The Intern Academy Tasks repository contains a collection of projects completed during the Data Science and Machine Learning Internship at The Intern Academy in July 2021. These projects showcase the application of Python and Machine Learning concepts in real-world scenarios and provide hands-on experience in data analysis, disease detection, and digit prediction.

1. Titanic Dataset Exploratory Data Analysis (EDA): Analyze the famous Titanic dataset to gain insights into the passengers' information, survival rates, and factors affecting survival. Perform data cleaning, visualization, and statistical analysis to uncover patterns and correlations in the data.

2. Parkinson's Disease Detection: Develop a machine learning model to detect Parkinson's disease based on speech features. Utilize the Parkinson's Telemonitoring Dataset to train and evaluate the model's performance, implementing classification algorithms and feature selection techniques.

3. Handwritten Digit Prediction: Build a machine learning model to recognize and predict handwritten digits. Utilize the MNIST dataset, preprocess the images, and apply classification algorithms to achieve accurate digit recognition. Evaluate the model's performance and visualize the predictions.

the-intern-academy-tasks/
├── titanic_eda.ipynb
├── parkinsons_disease_detection.ipynb
├── handwritten_digit_prediction.ipynb
├── LICENSE
└── README.md

1. Clone the repository:

   git clone https://github.com/sourrinn/the-intern-academy-tasks.git

2. Navigate to the respective project notebooks (titanic_eda, parkinsons_disease_detection, handwritten_digit_prediction) and explore the project notebooks (.ipynb files).

3. Run the notebooks using Jupyter Notebook or any other compatible environment to interact with the code and reproduce the analysis, models, and results.

4. Refer to the README.md files within each project directory for more details on the project setup, and instructions to run the code.

Contributions to the Intern Academy Tasks repository are welcome! If you have suggestions, improvements, or other project ideas related to the internship tasks, please feel free to open an issue or submit a pull request. Let's collaborate and enhance the projects together.

MIT

For any questions, suggestions, or discussions related to the Intern Academy Tasks, please reach out to the repository owner(s) or open an issue in the GitHub repository. Let's continue learning and growing in the field of Data Science and Machine Learning.