pip install numpy
pip install opencv-python
pip install dicom
pip install pydicom
pip install scipy
pip install scikit-image
pip install torch
pip install torchvision

- Intro to Python Notebooks
- Intro to Python
- Intro to Numpy
- Intro to Image Processing ( OpenCV )
    - Importing and
    - Chroma Keying
    - To be Done - Frequency Histogram
    - To be Done - Thresholding

- Sobel Filters
- Bar Code Detection and Scanning
- Learning about EAN-13 Barcode System
- Thresholding Methods
    - Global Threshholding (using same threshold for all pixels)
    - Adaptive Threshholding (using different threshold for different pixels)

- HW
    -Find seed fill algorithm (similar to DFS)
    - Sobel Filters

- Intro to Document Imaging
- Hands-on Task
    - Canny Edge Detection
    - Hough Line Transform
    - Skew Correction
        -(Not aligned with the horizontal axis)
        - Correction by Rotation
        - Rotation of a document image from its intended orientation
        - Reduces the acuracy of OCR
    - Line And Word Detection
    - Reading Check Number

    - HW : try root(sobelX^2 + sobel^2) and compare with Canny
    - Non-Maximal Suppresion

- Understanding the nomeclature of a cheque
- Smoothing techniques
- Removing noise and borders
- Intro to OCR (by template matching)
- Sobel Filters
- Black Hat Transform

- Intro to Convex Optimization
- Using CVXOPT library
- Solving Knapsack Problem
- Smoothing graph using Convex Optimization
- Realtime Application of smoothing boxes in video

- Windowing for different parts of the body
- Parallel Beam Tomographic Reconstruction using Simple Backprojection

- Intro to 3D
- PyMesh
- Open3D
- ICP

- Blender

- Basics of ML
- K- Nearest Neighbours
- K-Means Clustering
    - Distance Metrics

- Linear Decision Boundaries
    - Loss function 
    - Minimizing the loss fucntion with respect to the parameters (weights)
    - Gradient Descent
        - Different Loss Functions for Gradient Descent


- Neural nets
    - Basics

- Formula for neural nets $\sum_{i=1}^n(w_ix_i + b)$
- Activation Functions

- Classifier for a small dataset
- Face detection
- Face Recognition

- Basics of Research (more on notion page)

- Intro to experiment tracking with W&B
    - Basics
    - Sweeps
    - Other features
- Multi- threading and multi-processing using concurrent.futures
- Image captioning
    - Multi-modality

- Intro to Conv Nets
    - Basics
    - Convolutions
    - Different Architectures
    - Hands-on with MNIST
- Play learning rate, batch size, different datasets