Description
Course A to Z (NLP) Machine Learning Model building and Deployment. Machine Learning The real value comes from deploying a machine learning solution in production and monitoring and the necessary optimization work that follows. Most of the problems today are because I’ve built a machine learning model, but what’s next. How is it available to the end user, the answer is via API, but how does it work? How can you find out where Docker is and how can you monitor the build we created. This course is designed to keep these areas in mind. A combination of the industry standard build pipeline with some of the most common and important tools. This course is designed in the following sections:
1) Configuration and quick review of each of the tools and technologies we used in this course.
2) Building the NLP machine learning model and setting meta-parameters.
3) Creating flask API and running WebAPI in our browser.
4) Build your image and run your ML model in a Docker container by creating a Docker file.
5) Configure GitLab and push your code to GitLab.
6) Configure Jenkins and write the Jenkins file and run the end-to-end integration.
This course is suitable for you to enjoy industry standard data science and local server deployment. I hope you enjoy the course as much as I enjoyed making it.
What is in the A to Z (NLP) Machine Learning Model building and Deployment course. you will learn
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Development of NLP model for sentiment analysis and deployment of machine learning on local server using Flask and Docker.
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Select the most efficient machine learning model, adjust the above parameters and select the best model using cross-validation technique.
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A quick discussion of the basics in brief about DevOps tools like docker, Git and GitLab, Jenkins etc.
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Better understanding about software development and automation in real scenario and concept of end-to-end integration.
This course is suitable for people who
- Beginner machine learning enthusiasts want to implement their own model.
- Beginner Python developer curious about data science.
- Anyone wants to learn Devops and the role of DevOps in data science.
Specifications of A to Z (NLP) Machine Learning Model building and Deployment course.
- Publisher: Udemy
- teacher: Mohammed Rijwan
- Training level: beginner to advanced
- Training duration: 4 hours and 56 minutes
- Number of courses:
Course headings
Course prerequisites
- Basic programming in any language
- Some exposure to Python (but not mandatory)
Course images
Sample video of the course
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
download link
File(s) password: www.downloadly.ir
Size
2.1 GB
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