hit93 / sagemaker-flight-prices-prediction

End-to-End Machine Learning using AWS SageMaker Course

Welcome to the AWS SageMaker End-to-End Machine Learning Course conducted in partnership with CampusX! 🚀

This comprehensive course is designed to take you through the entire workflow of implementing a machine learning project using AWS SageMaker. Whether you're a beginner or an experienced practitioner, these 6 sessions will provide you with theoretical and practical knowledge as well as hands-on experience to build, deploy, and manage machine learning models on the cloud.

Relevant Links

• Course
• Web Application
• Course Instructor

Course Overview

• Session 1: Introduction to AWS SageMaker

  • Overview of SageMaker, S3, EC2 & IAM features and capabilities
  • Setting up AWS environment and SageMaker instance

• Session 2: GitHub Setup & Data Cleaning

  • Setting up local & remote repository using GitHub
  • Data Cleaning using Numpy and Pandas best practices

• Session 3: Exploratory Data Analysis

  • Understanding the workflow of systematically analyzing datasets
  • Understanding the various plots, statistical measures and hypothesis tests to analyze datasets

• Session 4: Exploratory Data Analysis (continued)

  • Exploring a custom EDA module for convenience and significantly reduce complexity of analyzing datasets
  • Performing in-depth analysis of various kinds of numeric, categorical and date-time variables
  • Leveraging statistical measures, hypothesis tests, and univariate, bivariate and multivariate plots

• Session 5: Feature Engineering and Data Preprocessing

  • Understanding feature engineering teachniques for different types of variables
  • Creating scikit-learn compatible custom classes and functions
  • Using advanced scikit-learn features for feature engineering and data preprocessing such as:
    • Pipeline
    • Feature Union
    • Function Transformer
    • Column Transformer

• Session 6: Model Training and Deployment

  • Training and Tuning a machine learning model on SageMaker
  • Using S3 buckets for storage and EC2 for computing purposes
  • Creating a web application from scratch and deploying over cloud using Streamlit

Prerequisites

• Familiarity with Python programming language
• Basic understanding of machine learning concepts

Getting Started

To get started with the course, simply clone this repository and follow along with the course sessions and materials provided in each session's directory.

git clone https://github.com/MisbahullahSheriff/sagemaker-flight-prices-prediction.git

Happy learning! 🌟
Hope you enjoy the course 😊