Placement_Prediction

Machine Learning course-based project (CBP) made using Python | Numpy | Pandas | Sklearn | Tensorflow | Streamlit

Basic Setup

• Place the Jupyter Notebook and Datasets in the same folder
• Change the path links of the dataset in the 'read-method' appropriately

Installation

( !pip install <package_name> )

NOTE: type one command in each cell

# Basic
> !pip install scikit-learn
> !pip install pandas
> !pip install numpy
> !pip install matplotlib
> !pip install seaborn

# Other:
> !pip install tensorflow
> !pip install torch
> !pip install torchvision

# To Check installation
> !pip install streamlit
Steps:
(
    type "streamlit hello" to check for streamlit intsall in the terminal
     - Go to --> Anaconda Navigator --> Environments --> Terminal
     - change path to your working directory
     - type > streamlit hello
)

# To Run the file using above terminal
> streamlit run cbp_web.py

Instructions to run

1. Open jupyter niotebook and run the College_Placement_Prediction.ipynb file.
2. After running, check if 'knn_model.pkl' or other .pkl files are in the /Downloads section or your working directory

• (if not present check its path)

3. Go to --> Anaconda Navigator --> Environments --> Terminal Change the path to /Downloads or your working directory.
4. Run 'streamlit run cbp_web.py' command. (Interface Opens in Web browser)

Algorithms Used

• Decision Trees
• Random Forest
• Naive Bayes
• K-Nearest Neighbor Classifier
• Logistic Regression
• Support Vector Machine
• Perceptron
• BackPropagation