This project showcases exercises and code I have learned from the Deep Learning A-Z course. The content is primarily focused on deep learning techniques, concepts, and practical implementation.
The following technologies are used in this project:
- R Studio
- Python
- Jupyter Notebook
- Machine Learning
- Data Mining
- Data Visualization
- Business Analytics
- R CRAN Project: A free software environment for statistical computing.
- RStudio IDE: A powerful IDE for R, offering features like code execution, debugging, and workspace management.
- Jupyter Notebook: A web-based application for creating and sharing live code, visualizations, and text.
- Anaconda Navigator: A desktop interface for managing Python and R projects, including package management and environment setup.
Steps to set up the development environment:
- Install R: Install R for statistical computing.
- RStudio IDE: Install RStudio as your primary IDE for R.
- Anaconda Navigator: Install Anaconda Navigator to manage Python or R environments.
- Jupyter Notebook: Use Jupyter Notebook for coding and testing in Python.