sausolofer / ml-web Goto Github PK

This reposity contains ML projects with Web.

Technology stack

• flask/python, aws, heroku, html, css, bootStrap, javascript, jQuery
• postman, visual code, pycharm, jupyter notebook

1. Project 1 - Model to Predict Employee Retension @ https://tinyurl.com/y6pdv9v5
2. Project 2 - Predict Startup Profits @ https://tinyurl.com/y3c48ou7

Tutorial by ML guru on this @ https://tinyurl.com/y6hpsxqz

A website that predicts the probability of a forest fire taking place based on oxygen,temperature and humidity content Instructions for Pycharm :

1. In project , add the forest html file in the templates folder
2. In the static folder add the css and js file for css js elements to work on webpage.Get it from here : https://materializecss.com/getting-started.html
3. Complete explanation and tutorial on my youtube channel :https://www.youtube.com/watch?v=Pc8WdnIdXZg

Data Science with Harshit @ https://tinyurl.com/y533m3c8

1. Case study: Fuel Consumption
2. End to End Machine Learning Project on Fuel Consumption Prediction of 70s and 80s vehicles.

Technology and datasets:

1. Flask, Heroku, Jupyter Notebook, Sci-kit learn, Pandas
2. Datasets: http://archive.ics.uci.edu/ml/datasets/Auto+MPG

Tutorials

1. End-to-End Machine Learning Project Tutorial - Part 1
2. Data Preparation with Sci-kit learn and Pandas - Part 2
3. Training and Fine-Tuning ML Models with Sklearn - Part 3
4. Deploying a Trained ML model via Flask on Heroku - Part 4

Code

Jupyter Notebook for ML model : https://tinyurl.com/y5r4keuk

1. Tutorial by ML guru on this @ https://tinyurl.com/y6hpsxqz
2. Dataset Used: https://www.kaggle.com/quantbruce/real-estate-price-prediction/download

Excellent tutorial Series by Dhaval Patel (Codebasics) Tutorial Series link - https://tinyurl.com/yxobwajo

Tutorial Series:

1. Tutorial 1: General introduction of the case study
2. Tutoral 2: Data Collection (google image, plugin- Fatkun, Web scraping)
3. Tutorial 3: Data Cleaning, Idenfying face using OpenCV (haar cascade), manual
4. Tutorial 4: Feature Engineering
5. Tutorial 5: Model training
6. Tutorial 6: Flask Server
7. Tutorial 7: UI
8. Tutorial 8: Deployment

Here is the video playlist for entire project: https://www.youtube.com/playlist?list=PLeo1K3hjS3uvaRHZLl-jLovIjBP14QTXc

@ https://tinyurl.com/y5xjt5wu

Tutorial Series

1. Predicting Year of Marriage - End to End Machine Learning Deployment with FLASK and AWS -PART 1 @ https://tinyurl.com/yxrgm7ks

2. Predicting Year of Marriage - End to End Machine Learning Deployment with FLASK and AWS -PART 2 @ https://tinyurl.com/y6mcutlx

Simple application with authentication and CRUD functionality using the Python Flask micro-framework

Tutorial by Dhaval Patel (Codebasics) : https://tinyurl.com/y56d7g8y

Tutorial Series by Total Data Science @ https://tinyurl.com/yyja24z2

The objective of this project is

1. to perform extensive Exploratory Data Analysis(EDA) on the Zomato Dataset.
2. to build an appropriate Machine Learning Model that will help various Zomato Restaurants to predict their respective Ratings based on certain features DEPLOY the Machine learning model via Flask that can be use…

In this python project, we will build a grocery store management application. It will be 3 tier application,

Credit: https://github.com/Mandal-21/Flight-Price-Prediction

1. Tutorial by Krish Naik @ https://www.youtube.com/watch?v=p_tpQSY1aTs
2. Repo: https://github.com/krishnaik06/Car-Price-Prediction

1. Repo: https://tinyurl.com/ycau5c5e
2. youtube: https://tinyurl.com/yc97to6y

1. ML/DL Model Deployment Architecture Using API's: https://tinyurl.com/yb7255py

2. ML/DL Model Deployment Architecture Using TFLite : https://tinyurl.com/ycbeyg4u

3. Premises VS IAAS (e.g., AWS, Azure) vs PAAS cloud Platforms: https://tinyurl.com/y7xakovs

4. Deployment of ML models in Heroku using FLASK: https://tinyurl.com/yc5652j7

   Github Repo: https://github.com/krishnaik06/Heroku-Demo

5. Deployment of NLP Model in Heroku Cloud: https://tinyurl.com/y8e4ebod

   Github Repo: https://github.com/krishnaik06/NLP-Deployment-Heroku

6. Deployment Of ML Models In AWS EC2 Instance: https://tinyurl.com/yckfg8ls

7. Deployment of ML Models in GCP: https://tinyurl.com/y8gchs34

   Github Repo: https://github.com/krishnaik06/Google-Cloud-Platform-Deployment

8. Deploying ML Models In Azure: https://tinyurl.com/ybh2nfrp

   Github Repo: https://github.com/krishnaik06/AzureDeployment

1. github repo: https://github.com/dis-is-pj/Movie-Recommender-System
2. Youtube video by Krish Naik: https://tinyurl.com/y73mdx74

1. Keywords: Image classification, TF, DL, flask, keras, transfer learning, restnet50
2. Keywords: ImageNet DataSet, computer vision
3. Video: https://www.youtube.com/watch?v=Ie4-AOpPxBg
4. Repo: https://github.com/krishnaik06/Deep-Learning-Car-Brand

1. Keywords: Image classification, TF, DL, flask, keras, transfer learning, restnet50
2. Keywords: ImageNet DataSet, computer vision
3. Video: https://www.youtube.com/watch?v=H-bcnHE6Mes
4. Repo: https://github.com/krishnaik06/Malaria-Detection

1. Keywords: Image classification, TF, DL, flask, keras, transfer learning, restnet50
2. Keywords: ImageNet DataSet, computer vision
3. Video: https://www.youtube.com/watch?v=-vDwY1kOfNw
4. Repo: https://github.com/krishnaik06/Tomato-Leaf-Disease-Prediction

1. Keywords: Image classification, TF, DL, flask, keras, transfer learning, restnet50
2. Keywords: ImageNet DataSet, computer vision
3. Video: https://www.youtube.com/watch?v=-vDwY1kOfNw
4. Repo: https://github.com/krishnaik06/Cotton-Disease-Prediction-Deep-Learning

• Description: This is for a doctor, which upload x-ray images to identify a disease (e.g., Pneumonia)

1. Keywords: signin, payment, image classification, healthcare

2. Video: https://tinyurl.com/ya8b3ruv

3. Repo: https://github.com/pankeshpatel/AI_Startup_Prototype

4. Flask + Stripe + User Registration + DB

   • Flask-Stripe Repo by mjhea0: https://github.com/pankeshpatel/flask-stripe

5. flaskSaaS by alectrocute

• A great starting point to build your SaaS in Flask & Python, with Stripe subscription billing.
• Repo: https://github.com/pankeshpatel/flaskSaaS

7. Upload functionality by bboe
   • A simple flask app that runs on heroku and demonstrates HTTP Server-Sent Events (EventSource) protocol.
   • Repo: https://github.com/bboe/flask-image-uploader

• Steps

1. Step 1 List Personal Problems
2. Step 2 Market Research (competing products)
3. Step 3 Buy Domain (e.g., GoDaddy)
4. Step 4 Create Landing Page
   • logo - www.brandmark.io,
5. Step 5 Share Landing Page
   • Landing page - www.mailchimp.com
6. Step 6 Create Business Plan
7. Step 7 Design Pipeline
   • User Authentication (SQL)
   • Database (SQL)
   • Payment (Strip)
   • Uploads (Flask Native)
   • Inference (Keras)
8. Step 8 Transfer Learning (!)
9. Step 9 Create Web App
10. Step 10 Deploy!