No-Code Machine Learning Model Building Platform

Welcome to the No-Code ML Model Building Platform! This platform enables users to perform data cleaning, transformation, visualization, and machine learning model building without writing any code. Link - NoCodeML

Features

1. Data Upload and Display

• Upload your dataset in CSV format.
• View and explore the data directly in the app.

2. Data Cleaning

• Handle missing values:

  • Drop rows with missing values.

    

  • Impute missing values using mean, median, or mode.

    

• Replace values in columns.

  

• Change column data types.

  

• Detect and remove outliers using:

  • Interquartile Range (IQR)
  • Z-Score

  

• Download Cleaned Data as CSV:

  

3. Data Analysis and Visualization

• Unique Values: Explore unique values for selected columns.

  

• EDA (Exploratory Data Analysis):

  • Univariate Analysis: Visualize single-variable distributions.

    

  • Bivariate Analysis: Analyze relationships between two variables.

    

  • Multivariate Analysis: Correlation matrix and heatmaps.

    

• Feature Importance:

  • Calculate feature importance using methods like Random Forest, Chi-Square, ANOVA F-value, Point Biserial Correlation, and Mutual Information.

    

    

4. Data Preparation for Modeling

• Drop irrelevant columns.

  

• Split data into train and test sets.

  

• Normalize numerical data and encode categorical data using:

  • Label Encoding

  • One-Hot Encoding

  • Ordinal Encoding

  • Standard Scaling

  • Min-Max Scaling

    

• Handle class imbalance (coming soon).

• Perform dimensionality reduction (coming soon).

  

5. Machine Learning Model Building

• Model Training:

  • Choose between classification or regression tasks.

  • Supported algorithms include Logistic Regression, Random Forest, Gradient Boosting, Support Vector Machines, and more.

    

• Model Testing:

  • Evaluate trained models on test data.

  • Download trained models as pickle files.

    

6. Notes and Downloads

• Take notes directly in the app.
• Download cleaned data, transformed data, models, and notes.

Getting Started

1. Clone the repository:

   git clone https://github.com/Dhruv-Limbani/NoCodeML.git

2. Install the required Python dependencies:

   pip install -r requirements.txt

3. Run the app:

   streamlit run app.py

4. Open the app in your browser and upload your data to get started.

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