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SimplifiedAI

DeepSource DeepSource

Features

----- Main Page -----
1. Project Creation 
2. Data Ingestion (Aws,Gcp,Azure,Local)
3. Project Report 
4. Data Export 

----- ML Life Cycle ------
1. Exploratory Data Analysis API
2. Data Preprocessing API
3. Feature Engineering API
4. Model Training API
   I)  Auto-Matic 
   II) Custom
5. Prediction API
6. Process Scheduling API
7. System Logs
8. History Tracker

Tech Stack

Front End: 
1. Html
2. Css
3. Javascript
4. Jquery

Back End:
1. Python
2. Data Preprocessing Libs(Numpy, Pandas, Matplotlib, Plotly)
3. Linear Regression, Classification , Clustering 
4. Database (MongoDB, Mysql)

Acadamic and Industrial usage

Research :

The web app can the used by the small bussinesses that are incompetent to hire to a Data Analyst/Scientist. The interface 
and functionalities are so simple and straight forward that anyone who can run a computer can easily work on our web app.
The user can upload the data from the provided sources, can perform Exploratory Data Analysis (EDA), Data Preprocessing,
Feature Engineering and can train Machine Learning models. Once the model is trained the user can download all the required
binary files in the form of a zip file for prediction and future usages.

Industrial:

The web app is also equally useful to the people who are working or have the knowledge of Data Analysis, Machine Learning etc.
The user can use our web app to save time and effort in order to analyse the data and train Machine Learning models.

Interface

image image

Documentation

Documentation or Design Architechture

Support

Nothing can be perfect, So if find any bug please let us know!

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