This is the project about initial steps into AI field.

The group works with basis Machine Learning idea like: Gradient Descent, Linear Regression, k-Means... Later on, expand to the field of Computer Vision, Generative Model and basic Transfer Learning.

• Google Colab (either CPU or GPU)
• Numpy
• Matplotlib
• Pygame
• Scikit-Learn
• Pillow
• TensorFlow
• PyTorch

git clone https://github.com/electrodrago/colab-learning.git

• First run the command line below
• cd to the target folder store the file and run

pip install -r requirements.txt
cd colab-learning

ML_basis have 3 directories GradientDescent, K-means and LinearRegression.

• GR_report.py work with Gradient Descent, provide basic code and visualization of how Gradient Descent work.
• linear.py is Gradient Descent approach to solve the problem of Linear Regression.

• xuli.py work with k-Means clustering to find k most density distributions of colors in the image, change the pixels of those exterior points to its related cluster, the result is nearly the same image but reduce the capacity of the image.
• • From:
    
• • To:
    

• parabol.py work with matrix multiplication to fix the best line to the scattered point, use the mechanism of Linear Regression matrix multiplication.
• imglm.py work with images, perform slightly color change adaptive.
• • From:
    
• • To: