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UdemyMachine LearningPaid courseIntermediate levelCertificate

A to Z (NLP) Machine Learning Model building and Deployment. (Udemy.com)

Python, Docker, Flask, GitLab, Jenkins tools and technology used for deploy model in your Local server. A complete Guide

4.1
162 reviews

Created by: Mohammed Rijwan

Last updated August 2023

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What you will learn

  • Developing the NLP Model for Sentiment analysis and Machine learning deployment on local server using flask and docker.
  • Select the most efficient Machine Learning Model,Tune the hyper-parameters and selecting the best model using cross-validation technique
  • A quick discussion from the basic in nutshell about DevOps tools like docker, Git and GitLab, Jenkins etc.
  • A better understanding about software development and automation in real scenario and concept of end-to-end Integration.

How it compares

Against the other 155 rated Udemy courses in Machine Learning on CourseDuck:

  • Rating4.1 out of 5higher than 20% of them
  • Reviews162#112 of 156 by number of reviews
  • Length4.9 hoursshorter than 65% of them
  • Last updatedAugust 2023more recently than 52% of them

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Course Description

Machine Learning Real value comes from actually deploying a machine learning solution into production and the necessary monitoring and optimization work that comes after it.

Most of the problems nowadays as I have made a machine-learning model but what next.

How it is available to the end-user, the answer is through API, but how it works?

How you can understand where the Docker stands and how to monitor the build we created.

This course has been designed to keep these areas under consideration. The combination of industry-standard build pipeline with some of the most common and important tools.

This course has been designed into Following sections:

1) Configure and a quick walkthrough of each of the tools and technologies we used in this course.

2) Building our NLP Machine Learning model and tune the hyperparameters.

3) Creating flask API and running the WebAPI in our Browser.

4) Creating the Docker file, build our image and running our ML Model in Docker container.

5) Configure GitLab and push your code in GitLab.

6) Configure Jenkins and write Jenkins's file and run end-to-end Integration.


This course is perfect for you to have a taste of industry-standard Data Science and deploying in the local server. Hope you enjoy the course as I enjoyed making it.
Read More Intermediate Intermediate Level product length iconTime: 4.9h

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Instructor Details

Mohammed Rijwan

Hi, I am a working professional having experience in fields like ML, AI, DevOps tools like Docker, Jenkins, Git or GitLab, Python, C, C++, etc. I have worked in a much different organisation as a tech trainer and currently working as a Big Data and Machine Learning Engineer. My aim is to spread the knowledge which is an industrial standard and help you to find a better geek in you which will help you to make very robust projects which are highly in demand in the industries. I am sure my courses will help you to achieve your goals. Please visit my YouTube channel for more info. Cheer! Happy learning :-)

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Reviews

4.1

162 ratings on Udemy

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By Alan Beckles on 8/26/2021

Multiple benefits thus far include creating a Linux environment on top of your machine’s operating system.

By Anthony DiDonato on 11/13/2020

The intent of the content was intriguing however; it was hard to follow because it seemed to lack structure. The audio was sporadic. If you have basic experience with these tools, you will get through it and find value. Overall the quality of the training delivered and the structure need some work. In the end if you want to understand how to take your ML model to deployment. That mission could be accomplished. Patience was required to sit through every section.

By Nowshad Shaik on 6/26/2020

It's a good course for those who are looking for the NLP Machine learning model building.

By Ekjot Kaur on 6/25/2020

very informative and very detailed. Good for both freshers and experienced :)

By Aishwarya Malgonde on 5/18/2020

Better structuring of the course is required. Also the teacher is not able to articulate when he tries to explain. But I got to learn about Jenkins and how to integrate it with our flask api so it was ok. Wouldn't have paid for this course

By Erjan Kenjegalee on 2/5/2020

nice, but typos make the overall impression weak.. sorry , the content is pretty good and the course is short - only 3.5h. fix typos!

By Sandeep Panchal on 1/13/2020

Firstly, I thank the instructor Mohammed Rizwan for providing this good beginner course for free. The instructor had nicely explained that is easy to understand. A very good course to begin the ML models (NLP) deployment. Just one suggestion- It will be very much helpful if this course contains 2 or 3 more models deployed with different scenarios.

By PALAKOLANU SREEKANTHA REDDY on 12/29/2019

Great experience. End to End development and deployment concepts are explained. Thank you very much. Expecting another course on Django deployment.

By Shivender Khajuria on 12/15/2019

The instructor could have mentioned how to setup Jenkins user Id and password in the setup videos .

By Ameya Bapat on 12/15/2019

i have completed this course few days back , and it helped me a lot in my undergoing projects , the way real time problems are simplified is totally awesome , i suggest everyone to must undergo this course . Thanks instructor for great knowledge.

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Overall Score : 82 / 100

A to Z (NLP) Machine Learning Model building and Deployment.
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  • Video Duration: icon 4.9h
  • Price: $49.99
  • Provider: icon Udemy
  • Updated: icon August 2023
  • Level: Intermediate Intermediate
  • Language: icon English
  • Certificate: icon Yes
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