AndyTKH / Deep-Learning

Real World Applications of Deep Learning.

Deep-Learning

Deep Learning (DL) is an advanced technique of machine learning (ML) based on neural network algorithm. This technique has found its application in almost every sector of business. Various deep learning models such as convolutional networks, recurrent networks, and GANs are implemented in the projects for trends prediction, image classification, and data generation.

Configure and Manage Your Environment with Anaconda

1. Install miniconda on your computer.

2. Install git for working with Github from your terminal window with command:

   conda install git 
   

3. Clone this repository to your local computer, and navigate to your downloaded folder with command:

   git clone https://github.com/AndyTKH/Deep-Learning.git                                                          
   cd Deep-Learning
   

4. Create and activate a new environment, named the new environment as deep-learning-project with Python 3.6 installed:

   • Linux or Mac:

   conda create -n deep-learning-project python=3.6
   source activate deep-learning-project
   

   • Windows:

   conda create --name deep-learning-project python=3.6
   activate deep-learning-project
   

5. Install latest version of PyTorch and Torchvision:

   • Linux or Mac:

   conda install pytorch torchvision -c pytorch 
   

   • Windows:

   conda install pytorch -c pytorch
   pip install torchvision
   

6. Install the required pip packages, as specified in the requirement text file:

   pip install -r requirements.txt
   

7. Now that you have all the required libraries to run my project, assuming your deep-learning-project environment is still activated, you may now navigate to the specific project directory to view my project from Jupyter Notebook, replace project_directory with the project name directory. To do this, replace project_directory with Image_Classification_CNN_Project for the Image Classification project directory, and subsequently, replace Project_name with Image_Classification to open the specific project in Jupyter Notebook browser:

   cd
   cd Deep-Learning/project_directory
   jupyter notebook Project_name.ipynb
   

8. Simply close the terminal window to exit Jupyter Notebook.