle

Lecture 1: Section Introduction

Lecture 2: Data Lifecycle Overview

Lecture 3: Data Collection

Lecture 4: Data Preparation – Part 1

Lecture 5: Data Preparation – Part 2

Lecture 6: Data Preparation – Part 3

Lecture 7: Data Wrangling

Lecture 8: Data Validation

Lecture 9: Data Storage – Part 1

Lecture 10: Data Storage – Part 2

Lecture 11: Feature Engineering

Lecture 12: Train the model

Lecture 13: Test the model

Lecture 14: Deployment

Lecture 15: Section Summary

Chapter 3: ML Pipeline

Lecture 1: Section Introduction

Lecture 2: Overview of ML pipelines

Lecture 3: Quality assurance and validation for ML models – Part 1

Lecture 4: Quality assurance and validation for ML models – Part 2

Lecture 5: Case studies of ML pipelines in production – Part 1

Lecture 6: Case studies of ML pipelines in production – Part 2

Lecture 7: Case studies of ML pipelines in production – Part 3

Lecture 8: Mapping security and privacy to your pipeline

Lecture 9: Summary

Chapter 4: Deploying ML Solutions

Lecture 1: Section overview

Lecture 2: ML endpoints during deployment

Lecture 3: Windows vs. Linux Deployment considerations – Part 1

Lecture 4: Windows vs. Linux Deployment considerations – Part 2

Lecture 5: Tensorflow extended with Airflow

Lecture 6: Batch prediction with PyTorch

Lecture 7: Streaming Apache Spark

Lecture 8: AWS shadow models

Lecture 9: Embedding ML models

Lecture 10: Flask

Lecture 11: Streamlit

Lecture 12: KubeFlow Theory

Lecture 13: Production quality ML libraries

Lecture 14: Section Summary

Instructors

Eduonix Learning Solutions
1+ Million Students Worldwide | 200+ Courses

Rating Distribution

1 stars: 0 votes
2 stars: 1 votes
3 stars: 3 votes
4 stars: 9 votes
5 stars: 10 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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