From d4326979ce06250e4eb658c015576b09a194674d Mon Sep 17 00:00:00 2001 From: Ambarish Singh <105585526+Ambarish-224@users.noreply.github.com> Date: Thu, 21 Dec 2023 22:49:22 +0530 Subject: [PATCH] Update README.md --- README.md | 28 ++++++++++++++++------------ 1 file changed, 16 insertions(+), 12 deletions(-) diff --git a/README.md b/README.md index e79a9c0..9691066 100644 --- a/README.md +++ b/README.md @@ -2,14 +2,18 @@
-Application URL Links : [InsurancePremiumPredictor](https://ambarish-224-insurance-prediction-project.streamlit.app/) +[Linkedin](https://www.linkedin.com/in/ambarish-224/) +[Medium](https://medium.com/@Ambarish_224) +[Github](https://github.com/Ambarish-224)
-## UI of Application :- -

- +## UI of Application:- + +
+ +Application URL Links : [InsurancePremiumPredictor](https://ambarish-224-insurance-prediction-project.streamlit.app/)
@@ -25,12 +29,12 @@ Application URL Links : [InsurancePremiumPredictor](https://ambarish-224-insuran
## About project -Insurance Premium Prediction is an Machine Learning Project which predicts Insurance premium price based on some Input data. +Insurance Premium Prediction is a Machine Learning Project that predicts Insurance premium prices based on some Input data.
## Technologies -This project is created with below technologies/tools/resorces: +This project is created with below technologies/tools/resources: * Python: 3.7 * Machine Learning * Jupyter Notebook @@ -51,16 +55,16 @@ This project is created with below technologies/tools/resorces: ## Setup -To install requirement file +To install the required file ``` pip install -r requirements.txt ``` * Add files to git `git add .` or `git add ` * To check the git status `git status` -* To check all version maintained by git `git log` +* To check all versions maintained by git `git log` * To create version/commit all changes by git `git commit -m "message"` -* To send version/changes to github `git push origin main` +* To send version/changes to GitHub `git push origin main`
@@ -88,7 +92,7 @@ pip install -r requirements.txt
### 2. Data Validation: -* Data validation is an integral part of ML pipeline. It is checking the quality of source data before training a new mode +* Data validation is an integral part of the ML pipeline. It is checking the quality of source data before training a new mode * It focuses on checking that the statistics of the new data are as expected (e.g. feature distribution, number of categories, etc).
@@ -110,8 +114,8 @@ pip install -r requirements.txt
-### 6. Model Deployement -* Deployment is the method by which we integrate a machine learning model into production environment to make practical business decisions based on data. +### 6. Model Deployment +* Deployment is the method by which we integrate a machine-learning model into the production environment to make practical business decisions based on data.