Complete Machine Learning Model building and Deployment.

  • 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.
  • Course completion certificate
  • Mode of Study – Self Paced Learning
  • 24/7 support


INR 999

Complete Machine Learning Model building and Deployment.

Section 1: Installation and Configuration


  1. Environment – Virtual BoxConfiguration and Installation


  1. Environment – Docker Installation


  1. Environment Setup – Installation ofjenkins.


  1. Environment Setup – GitLab Installation


  1. Introduction to Flask


Section 2: Part 1 Natural Language processing Programming


  1. Sentiment Analysis introduction anddata set.


  1. Programming Python Flask Web API


  1. Sentiment Analysis Cleaning of data.


  1. Regex to remove username


  1. Punctutaion and body lengthFeatures


  1. Vectorizers and Model Selection


  1. HyperParameter tuning and modelselection


Section 3: Part 2 Programming Python Flask NLP Model


  1. Understanding Templates andWebPages


  1. Importing webpages and mainfunction


  1. Running our flask API


Section 4: Part 3 Introduction to docker commands and Dockerfile


  1. Understating the docker in Nutshell


  1. Writing Dockerfile


  1. GitHub Clone and docker build


Section 5: CI -CD Pipeline and jenkins configuration


  1. Push code to GitLab and makeJenkins freestyle project


  1. Making Jenkinsfile and creatingJenkins pipeline


  1. Configuring CI-CD Pipeline withGitLab webhook and Jenkins


Section 6: Course Completion


  1. Congratulation for your completion

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