Journey of ML Algorithms

Warm welcome to everyone. You are going to join one of the best journey in ML Algorithms.

If you are already a companion of compiler journey then you already know the stop concept in our journey. For those who are joining us first time lets start with the journey manual. In this journey we are going to take a time to time stops. At each stop we are going to learn a machine learning algorithm. Feel free to ask question at any point of time in the journey. For this you can use the comment section present below. I will try to whisper there the answers and if required then we will take a small stop (blog) to properly resolve the query.

In this journey at each stop we are going to either understand Discriminative algorithm or Generative algorithm. Each algorithm may required one or multiple stops.

ML Algorithms
    - Discriminative
        - Classification
            - Logistic Regression
            - Decision Trees
            - Neural Networks
            - SVM
            - k-Nearest Neighbor
        - Regression
            - Linear Regression
            - Decision Trees
            - k-Nearest Neighbor
            - Neural Networks
    - Generative
        - Text Generation
            - RNNs (GRU, LSTM)
        - Image Generation
            - VAE
            - GANs
            - Diffusion Models
            - Autoregressive Models
            - Flow-based Models
        - Audio Generation
            - VAE
            - Autoregressive Models
        - Video Generation
            - Diffusion Models
            - Autoregressive Models

Note: I may update the list time to time as per requirements current world as well as requirements of you as a traveler

Wait but haven't we all learn ML algorithms have mainly 3 types:

1. Supervised Learning

2. Unsupervised Learning

3. Reinforcement Learning

Then why aren't we seeing this kind of type in our journey.

Ok then, I will tell you how exactly ML algorithms are

ML Algorithms
    - Supervised and Unsupervised
        - Discriminative
        - Generative
    - Reinforcement Learning

So, In this journey we are going to learn algorithms one by one and every stop. At some stops we are going to take numerical drinks or coded food so that we can learn not just theory but also what's happening behind it.

🚍 LET'S BEGIN THE JOURNEY TOGETHER.

See you at the next stop, till then stay tuned 😊