BUILD YOUR MACHINE LEARNING Web-App IN MINUTES - Part 5
Welcome to our series! We're going to build a machine learning web app from scratch. Whether you're a pro or a beginner, this series is for you. We'll use tools like Amazon SageMaker, AWS Amplify, and more to make our app shine. Our goal? To teach you the basics of ML focused AWS tools integration and web development, one step at a time. Ready to dive in? Let's get started! Here are few key links:
https://aws.amazon.com
https://www.anaconda.com/download
https://www.kaggle.com/datasets/bsugi...
Support us: paypal.com/donate/?hosted_button_id=6ABQ3FCM9CRF2
Part 5: In this part of our tutorial series, we'll cover the essential steps to create an S3 bucket on Amazon Web Services (AWS). This involves navigating to the AWS Management Console, selecting the S3 service, and initiating the bucket creation process. We'll guide you through defining a unique bucket name, selecting the appropriate storage region, and configuring access permissions. By the end, you'll have a fully configured S3 bucket ready to store your machine learning datasets and model artifacts securely in the cloud, setting the stage for seamless integration with Amazon SageMaker and other AWS services.
To follow along, you’ll need:
*A text editor (such as Notepad or Notepad++)
*An AWS account and access to the Console. Note: You'll need administrator permissions.
*Some basic knowledge of AWS is preferable, but you can still follow along if you’re an absolute newbie.
*Additionally, Microsoft Excel and access to an Anaconda environment for python editor are required.
Below is the complete code and raw data, necessary for constructing the application:
Loan Data file:
https://drive.google.com/drive/folder...
Python program for model evaluation in local machine:
https://drive.google.com/drive/folder...
SageMaker notebook:
https://drive.google.com/drive/folder...
Lambda function file including JSON text file:
https://drive.google.com/drive/folder...
Amplify HTML file:
https://drive.google.com/drive/folder...
#MachineLearning #DataPreprocessing #FeatureEngineering #JupyterNotebook #DataCleaning #DataAnalysis #DataScience #PythonProgramming #DataManipulation #MachineLearningWebApp #AWSIntegration #WebDevelopment #KaggleDataset #InteractiveComputing #PredictiveModeling #DataInsights #DataVisualization #AmazonSageMaker #AWSAmplify #MLTutorial #AIWebApp #CloudComputing #AWSBasics #TechTutorial #AWSDeveloper #AWSLearning #AWSCommunity #AWSUsers #CloudServices #Serverless #AWSLambda #AWSCloud #AWSTools #AWSInfrastructure #AWSConsole #AWSS3 #S3bucket #AWSlambda