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https://github.com/chekoduadarsh/blocklyml
BlocklyML is a simple visual programming Tool for python and ML. 🧩 🖥️
https://github.com/chekoduadarsh/blocklyml
blockly blockly-games deep-learning hacktoberfest javascript machine-learning pycaret python scikit-learn sklearn tensorflow
Last synced: 5 days ago
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BlocklyML is a simple visual programming Tool for python and ML. 🧩 🖥️
- Host: GitHub
- URL: https://github.com/chekoduadarsh/blocklyml
- Owner: chekoduadarsh
- License: apache-2.0
- Created: 2021-05-26T08:29:36.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-08-23T19:58:31.000Z (over 1 year ago)
- Last Synced: 2025-01-26T15:08:29.502Z (5 days ago)
- Topics: blockly, blockly-games, deep-learning, hacktoberfest, javascript, machine-learning, pycaret, python, scikit-learn, sklearn, tensorflow
- Language: JavaScript
- Homepage: https://blocklyml.onrender.com/
- Size: 37.7 MB
- Stars: 449
- Watchers: 9
- Forks: 45
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
BlocklyML is a **No Code** training ground for python and Machine Learning. This tool is designed to simplify standard machine learning implementation.
This tool can assist anyone who wants to start with Machine Learning or python. This is a forked project from [Blockly](https://github.com/google/blockly) and adapted for machine learning and Data analytics use-cases. :brain:
For a sample run go to sampleLayouts folder upload and try it out :smiley:
Read the  for further info
In the Example given below we will train a random forest for Iris Dataset
https://user-images.githubusercontent.com/26855534/174473003-488f675f-50a0-48f1-9ef0-81987bd21166.mp4
# Table of contents
- [Table of contents](#table-of-contents)
- [Installing as BlocklyML App](#installing-as-blocklyml-app)
- [Flask Method](#flask-method)
- [UI Features](#ui-features)
- [Shortcuts](#shortcuts)
- [Dataframe Viewer](#dataframe-viewer)
- [Download Code](#download-code)
- [Contribute](#contribute)
- [This repo welcomes any kind of contributions :pray:](#this-repo-welcomes-any-kind-of-contributions-pray)
- [License](#license)
- [Thanks to](#thanks-to)
# Installing as BlocklyML App
First clone this repo
```shell
git clone https://github.com/chekoduadarsh/BlocklyML
```
After cloning the repo you can either follow the Flask Method
# Running the App Using Docker
If you've cloned the project and want to build the image, follow these steps:
1.Open your terminal and navigate to the project directory.
2.Run the following command to build the Docker image:
```shell
docker build . -t blocklyml/demo
```
Once the image is built, you can launch the app by executing the following command:
```shell
docker run -ti -p5000:5000 blockly_ml/demo
```
This will start the app, and you'll be able to access it by opening your web browser and navigating to `http://localhost:5000`
### Flask Method
Install the requirements from `requirements.txt` with the following command
```shell
pip install -r requirements.txt
```
then you can run the application by
```shell
python app.py
```
Simple as that :man_shrugging:
# UI Features
## Shortcuts
You can find these buttons in the top right corner of the application. Their functionality as follows
1. Download XML Layout
2. Upload XML layout
3. Copy Code
4. Launch Google Colab
5. Delete
6. Run (Not Supported Yet!!)
## Dataframe Viewer
Blockly support complete html view of the DataFrame. This can be accessed by view option in the navigation bar
## Download Code
Blockly support both .py and .ipynb formats. You can download the code from the download option in the navigation bar
# Contribute
If you find any error or need support please raise a issue. If you think you can add a feature, or help solve a bug please raise a PR
### This repo welcomes any kind of contributions :pray:
Feel free to adapt it criticize it and support it the way you like!!
Read : [CONTRIBUTING.md](./CONTRIBUTING.md)
# License
[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)
# Thanks to
[](https://github.com/chekoduadarsh/BlocklyML/stargazers)
[](https://github.com/chekoduadarsh/BlocklyML/network/members)
[](https://www.buymeacoffee.com/chekoduadarsh)