AutoCraftML is a machine learning automation platform designed to streamline the entire machine learning pipeline. From data preprocessing to model training and visualization, AutoCraftML automates repetitive tasks, enabling users to develop and deploy machine learning models with ease. Leveraging intuitive interfaces and powerful libraries, it caters to users across various domains, simplifying the complexities of AI and machine learning.

• Artificial Intelligence and Machine Learning
• Web Development
• Education
• Open Innovation

• Dataset: Users can upload a CSV file containing their dataset.
• Data Preprocessing: Missing values are handled using SimpleImputer, and categorical variables are encoded using OneHotEncoder.
• Model Training: Users can select the target variable and choose between classification or regression tasks.
• Data Visualization: Exploratory Data Analytics(EDA) of the dataset using pandas profiling
• Model Visualization: Visualization of Different Machine Learning Models
• Download Model: Functionality to download trained models for later use.

• Streamlit
• Pandas
• deta
• python-dotenv
• Scikit-learn
• PyCaret
• ydata_profiling
• streamlit_pandas_profiling
• streamli-authenticator
• streamlit-lottie

1. Clone The Github repo :

git clone https://github.com/Rjchauhan18/DUhack3.0.git

2. Navigate to Downloaded folder :

cd DUhack3.0

3. Install all the requirements for the project :

pip install -r requirements.txt 

4. Run the app using following command :

 streamlit run Home.py